Your comment was likely focused on dysfunctional parts of the culture there (and that seems to be how most replies to you interpreted it as well). There's truth to that, sure. But I think respect for data sensitivity and security is also a big part of what makes the culture ill-suited for frontier AI lab work.
When I was at AWS, we had data access locked down very tightly. I was trying to train a model to predict how long various dynamic workloads running on behalf of customers would take. Just getting access to anonymized production data from a DB that my team owned took well over a month and had me compromise heavily on what attributes I could access. I also spent a decent amount of time in meetings with lawyers and compliance folks to explain and justify all our data classifications for PII, retention, access controls, etc. We would review our data policies quite frequently. We needed break-glass procedures to access prod data in our own systems, and it was uncommon to need to resort to that. Even when you broke glass, certain classes of sensitive data would still not be visible to you. On the plus side, We did get quite good at operating and maintaining systems without needing to see sensitive info.
If you contrast that with Meta's disregard for privacy or the way frontier labs disregard the law, it's easy to see why Amazon would struggle in this space.
I read your comment as “amazon acts too responsibly to be a frontier lab,” and that worries me. That they even bothered to do all that stuff is good. That others don’t is bad.
I did indeed mean it that way, but I agree with you. It sucks, but it's just the unfortunate reality of the world. Many of the most disruptive and successful startups made it there by ignoring legal or moral limitations.
Frankly reading your comments was a relief. I'd rather they take my privacy (and security) seriously. I don't need or want any AI features or technology from Amazon, thanks very much.
Amazon has a history of fostering off-shoot companies that are given more freedom to innovate[1][2]. Keeping AI development in-house under Bedrock was probably their mistake. There's a big difference between running AI and developing new AI models.
Their core selling point is customer trust that their product works as advertised.
From my interactions with them, is that they really care about customer success, and everything including AI is a means to an end to them.
I think building a cool product with undefined reliability and capabilities, then selling fantasies about what it will possibly be able to do down the line isn't really what they do - or what their customers are paying for.
I agree, from my personal experience. AWS support at most tiers I’ve used is excellent. Granted, the larger account you have, the friendlier the service, but even when using it for smaller personal projects, I’ve always been pleased with the level of support and devotion to customer experience (except the console experience, that is not fun).
Don’t know to comment about the other areas of their business but AWS has always been excellent for me.
Incentives can produce locally rational and globally harmful behavior. (See also: "Moloch", although I'm less of a fan of the concept lately since it focuses exclusively on the harmful aspects of emergent systems, deleting the neutral and positive ones in the process.)
A relevant metaphor is the nuclear arms race. Nobody wants a world full of nukes pointed at each other, but if the other guy is gonna do it...
The argument in this case is, we can't slow down, because China certainly won't, and do you want those guys to build the machine God first? So it's "rational" to maximize p(accidental_skynet).
I interned there for a summer working on evaluating text generation and despite the fact that I used no consumer data whatsoever, but rather a well-known public research dataset, I also couldn't egress from the machines I ran training on. Not even reports on the training (admittedly, this was 2021 when they had just introduced this new system). So it was even more of a damper on research progress than you might imagine.
People, usually starting from scratch (0 to no seed funds), immigrating to the US from communist countries and becoming financially stable at the minimum, often times building muiltimillion dollar empires and less often, muiltibillion dollar empires. ChatGPT/Claude/Gemini/Grok will give you well researched datapoints that you will be able to follow up on yourself.
I can suggest a prompt that will report how many founders part of Y-Combinator, who came from nothing, some immigrants from communist countries, have become ridiculously successful.
Have you tried to start a business in Pakisthan, Russia, Cuba or China as an outsider? Even with a few thousand dollars as seed? Do you want to buy a house in Pakisthan, Russia, Cuba? Do you want to study there?
... but you didn't answer my question, and I have yours.
this is arguably why he is the way he is: NYC high society mocked him to his face.
a lot of his "burn it down, fuck em" attitude stems from that.
he is, however, completely and utterly narcissistic and greedy, and smart rich people are able to play him like a fiddle.
the KGB picked up on that in, like, the 80's, after Ivana's dad -- an informant for the Czechoslovakian secret police -- passed on details of their relationship to the Czech internal security
Too bad they died off, those were the captains of industry in the 20th century, it was tragic to see them go.
Now it's even more tragic with huddles built from captains of non-industry, "monetizing" rather than producing.
If a consumer recovery is going to happen, what is it being produced that the bottom 10% is going to consume where they can get their money's worth if nothing in the affordable tier qualifies any more? A greater number of people across the board need to get their money's worth on almost everything like never before seen during so many peoples' lifetime at this point.
I liked it better when Trump-like character was almost universally recognized as nothing other than a mindless financial squanderer wrapped around an inherently dishonest core. This was voiced most strongly especially among the rich and powerful.
They used to know better, but that was then and these are not them.
Which has nothing to do with Amazon. Except for the way the political party which leveraged Reaganomics in the 20th century to the effect that average consumers would eventually no longer be able to afford anything other than Chinese-made products, turned out to be the same party which fell behind Trump in the 21st century as if his financial acumen was't completely non-advanced.
And just as consumer prices of the Chinese mass-produced goods continued to fall as desperately needed by consumers due to direct purchase from China, Trump halts that so there's more need to go through Amazon, they can maintain more control that way.
What does that have to do with anything? And still, so what?
Do the rich hate him because he exploits the working class? Because they think the way he got rich is obscene? No! It's because he won't shut up, and says the quiet parts out loud. They only hate his personality. You would know if they hated his policies, which they don't, because he'd be out on his senile ass before you could say dementia.
> That they even bothered to do all that stuff is good. That others don’t is bad
good and bad isn't what Meta and AWS is running with. If AWS trains willy nilly on user data like Meta does, AWS is toast. AWS is already taking a huge risk by now using their own take of AWS FDEs competing against their established ecosystem of consulting companies that used to recommend all 583 of AWS products to host a static webpage. Turning of more customers by training on their data is too much of a risk. That's the "good" - a risk analysis.
Meta doesn't care if you stop using Facebook, Whatsapp etc. Frankly, if you are embedded in the Facebook, Whatsapp ecosystem, you don't have a way out as a normie. Even if you are technically capable, good luck publishing your custom Mattermost build for iOS.
Meta has a significant amount of investment in hardware, originally due to Metaverse. The way to monetize that investment is inference and training. That's a do or die decision for Meta. Meta isn't releasing open-weight models because they are "good".
Meta is releasing open-weight models for the same reason Alibaba, NVIDIA or IBM does. Or Google releases Gemma.
There's no "good" or "bad" - the moment Alibaba, NVIDIA, IBM or Google's objective functions change, "Do no evil" will quickly morph into "Do as much evil as necessary without the costs of getting caught exceeding E(outcome)"
That explains a lot. They are anti “move fast and break things” which is great news for enterprises or anyone seeking stability but terrible for innovation.
I don’t condone the use of pirated content for training. But anything that was bought is above the board as far as I’m concerned. Can let the lawyers fight out the minutia and inevitable licensing specifics after the fact (book publishers are hawks).
Fun fact, did you know that every library in the world has an independent contract with every major book publisher?
In cases I am familiar with, they added a condition that a physical book can only be lent X times. After that, the library must purchase a new copy (even if the original copy is in pristine condition). Yeah, hawks.
What you are citing appears to me as a business use case of classical machine learning models not necessarily LLMs, and demand forecasting. Frontier AI is clearly not dependent on such data, and has many outside data sources and I'm even sure sensitive AWS data would be of good use as training data, not to mention the legal/contractual obligations AWS has in protecting that data, what am I missing?
That was just an example anecdote to highlight the culture around respecting privacy and security. Obviously AWS would never allow for training on customer data, but even for metadata or data of our own internal systems, things are super strict.
Public datasets that are liberal with licensed access is one thing, but the best frontier labs clearly went well beyond that.
this. the culture that makes AWS the gold standard in cloud security (yes, it is still the best in the business despite the one-off embarrassing CapitalOne incident) with a strong emphasis on locking down data, minimizing PII, and saying “no” by default, is the very opposite of what building frontier LLMs is all about, which is really around hoovering up vast amounts of other peoples data and moving fast before the rules catch up.
Not an employee, just have a "shit ton" of Amazon stock that has been beating inflation very well. The last few quarters of volatility has allowed me to buy and sell, often fully covering my monthly expenses. I'm very greatful for that. Far from a company "nobody" wants to work for. You have a better performing company than Amazon to recommend that I can use instead? I'm all ears and I'll even give you a kickback for your time!
This is what I've heard from my friends both there and at Meta. It definitely doesn't carry the prestige it once did. It's more like, "willing to get yelled at, be afraid of being put on a PIP every day, and trying to ensure output outpaces your peers". That's sad, but it's where the industry is at so many places right now.
Amazon offers good signing bonuses that pay out over two years, so it's very common to peace out right at the 2-year mark when your take-home pay abruptly goes way down and the grind is no longer worth it. That's what I did, and I noticed it almost everywhere: there's a constant revolving door of inexperienced people. I don't understand how they keep it going with so much turnover, but somehow they've built a system that kinda withstands it, except in frontier AI apparently.
I think it's coasting on that prestige of being FAANG. People still want it on their resume. I share this from time to time but I interviewed there at the same time I interviewed at Facebook (right before the name change). And the difference was night and day. Amazon truly treated me like cattle. Get in, do the automated Leetcode/HackerRank thing. Canned conversations. Facebook at least _seemed_ like they were rooting for my success the entire time.
I will say it’s an excellent place to learn on-the-job engineering fundamentals as a junior if you’re ok with the otherwise shitty culture for a year or two. The high turnover also means they’re really efficient at training new people.
Because all humans are 100% fungible with all other humans. So, you can take whatever old humans you have, throw them away (or make them want to leave), and then replace them with all new humans, with zero negative effect on anything. Rinse and repeat.
Human experience means nothing. Anything that does have meaning gets encoded in the system for the mindless humans to implement.
That’s my take on the view from the top, based on my time working at AWS.
If you chart money in your pocket per unit time, it takes a dip around 18 months where your average pay is less than your first month’s pay. (When I was there, using RSU numbers for that time.) Guess when average quitting time was?
HR swore it wasn’t on purpose and I was somehow measuring pay “wrong” by looking at money in my pocket over time; but knowing their HR, I’m sure the valleys in transition from signing bonus to vesting are intentional.
This is where Bayes bites in practice: we can know that impatient and long-minded behaviors are correlated to outcomes, ie p(quit | impatient), without the outcome meaningfully informing which case we have, ie p(impatient | quit).
That’s because people are complicated and do things for many reasons, so people quitting when we cut their pay might not tell us they’re impatient.
I suspect the intent is what you say, but I don’t think the outcome is.
Was s3 the last time Amazon showed lab grade innovation? Lambda?
I could be wrong because I haven't paid much attention but Amazon has just fast followed everyone else innovation for a awhile so it's in like one ecosystem yeah?
I'm not trying to be snarky, I just haven't thought about aws as having any innovation for a while and I always figured it was because ruthless companies that churn through people as disposable commodities generally don't do tech innovation.
I'm talking on the AWS side, on the logistics side they clearly are doing insane things on supply chain perf optimization.
Dunno about that, but my experience with AWS is their stuff generally works, the other big 2 doesn't.
Generally speaking, on AWS you can buy compute, storage, network and other basic 'goods' and just like a supermarket where you can get either flour and eggs, a cake mix or a ready-made cake, AWS is willing to serve it to you in various levels of ready-ness, and you can start at the level you want, and build your own layers on top if you don't like AWS's solutions.
And AWS's solutions are generally built like that as well, there's no magic to Lambda or Fargate or EKS, its just they run the same EC2s, but with some proprietary magic that lifts some complexity from your shoulders, at the cost of generally some markup, and loss of some otherwise desirable features.
But the core thing is that AWS's offerings are generally solid, so as AI evolves and companies become more willing to take on more complexity, they will move to lower level services, but not necessarily out of AWS itself.
> I could be wrong because I haven't paid much attention but Amazon has just fast followed everyone else innovation for a awhile so it's in like one ecosystem yeah?
A lot of innovation at AWS is invisible on the outside. They pioneered hyperscale datacenters with publicly accessible capacity, software-defined networks, secure VMs, and so on.
> I'm not trying to be snarky, I just haven't thought about aws as having any innovation for a while and I always figured it was because ruthless companies that churn through people as disposable commodities generally don't do tech innovation.
I worked at AWS before COVID. It was really a varied experience, but it was not _bad_ overall. We prided ourselves on making sure our APIs are solid, stable, and backwards compatible. When we had to make a backwards-incompatible change, we actually contacted every affected customer and ensured that their workflows wouldn't be broken.
Oh for sure, these many years AWS has set a high bar in the service space for conscientiousness in offerings. When I compare to my personal work experiences with gcp and azure the amount of times I've been rug pulled over the years has been essentially zero for AWS.
There is intense competition in the AI industry, especially with AI firms in China driving down prices, so it seems likely that LLM's and software products may become fungible commodities that trade close to marginal cost = marginal revenue = minimum average total cost. In other words, most of the profits from AI and software development will be competed away, eventually.
Data center hardware, by contrast, is a scarce commodity with rapidly growing demand, and therefore likely to capture most of the profits from AI and software development, if current market conditions persist.
Today's IT business trends represent a remarkable change in the industry compared to the situation 50 years ago, when startups like Microsoft and Oracle, whose business models were based exclusively on software development, challenged and overthrew the dominant player, IBM, whose primary source of revenue was from hardware.
> Let someone else take on the research and training costs, and charge a massive premium for your hardware.
the linked article is from July, it is almost three months old.
Now there may be a very relevant recent story; it has the potential to reduce the flow of new open weight models. This could change quite a few expectations, which are based on open weight models:
"China’s STAR 50 Index Falls 40%, Erasing $480 Billion as AI Stocks Crash"
Reuters says there is a run, but also deeper reasons:
"There has been no obvious selling trigger in China, although traders said high prices, tax bills and the threat of the US or other nations banning Chinese equipment in data centers all contributed."
So far I don't see any discussions of this story on HN, interestingly.
> Microsoft went all in and have really not got much out of their efforts.
The problem was rather that Microsoft had no real plan what they wanted to get out of AI. If they had a plan, they could have laser-focused their all-in on AI.
Instead, Microsoft just AI-slopped a lot of their bread-and-butter products, making them much worse than before. If AI is as revolutionizing and beloved by users as Microsoft believes, Microsoft could easily have created an offering like "Windows AI Pack" or "Microsoft AI" that should sell like hot cakes.
On the other hand, if you have to force AI functionality onto the users, it should be considered as a strong sign that perhaps it is not something that the users want.
Regular ppl i.e non-techies love the copilot integration into all office products. Since techies know better, they think microsoft messed up with the AI integration everywhere.
Even tech-adjacent folk in areas like product, user research and enterprise architecture seem to love it.
The bulk of the hands-on-keyboard time for those disciplines now seems to be using Copilot 365 as "fancy autocomplete" and "make this presentation better", Copilot Notebooks for deeper work, and coming up with all sorts of Copilot integrations and agents for managing email, Teams meetings and chats.
It's almost as if "copilot" has already become the generic term for "professional LLM", and many genuinely can't understand why us techies find it so limiting.
I, for one am very thankful for what Microsoft did with Windows 11. It has exactly the feature set, and AI value-add ... to inspire me to take the plunge to Fedora Workstation and I've never been happier. Even Steam games (kind of) work. More importantly dnf update -y becomes exciting.
Windows (and increasingly Apple) updates are more of a sigh and lip biting experience than an exciting one.
I'm really happy not to have touched Windows recently at all.
At work Microsoft's updates are buggy - Outlook and Teams are pretty awful on corporate Macs. Teams especially, it has a bunch of papercut type annoyances. And updates torture Corp IT.
Just as there is product-market fit, there is also product-company fit. Amazon as a company has their own cost of capital, earnings expectations, talent distribution, and organizational capacity. It is not a place where the best of the best work in mainline product development, nor is it a place that is willing or able to go through long periods of losing money in order to rapidly improve the product. The Amazon of old did that, and had different capabilities, but today's Amazon is not the same company.
Notice that you also see Google really struggling (and falling behind) in the AI race. This, despite massive resources and being responsible for key pioneering research. Same reason why IBM has failed in this area. The big established companies tend to shut their brightest people into research departments where they write papers and produce demos while the main cash cow areas remain undisturbed, so they have collections of bright people and they have money, but they rarely let their brightest people make big bets with the money, whereas startups do.
It's also why poor people spend more on lottery tickets than rich people.
The best of the best do work at Amazon. Their cloud infra is world class. They just cannot compete in the ai/ml space with different economics. It’s an operational company and not one to do tech innovation.
Basically you want to run an LLM, Amazon. You want to build an LLM not Amazon
Either you are getting the smartest engineers, or offer the most freedom to pursue interesting goals that aren't on the frontier. Amazon has neither so they naturally aren't going anywhere in that domain.
I advise a B2B startup that went from 4 developers to just the founder, who is technical but not a developer. It is now profitable and delivering just as many features with arguably better security. N=1
So how is this startup going to be a value add long term? If they can cut all the devs, what moat is there? What's stopping their customers from just prompting their own model?
Seriously asking, why would this look like a good business model to be in? If they don't need anyone besides a technical non-developer to create the product, why would this look like a good business? If it's B2B, then most of their customers will have that type of IT person on staff.
A dry cleaner and a car wash can be a good business. Outsource things that are not your core competency. A moat means you can defend it better, but in this case your business can capture the value of them not having the IT person on staff and not having to spend the tokens. It’s a good old fashioned business.
a regular business is not a startup though. A startup implies a much higher ceiling on growth and profit. Worth investing in on a high risk, high multiple of return manner. An SME sized business is not that.
Wait... Are anthropic and openai just commodity suppliers? Because dry cleaners and car washes both need soap, but I've never heard of a trillion dollar soap company.
AWS, Azure and GCP supply a commodity -- compute -- yet each one of them could be a trillion dollar company in its own right. Even when on-prem is nominally much, much cheaper than cloud services.
Turns out there are ways to monetize commodities, to the tune of double-digit billions in revenue per quarter.
If it were true that what OpenAI and Anthropic offer were commodities, that there is no moat, Microsoft could trivially eat their lunch. There would be no OpenAI. Google with its nation-state money, extreme AI talent, chips, datacenters, could eat their lunch.
So mighty Google can't manage it. But it's a commodity that's easily copied.
Somehow HN can't reconcile the contradiction even though it's laughably obvious.
Hey anybody could go MVP a ride hailing app over the weekend. It's a commodity app. Should be super easy with LLMs.
Oh shit, wait, you mean I'd have to take a billion users away from GPT and getting those users is now 50x harder than it was four years ago? You mean it's drastically harder to peel users away from existing services than if you get to start fresh? Ohhhh.
They have gigantic moats and so long as they don't do anything too stupid, those moats will just get stronger with time.
No VC is giving you money to try to run down OpenAI and Anthropic. Nobody is writing that $100 billion check. It's already over, HN is just in its standard denial phase.
OpenAI's moat is the userbase and service layer, which is gigantic. It is extremely difficult to pull users away from giant services.
The Chinese models have no great branding with the masses, they have no service layer that any average user understands. Where does Joe go to use the Chinese model that he doesn't even know the name of? Joe has no clue what the difference between DeepSeek and Kimi is, and Joe will never know that.
They all know ChatGPT, they have all been trained on how to use it and what it is. The inertia is enormous and HNers endlessly undercount how that works because deep tech users all want to think the masses view tools like they do and approach tech like they do (which is entirely false).
OpenAI's future is as an ad platform in terms of its business. That's at least 2x-4x larger as a business opportunity than anything they have going on now. Which is to say $80-$160 billion minimum. That requires they maintain the giant userbase, we'll see how that goes. Losing it requires someone take it from them. Joe isn't just going to wake up tomorrow and go seek out how to use Kimi.
The LLM space is worth a minimum of half a trillion dollars per year in ad revenue. It will subsume all of search. Search becomes merely a service of an LLM, which will perform the function on your behalf. Google is on top of that shift, so OpenAI has its work cut out for it competing with Google there.
Of the US big three, Anthropic is by far the one most threatened by the persistence of the Chinese models. Anthropic will probably never stop being chased by them and will have to endlessly race to try to stay ahead. Anthropic has to figure out how to build out the LLM+ equivalent of AWS before China figures out how to beat them, ie build a very deep service / tool moat around Claude that the userbase gets stuck to. In short dramatically increase the difficulty in peeling away users, it has to become a big chore to switch (which eventually this is exactly what someone will figure out in that area of LLM competition).
The question is "what business value is AI driving?" and the answer was "a solo founder cut all the devs and still delivered a product".
Separate question: "now that AI is here and development isn't a moat any more, how does a business defend itself from competition?"
That second question is a direct result of AI. Five years ago the amount of cost and effort spent on software development was a moat. Now it's not. So that answers the first question completely, I think.
As for the second question - market sector knowledge, customer contacts and industry reputation, all the usual non-technical things that make a moat. Also, we may now be living in a world where software companies cannot expect to be monopolies in their markets any more. This company will have to compete with many similar competitors for market share, like in most other markets. I think this is a good thing. Less enshittification will ensue.
No extra value was generated in the example. If anything, AI in this example reduces the price of the product AND employment.
Value was destroyed.
The hope is that all these unemployed engineers can somehow generate value? Even if they do they need to generate enough value that would employ 4 engineers.
If a business can create software cheaper, then it can charge its customers less for that software (or, conversely, if a business can use an AI to create bespoke software for cheaper than it would cost to buy that software) then the customer business saves money. It, in turn, can use that money to improve its offering to its customers. They, in turn, and so on.
Having cheaper things means everyone gets more things. The value created is created further down the supply chain.
I understand what you are saying, it just seems that this technology in contrast to any other productivity related technology is deflationary, because there is no alternative avenue to employ the idle labor. Not now, not in the future.
Where will people work on if both blue and white collar jobs go away? In brothels?
Good question, and the question of our age, for sure.
I loved the article that was on HN a while back (original article here [0] be warned it's a quite a long read). It compared the current revolution we're undergoing to the Mercantilist revolution when we stopped being farm workers and started doing other things instead, driven by technological change in agriculture.
The answer they came up with: we don't know yet. Much like the move from subsistence farmers who started working in a factory had to rely on other people to feed them, we have to answer this question ourselves and it'll probably involve doing something very different. And wonderful - subsistence farming is a shit life (despite all the influencers saying how amazing being in touch with the land is) and we would all prefer to be working in an nice clean office than trudging knee-deep in muck in the rain trying to keep our crops alive and pest-free. The same will probably be true once the dust settles on this revolution and we'll all be profoundly glad that AI came along.
The big problem we have to face as a society is that we cannot allow all the value from this technology to be captured and retained by the wealthy few. Our ancestors had to fight the same conflict with factory owners during the Industrial Revolution, and they didn't manage to win that war completely despite all the blood shed and battles won.
What are some businesses where software was really a moat but the software lacks sufficient complexity that AI can reproduce it?
I can't think of any, I'm sure there are some, but I would really like to know. I just don't think for most business the software is so much of a moat unless it's very complex.
yup, it's happening. many of the CEOs/CTOs of PE owned ISVs have their marching orders: put in strong product managers, software architects and other senior roles who define what to build and how the software should work, and thin out the developer teams, as agentic coding becomes the norm. Am not saying this makes for quality software, but this is where the industry is heading.
> It's going to be funny when AI soon costs 4x or more than it does now
What exactly will cause that? Hardware costs are (generally) going down, and open weight models are getting smarter. The subsidised subscription prices will go away, sure, but I don't see the average token getting more expensive.
But there still remains the possibility of error/hallucination. Do you bet on a future where AI will never make any mistakes whatsoever?
I am often told humans make mistakes, too. But this is an elementary logical fallacy because the type, frequency and severity of the problems is never the same.
Also, humans are more likely to do as told, whereas AI often takes liberties (i compiled a book from a github repo and it did things on its own in the book though i had explicitly forbidden that).
Where I work, we take on way more exciting and ambitious projects than we would have when I was hired. It's exhilarating at times. Genuinely, AI in general (not just LLMs) has radically transformed the types of work we can conceivably pursue and deliver on. We're an NGO so we have different staff than a regular tech company, but we're highly tech-driven. I don't doubt that this is the case at many orgs like ours.
And it's measurable. We don't just feel more productive; we get grants, we build systems, and we make plans we simply couldn't have before.
I'm not sure if I'm more productive, but in my role where most of my deliverables are technical documents or emails I think my output quality has gone up. Now that I typically use LLMs as a research assistant and editor before sending anything significant to co-workers or customers I'm sure I make fewer mistakes. AI catches a lot of gaps and errors. That's a significant qualitative improvement although I can't quantify that in terms of profit impact.
I think you're letting the LLM write emails that are overly verbose that are shortened on the other side by another LLM and so there are 2 minus habens to both side of a communications that are communicating the same stuff as before but now are paying for altman's yacht in order to do it
Nah, that's not what I'm doing at all. Did you even read my comment? I use it more like a fact checker. It's not perfect but it catches a lot of my errors.
Maybe you could use an AI assistant to help you write better HN comments.
i know multiple stealth startups with 9 figure revenues and profitable and growing
lab arr is climbing
given the recent crackdown on token spend and from speaking to execs they are very focused on the exact ROI they will get from AI
Note that business revenues in competitive markets may actually not change that much, because if everyone is using the same models there's no competitive advantage from using AI. but if one of them didn't use AI they would fall hopelessly behind
We ship features faster and workers are more independent. They can get the answers they need faster than ever. And i'm talking about the business itself if the business has enabled that. There are a ton of productivity gains.
But make no mistake. Being more productive does not equal higher profits because your customers think you've added value. Both value and productivity are highly subjective terms which is why it is measured differently depending on where you work.
Most businesses adapted to AI by shipping a lot more features in smaller increments of time. What they should have done is become much more ambitious and build moon shots in two quarters instead. You need to go big or go home if you're going all in on AI.
AI is not about productivity. It's about weaponizing the ability to ship fast go-to market features in the blink of an eye when it becomes necessary. If trends change fast and you can't adapt quickly with AI: you're dead. So you need to have AI ready to go, just in case.
GPT 3.5 is 2022. In the past ~18 months the majority of all human software development has been wiped out and the models keep getting better rapidly. AI has already radically overdelivered and the biggest returns are in the next 10, 20, 50 years.
Models are finally good enough that I'm confident that I can repeatably build pretty much any software reliably in less than 2% of the time that I could before 2022. I wouldn't have made that claim 6 months ago.
Even quantized local models like Qwen3.8 are good enough to handle a lot of drudgery. For example, I hooked my wife's computer up to a local model, and now she finally has a clean desktop. She just drops spreadsheets or powerpoints or whatever on her desktop and automation takes care of everything.
The caveat is that I developed software for 30 years, so I understand most of what it produces and can guide it to make fewer mistakes and fix what it can't do. The biggest challenge has been keeping my requirements focused - it's very easy to gold plate everything and prematurely optimize.
The biggest question I ask myself is why am I even still doing this. The smart people are probably already trying to figure out how to pipe raw matter and energy to their homes to build replicators.
The future is already here, it's just not evenly distributed.
Build experiences that are user dependent. The value isn't in the software it's in the users. That's the ultimate moat. It's what isn't properly grasped about GPT's position, insofar as they don't mess up big: they have captured a zillion users, they're Kleenex. Ask GPT = Google it.
You don't want to be in the CD selling or radio business with the Internet & digital & streaming & smartphones & iPods bearing down on you. Go for concerts. Notice that humans are spending more than ever on live concerts. Disney World and Disneyland still command extraordinary pricing power, despite everybody hiding inside on their phones.
LLM clones of eg Photoshop will end up being worthless, like ideas generally. The software will be worthless for the same reason ideas are: they're too easy. Users are hard, software will be (relatively) easy.
Is the value in McDonalds in the food? Everybody knows it's not. McD captured consumers, their heft is extraordinarily difficult to displace. Ie habits, brand awareness, location, etc.
"LLM clones of eg Photoshop will end up being worthless, like ideas generally. The software will be worthless for the same reason ideas are: they're too easy. Users are hard, software will be (relatively) easy."
I doubt that. If a clone out there offers all the Photoshop's features for free or much lower cost, without additional learning curve, then many professionals will switch to save money.
McDonalds would be gone too if somebody opened a restaurant chain serving similar food for free or 80% lower price. But that's impossible to do profitably, while freeware software has existed for a long, long time.
Photoshop users could switch to GIMP tomorrow. They don't want to.
The many professionals are the ones that could most easily understand how to switch to GIMP, which is free to use. They could save enormous amounts of money. They prefer to spend money and stick with Photoshop instead. That has persisted for a very long time now.
It means in corporations across the globe, the majority of code is no longer being written by humans. That is over and it will only keep dwindling by the quarter.
Writing lines of code by hand is all of human software development? Pretty sure in all of those companies its still software engineers writing the code, even if they're using LLMs to do it.
Unless you're making the claim that software engineers aren't involved or that only writing code is software development.
Yes it means in corporations across the globe, the majority of code was no longer being written by humans long before the majority of code was no longer being written by humans.
Also remember, the majority of all human software development has been wiped out 18 months ago but the dwindling will keep going by the quarter until the majority of all human software development has been wiped out.
Nonsense. Nearly every software house in the world has just as many or nearly as many programmers as they did 7 years ago when GPT-2 was "too dangerous to release." You live in a very tiny bubble if you think most businesses are building software without humans. Total horse shit.
Microsoft is laying off 60,000 people. That's just the early pin prick of the layoff gusher that is incoming.
One million software developers will lose their jobs in the US over the next ten years.
The big firing waves will begin when valuations decline as the initial AI boom slows. That has started already, although it's early. Companies like CoreWeave will basically collapse. Investors will demand & reward the layoffs, efficiency push, the end of rah rah times will prompt the inflection on employment in tech. And it'll never be like it was ever again.
Microsoft isn't laying off 60,000 people. They offered voluntary separation agreements, but nobody was laid off.
For 1 million software engineers in the US to lose their job you'd have to shrink the industry by 62.5% and nobody is doing that. We employ more software engineers this year than last year, which was higher than the year before which was higher than a year before. Get off the social media and look at real statistics and news.
Those 60,000 people are being eliminated from tech jobs. That's a gigantic number. Microsoft is pruning. They'll do it the hard way if they have to with literal firings. They'd like to avoid that if they can, and they're in a position currently where they can afford to. Most companies are not going to be so gentle.
HN is in denial. Just watch what happens over the next ~36 months.
I'm disengaging from this conversation since you seem unwilling to engage with facts. 60,000 software engineers are not being laid off at microsoft, full stop.
> HN is in denial. Just watch what happens over the next ~36 months.
In all likelihood, massive worldwide recession due to combination of oil issues and debt-ai bubble popping. That will be combined with instability due to democracies cracking up, wars popping up faster and faster all the while the richest and most powerful people are increasingly desperate to destroy democracies before it is too late for them.
There is definitely an unanswered question as to what the metric, but no, JavaScript is not 90+% by any useful metric. Most code is not a website, and JavaScript penetration outside of the client-side code on a website and some GUI applications on various operating systems is almost nonexistent.
Remember that all of the code in operation includes code like the microcontroller in your mouse, the hundreds of chips in your car doing things like keeping the engine running or "window goes up when I push the button," the DVD menu (which is actually Java code), not to mention all of the staid systems responsible for things like writing your paycheck every other week.
Astra, Fable, Opus 5.5 are drastically beyond the capabilities of the median software developer. It's not remotely close.
The bottom 2/3 of the human market is entirely dead. Their jobs are gone (AI-shored) they just haven't all gotten the forced retirement or pink slips yet, while they click a few more prompts for a few more pay checks. The frontier pushing forward will knock out most of the remaining top 1/3 without breaking a sweat over the next few years. The really good developers will graduate into babysitting AI as managers.
It is legitimately sad, it's millions of high paying jobs just in the US alone. It's going to be brutal on the housing market. Automation came for another field.
Software engineering isn't unique, if this is true then it's 99% of all white collar work. Those same software engineers are going to help automate every other job on their way out.
Correct. Everything will disappear, even hardware jobs and the trades but the people responsible with the automation jobs (software developers) will be the last to go.
I am improving my Spanish and staring at the massive savings that I have built up from my SV job. When my job goes and the industry is in flames, I am moving to Bolivia.
If you have a big mortgage and no savings, it’s going to be tough. Stop taking the Waymo now.
My income is not dependent on LLMs not taking all the software etc jobs from humans.
My suggestion to anybody staring this down is: do something for yourself while you can, while we're in the early going. Most people still have no understanding of AI, most tech employees are doing absolutely nothing interesting with it other than prompt prompt prompt prompt while at work and effectively doodling at home.
Go high value and go for the users. Do things that don't scale, that actually rings more true now than ever. Focus on areas of tech where it's really hard to get the users, where you have to practically hand acquire them to get started. Users are the moat.
It's not build the software and they will come. That's what nearly everybody has wrong about what is going on right now. The value is not in the software. Users, users, users, users - they should be your primary focus.
Also consider looking at software more as a layer related to something else you do, not as The Thing you do. Related to another service you offer, improving that service.
Let's say you started consolidating in the physical self-storage space ten years ago. You read that it was a very wide open field, where the market was not yet highly concentrated, 3/4 of the market was mom & pop operators. Over the next ten years you built up a lot of storage locations. LLMs can amplify your business, they can help you automate, layer better software on top of your physical business. You know what LLMs can't do? They can't build storage units, and humans love their storage space. That's just one example out of a zillion out there.
And in before ‘JumpCrissCross chimes in about inference being profitable while ignoring all the investment costs needed to get inference to where it is.
The full balance sheet captures the info. If the AI companies suck up all of our salaries and spend that money on R&D/training, they still aren’t profitable, right?
I mean, if anything summarizes where we have gotten to as an industry this quote is sure it. From Uber using VC funds to subsidize growth to where the AI players are at...
but profitability is a very narrow view on the labs, and investors are pricing in future free cash flow
you need to take into account the derivative, what is their growth? their opex and capex? their revenue growth? their moat? New product lines and applications?
Not saying that it's a homerun, but there is a case to be made for the labs being wildly profitable in 4-10 years
I mean, it literally does. Something like 70+ billion of those 80 billion are accounting adjustments because their debt is supposed to be handled in stock and their stock price skyrocketed.
While I was being facetious, Anthropic is nowhere close to being profitable in the normal, i.e., GAAP meaning of the term. It's only using unicorn fantasy lalaland financials that they are "profitable."
Before someone else jumps in talking about "unit economics": unit economics only matters if you can sell the units long enough to make the initial (capitalized) investment (i.e., R&D) back. Models aren't commercially viable long enough for the unit economics to work.
You're arguing the second quarter isn't representative of what they'll be able to sustain... that their revenue isn't durable? Let's see. But it's a profitable quarter
Why have they needed to worry about profitability?
They have been chasing extreme growth with cheap money. That enabled them to hyper scale at a pace the world has rarely seen before. They have made the correct choice so far.
The absolute dumbest thing they could have done up to this point is slow down to try to turn a profit. They have not needed to. Market capture is the sole thing they should be focused on. Here's a hint: how many users does GPT have now versus three years ago?
There appears to be very widespread confusion about what purpose turning a profit serves and how business operations actually work.
Go back in time and tell Uber in ~2013-2015 that it needs to immediately become profitable and not focus on capturing the market.
Market capture didn't work so well for Uber, and it won't work for AI, and even less so for AI because you can't get a driver in China to take you to LAX airport, but you can use cheaper Chinese AI.
Uber has to pay back all the billions of dollars it wasted trying to get people to use their platform, and now I can't afford most Uber or Lyft rides, it's way too expensive. So did market capture really work if they had to raise their prices so much as to make the service unworkable for most people? The only time I take uber is if my company pays for it, and that is getting less often.
AI is also going to have to become way too expensive so they can pay back the billions (trillions?) it is borrowing. And, when everyone is laid-off or fired because AI took their job, then who's going to be paying for AI? I guess the companies that lay off all the humans will, but when the wealthy business owners realize they've replaced everything with AI and nobody is buying what they are selling because there's no more jobs, then what?
Sounds like they should worry about profitability, and a lot of other things too.
Uber isn't dealing with a shrinking market. They're becoming critical transportation infrastructure and their business keeps expanding year after year.
$32b -> $37b -> $44b -> $52b -> $57b
That's Uber's sales growth year by year. And now they're solidly profitable.
The sole threat to Uber is the Waymo / Tesla automation angle. A merger is most likely there.
Huh? uber is an amazing success story given their market dominance and enterprise value created. of course the next kid on the block (Waymo) is going to do the same thing
The price of a given point on the intelligence frontier is only going to get cheaper, likely 10-20x over the next few years.
Too dangerous to release was 2019. Today it's only very useful for coding and other niche industries. It promised to automate all work and to usher in a utopia. Instead it helps programmers further enshittify Big Tech offerings. That's well short of any promise or expectation set out by boosters, paid and otherwise, for the last 7-ish years. Where's the civilization upending change? Where's the Beef(tm)?
Can you name 3 ways is positively impacted the average non tech persons life in a meaningful way? Meaningful would be more than the invention of the microwave, but not as important as a vaccine.
- File taxes and find issues that "accredited", "certified" entities missed. In one instance, my federal refund increased by nearly $5k. At $20/mo, just the refund is two decades worth of value.
- Appeal health, home and car insurance claims successfully
- Find out details of interesting plants without forking out tens of dollars for an app that claims to do the same but fails to do so most of the time
- Summarize never ending email threads with 20 disinterested parties who would rather not be on the email but have to respond to show they are "engaged"
- Write a convincing email to my mother in law why I cannot meet her this weekend and hold her hand through the tough times she's having with her ethnic neighbor who annoys her with their "ethnic" music and "smell of fish" BBQ
- Locate the user manual for my microwave and what that rapid 3 beeps every 1s for 2 minutes that starts at 10AM since the last 2 days mean
Help with health issues is turning into a big one.
My mother-in-law has a complicated set of medical conditions and sees half a dozen different doctors. Fable with max thinking came up with a bunch of interactions between drugs and conditions that her doctors hadn't considered. We've run its recommendations by one doctor so far and he agreed with everything.
My brother has one friend who used a frontier AI to diagnose his wife's uncommon cancer, and insisted on a test for that. It was correct and she's fine now since they caught it early. Brother has another friend whose wife had back pain after surgery; medical team didn't find what was wrong, he uploaded the scan, and the AI said "oh they left in a staple," which turned out to be correct.
I've started using it to work on a cookbook for the medically prescribed diet I'm on.
Sure it has replaced Google for a lot of people. But was that driven more by Google breaking search and actively ranking down good results and putting blocks in the way of seeing even the bad results?
Google had (have?) people using their service out of habit but built a hostile enough environment. We have this "contradiction" where non-tech folks are supposed to be difficult to move off "what they know" yet here we are where they are using ChatGPT to search and be a doctor.
I'd argue they're the most useful kitchen appliance, except possibly for air fryers. You can cook almost anything in a microwave, usually faster and with less cleaning up than otherwise.
Microwaves, or microwave ovens? Because I can name all sorts of ways that microwaves have improved communications. So many long-haul telco links, and remote radio/TV stations, have been accomplished by microwave. It's a powerful method of transmission.
Unless you're specifically meaning microwave ovens, which are of "limited utility" in a full-service kitchen. I'd have to agree there.
My previous microwave oven was so intensely powerful, that I needed to dial down the power to "7/10" so that it would not destroy my frozen meals. I could never run it at 10/10. My current appliance is very nice, and has an automatic button to run until doneness. Works every time now.
We're at the dot com boom stage of AI. You could say it didn't deliver because boo.com didn't make a profit or because the average person still used paper maps, but that was just because of momentum.
It's the same with AI. The technology is here now. My friends in financial advice and market research have not lost their jobs immediately, because of momentum.
I find it kind of odd that you equate a small oligopoly of intermediaries gatekeeping information as "democratization". Similarly Google maybe made it easy to find for a while, but that was/is not democracy either.
This is democratization of information in the truest sense because the AI can not only find information for you, like Google does, but even patiently explain it to you. We never had that before.
Like, a normal person is not going to open up an arXiv preprint from Google search because for approximately the entire population, it's going to be way beyond the limits of their comprehension. They won't even glance at the link, if Google even serves it up as a result.
But, with a chatbot, they could actually ask questions and get answers in a format they can understand. They may get a very rough understanding of the topic, but I would bet it's 100 times better than the same reference explained by modern "science journalism," which insists on presenting the most clickbait-y interpretation they can find.
And this is not theoretical, I've seen my high-school level kids figure out undergrad (or higher) level concepts like locality sensitive hashing with the help of ChatGPT, and I know they understood it because they could sketch out working solutions using those concepts. They didn't get the Mathematical underpinnings, but they understood the high-level behavior and that was enough.
Everybody can now understand anything if they really want to. Nobody is doing it today because they don't know it's possible. But they can, and we should encourage them to do so.
Linux (the kernel) and Git have done more in this regard, but think of FOSS in general. Without it, there wouldn't be Android. Without it, Windows NT would've won server space in the same way Windows won desktop space.
It is tools which are the commons (such as FOSS) and tools such as Wikipedia. But also open standards. LLMs cannibalize on these tools.
Furthermore, no customer wants an AI as customer bot. Especially elder people who are a bit computer illiterate can't find the real support (dark patterns). Can AI help a customer support representative? Oh, absolutely. AI can help a skilled person become better/quicker at certain tasks. But it cannot replace them, and it shouldn't either. If we do, we get all these 'fantastic' tools like *claw.
My conclusion is that this technology is operating in roughly the same way as the personal computer, and that it's going to take similar timelines for the effects to manifest. We still haven't nailed down all the stuff AI is good at, and it's capabilities in known-good domains are increasing consistently. Engineers on my team are chaining together fascinating workflows that I imagine could be entire products, but things just aren't mature enough yet.
Advances are still coming rapidly -- we have quite a bit of time before this settles.
Actually AI has been over promising and under delivering for about 70 years. Whether or not you think the juice is finally worth the squeeze, the distance we've come is impressive.
I just played with Nova after seeing this submission. I gave it some real problems for which I used Gemini. It markedly "dumb" in comparison, losing sight of facts that I presented in the first prompt of the chat, and other subsequently introduced, and its responses contain repetitions of the same point-form advice. It's like GPT-3 level or something.
Well except for the regular HN anti-AI crowd. Usually the same people that have wished for communism and never ever looked in detail into the 20+ states that failed that way.
The day is approaching when Anthropic and Open AI will reign as the next generation of big tech.
I guess it's an unavoidable cycle.
Big tech companies, having grown too large, find it difficult to innovate quickly, and new generations emerge to become the new big tech players. What comes after AI?
Nobody can know for sure but I am thinking that in the next 5 years one of the 2 will be dead and the last one standing will be sort of still depending in one way or another by the tech behemoths of today.
their innovation seems to be limited to renaming the forced sidebar on amazon.com every few months and not allowing me to dismiss their useless features.
Ublock hides the sidebar from me, but it does still take up the whitespace on the side of the screen. Now it won't remember that I dismissed it and it pops back in on every new screen. I am just used to the screen being narrower now. But it is still annoying.
The chatbot sidebar seems to also be the only way of accessing certain Amazon features, like the price history. And it seems to be implemented in a particularly silly way - clicking the "price history" button prompts the chatbot to show you the price history, rather than just showing it.
I think the forced-chat price history thing is a dirty way of trying to get people used to talking to the chatbot. Can't think of any other reason it would be designed so stupidly
- Single point of billing and vendor is still king in enterprise - look at how much of Ant's revenue flows through AWS Marketplace
- With OSS, models may move to a more of an AWS-shaped problem: host with 5 9s, provide the infra and shovels, do it as cheap as possible, fit them neatly into rest of AWS stack. I think this is actually a huge risk to OpenAI and Anthropic, as more commodization gives hyperscalers more advantage
- Still owns a huge chunk of Anthropic and leverage over compute
With this in mind, I'm not sure why they need a frontier model vs. the playbook they did with Linux (i.e. Kimi-K3-AWS-Enterprise-Edition). They are kind of playing both sides right now I guess, but could really stir things up if they wanted to.
I'm not at all close to knowing their internals with books in particular but for most products Amazon has made a significant effort to remove themselves from direct product stocking wherever possible (instead preferring to warehouse other people's stock for efficient shipping). I would guess that they aren't particularly well positioned with publishers at this point... Also, most publishers probably loathe Amazon at this point for all the times Amazon has tried to fleece them w.r.t. Kindle.
Tomorrow (October 28th) is the 1 year anniversary of being laid off from the Amazon Devices team. Nearly all of the senior people on my team were laid off at the same time as part of the "pivot to AI" strategy. Hurray for "commitment to accessibility".
This outcome for their years of squandered effort honestly doesn't surprise me as, other than the Graviton/Trainium work, the Amazon efforts were scattershot, half-baked and underinvested. Only the Siri team is more pathetic than the Alexa team. Well maybe Co-pilot stands between those two somewhere.
Amazon Nova is their model? I worked for a company that was being pushed into trying to use AWS's "Nova Act" [0], which I guess was their python-based wrapper to do things in Playwright. I didn't think it used Nova the model under the hood though, or maybe it did. Either way, Nova Act was horrible in terms of performance - it was so...damn...slooooow. Much easier to just use Playwright.
It would seem that they can experience most of the benefit of AI without most of the cost; anthropic is operating at the frontier and shows that even while supplying the best models and token sales to enterprise, they lose massive amounts of money.
Amazon makes 60B+ in profit per year, they don't need to tank that by losing it on training AI / selling tokens.
There are plenty of open weight models out there for it to use with most of the benefit and very little of the downside.
> Amazon’s standout AI model — organized under the name “Nova” — is about the farthest thing from a household name.
I have tried asking people if they've ever used an AI product from certain companies, and you only seem to get "no", or surprise that they have any AI products, for some.
Alexa+ is pretty terrible. It's surprising how no one has beat them in the home device market. Alexa stagnated and died a product death while still being the standard market option for 5+ years. I was hoping LLMs would improve it but I haven't seen any evidence, even after purchasing their new line.
I might try Google's home option again but I'm not a fan of giving Google second chances since they seem to care even less about committing to products.
It's possible for both a new technology to be hugely beneficial in the long run & for early investors to lose a lot of money funding it (if they over-invested / over-paid).
Values drive behavior. Who owns / runs futurism and what are their values?
Journalism / media as activity needs to be sustainable and unfortunately in our current world it's seems very difficult to sustainably remain high integrity. Sometimes it may be greed, but most of the time I think it's survival.
In this case AI is part of what is threatening journalist survivability, so it kind of makes sense.
Too much backstabbing from legacy employees inside amazon to allow for grassroots innovation. Good work will get stolen or stamped out by coworkers. Vicious employee base intent on collecting their paychecks
not a fan of recent AI wave. but if I wanted to be long on it I'd pick robots, drones and AMI (essentially +1 on Yann LeCun). if Amazon were to be refocusing/doubling-down on those areas too I'd respect it
Hard to innovate on AI when you're firefighting 30+ sevs a week.
funny story actually. I was recruiting an engineer from another stressful team. I pitched to him that we have about 4-6 sevs a quarter, and I was worried he would balk.
He said "that's nothing, when I was at Amazon we had 30 Sevs a week" .
My impression of Amazon is that it’s a doer and is scrappy and gets things done at scale quickly. I just don’t see them as a place that is at the forefront of research.
I wonder if the best play now is not to play and wait until the landscape is clear. They are making partnerships now (e.g OpenAI), and investments (e.g. Anthropic).
It doesn't make too much sense for Amazon to invest too much of their own money into AI.
They already sell a lot of the shovels for training and inference and make ample money from that, and there are enough open weight models on the market to make it infeasible to build a large enough moat.
The remainder of your quote matters more, I think:
> Instead, labor and computing power are being diverted toward a singular “frontier-model effort” led by Pieter Abbeel, director of the Berkeley Robot Learning Lab whose robotics company Covariant was hoovered up by Amazon in 2024. At the time Abbeel joined the tech giant, Covariant’s founders were working on AI models for robots, which lines up pretty well with Amazon’s push to automate everything it possibly can.
Amazon can't hope to compete in the LLM genAI (what is colloquially known as AI anyway) space. That is toast, the race is over for them, too much competition, no way to make money.
But industrial automation? Globally, Amazon employs about 1M people in fulfillment/operations roles, the utter majority of their headcount. If there is one company on this world that has the money and compute capacity to spare for a high performance, real world application of fusion between modern machine learning and robotics, it's Amazon - and to make life easier for Amazon, unlike every other competitor they don't have to pay or partner with another company for real world testing. They can just go and deploy a robot in their warehouse if they want to.
Achieve a breakthrough in a fully automated picker robot, and they can save half a million people on their payroll, if not more, they'd save shrink loss and handling mishaps as well. That is one hell of an opportunity to save money by R&D. And if they patent everything they do, they can lock their competitors out of that technology for a loooong time.
They could revert to the pre-LLM craze where Alexa was actually able to answer prompts in a reasonable amount of time. Alexa is a glorified egg timer for nearly all users - it's super convenient to use a voice prompt to start/stop timers while cooking and being able to play music on voice demand is kinda alright. It genuinely doesn't need to answer hard questions.
The new AI powered Alexa beta basically can't do egg timer, music, or light switch duties as reliably as the old Alexa, which basically makes it useless.
You'd think with all the data collected by these tech companies, they'd understand the common usage scenarios of their products. But instead we have AI Alexa that can't egg timer, or Gemini Assistant that can't navigate or make phone calls.
Wait so Microsoft gutted their AI Division and Microsoft looks like it did as well from the list of "departments" that are in the approved buyout list. Does this mean they are just going to be resellers of the big models companies going forward?
Outdated, sensationalist reporting off July 29 numbers that's already useless in the fast pace nature of the AI space. This is endemic of the last 5 years of "journalism".
The title is clickbait - Amazon is redirecting resources toward another major AI project and that does not, by itself, establish an overall "retreat from AI". The last 5 years have been a time of flux and now companies are starting to focus on niches and gaps in the market.
AI takes substantial focus and investment and we are compute constrained - AWS is correctly consolidating and refocusing by scaling back several of its existing Nova projects (Canvas, Reel) and concentrating resources on a new flagship model effort led by Pieter Abbeel.
If the claim is "sustained failure", what failed against which objectives? Technical capabilities? customer adoption? economics? delivery? The article does little to establish any. Consumer name recognition is a weak substitute for evidence about an enterprise model business!
A good report would have included benchmarks, revenue, or profitability evidence supporting the article's broad failure claim - this lazy "vibecoded" report doesn't even come near.
It credits Bloomberg while linking to Business Insider. That is a straightforward sourcing error - a journalism 101 no no.
If this is the new generation of shoddy, sensationalist "reporting", good riddance!
The frontier of AI has gotten so spicy that the delivery risk of pursuing this rabbit is astronomical. Knowing when to quit and use someone else's solution is critical at this scale.
If someone started from zero, how long do we think it would take for them to reach the cost/capability front currently provided by gpt-6.1-terra? How long until OAI figures out a way to distill that down again for pennies on the dollar?
Apple seems to have this sorted. You won't find them chasing OAI, Google and Anthropic around the playground.
Anyone that's been in the Amazon offices in the last few years is not likely to have witnessed a culture that fosters lab-grade innovation.
Your comment was likely focused on dysfunctional parts of the culture there (and that seems to be how most replies to you interpreted it as well). There's truth to that, sure. But I think respect for data sensitivity and security is also a big part of what makes the culture ill-suited for frontier AI lab work.
When I was at AWS, we had data access locked down very tightly. I was trying to train a model to predict how long various dynamic workloads running on behalf of customers would take. Just getting access to anonymized production data from a DB that my team owned took well over a month and had me compromise heavily on what attributes I could access. I also spent a decent amount of time in meetings with lawyers and compliance folks to explain and justify all our data classifications for PII, retention, access controls, etc. We would review our data policies quite frequently. We needed break-glass procedures to access prod data in our own systems, and it was uncommon to need to resort to that. Even when you broke glass, certain classes of sensitive data would still not be visible to you. On the plus side, We did get quite good at operating and maintaining systems without needing to see sensitive info.
If you contrast that with Meta's disregard for privacy or the way frontier labs disregard the law, it's easy to see why Amazon would struggle in this space.
I read your comment as “amazon acts too responsibly to be a frontier lab,” and that worries me. That they even bothered to do all that stuff is good. That others don’t is bad.
I did indeed mean it that way, but I agree with you. It sucks, but it's just the unfortunate reality of the world. Many of the most disruptive and successful startups made it there by ignoring legal or moral limitations.
Frankly reading your comments was a relief. I'd rather they take my privacy (and security) seriously. I don't need or want any AI features or technology from Amazon, thanks very much.
Amazon has a history of fostering off-shoot companies that are given more freedom to innovate[1][2]. Keeping AI development in-house under Bedrock was probably their mistake. There's a big difference between running AI and developing new AI models.
[1] https://en.wikipedia.org/wiki/Annapurna_Labs
[2] https://en.wikipedia.org/wiki/Amazon_Lab126
I don't know where the Strands team sits in the org structure, but there's been a lot of stuff put out by them lately too.
Their core selling point is customer trust that their product works as advertised.
From my interactions with them, is that they really care about customer success, and everything including AI is a means to an end to them.
I think building a cool product with undefined reliability and capabilities, then selling fantasies about what it will possibly be able to do down the line isn't really what they do - or what their customers are paying for.
I agree, from my personal experience. AWS support at most tiers I’ve used is excellent. Granted, the larger account you have, the friendlier the service, but even when using it for smaller personal projects, I’ve always been pleased with the level of support and devotion to customer experience (except the console experience, that is not fun).
Don’t know to comment about the other areas of their business but AWS has always been excellent for me.
Incentives can produce locally rational and globally harmful behavior. (See also: "Moloch", although I'm less of a fan of the concept lately since it focuses exclusively on the harmful aspects of emergent systems, deleting the neutral and positive ones in the process.)
A relevant metaphor is the nuclear arms race. Nobody wants a world full of nukes pointed at each other, but if the other guy is gonna do it...
The argument in this case is, we can't slow down, because China certainly won't, and do you want those guys to build the machine God first? So it's "rational" to maximize p(accidental_skynet).
I interned there for a summer working on evaluating text generation and despite the fact that I used no consumer data whatsoever, but rather a well-known public research dataset, I also couldn't egress from the machines I ran training on. Not even reports on the training (admittedly, this was 2021 when they had just introduced this new system). So it was even more of a damper on research progress than you might imagine.
If the people that do stuff well fail, what does that leave us with?
With the need to enact political change so incentives align for the benefit of society at large.
This indeed. Economic democracy is as important as political democracy.
What do you think of the idea of workplace democracy?
Careful there... people who cannot even describe or define what communism is will tag you as a communist.
what is communism and are there verifiable reports of it accomplishing what it promises?
Where is there verifiable proof that capitalism is not rule by the rich and powerful?
People, usually starting from scratch (0 to no seed funds), immigrating to the US from communist countries and becoming financially stable at the minimum, often times building muiltimillion dollar empires and less often, muiltibillion dollar empires. ChatGPT/Claude/Gemini/Grok will give you well researched datapoints that you will be able to follow up on yourself.
I can suggest a prompt that will report how many founders part of Y-Combinator, who came from nothing, some immigrants from communist countries, have become ridiculously successful.
Have you tried to start a business in Pakisthan, Russia, Cuba or China as an outsider? Even with a few thousand dollars as seed? Do you want to buy a house in Pakisthan, Russia, Cuba? Do you want to study there?
... but you didn't answer my question, and I have yours.
Trump is hated by most of the rich and powerful.
this is arguably why he is the way he is: NYC high society mocked him to his face.
a lot of his "burn it down, fuck em" attitude stems from that.
he is, however, completely and utterly narcissistic and greedy, and smart rich people are able to play him like a fiddle.
the KGB picked up on that in, like, the 80's, after Ivana's dad -- an informant for the Czechoslovakian secret police -- passed on details of their relationship to the Czech internal security
>Trump is hated by most of the rich and powerful.
Too bad they died off, those were the captains of industry in the 20th century, it was tragic to see them go.
Now it's even more tragic with huddles built from captains of non-industry, "monetizing" rather than producing.
If a consumer recovery is going to happen, what is it being produced that the bottom 10% is going to consume where they can get their money's worth if nothing in the affordable tier qualifies any more? A greater number of people across the board need to get their money's worth on almost everything like never before seen during so many peoples' lifetime at this point.
I liked it better when Trump-like character was almost universally recognized as nothing other than a mindless financial squanderer wrapped around an inherently dishonest core. This was voiced most strongly especially among the rich and powerful.
They used to know better, but that was then and these are not them.
Which has nothing to do with Amazon. Except for the way the political party which leveraged Reaganomics in the 20th century to the effect that average consumers would eventually no longer be able to afford anything other than Chinese-made products, turned out to be the same party which fell behind Trump in the 21st century as if his financial acumen was't completely non-advanced.
And just as consumer prices of the Chinese mass-produced goods continued to fall as desperately needed by consumers due to direct purchase from China, Trump halts that so there's more need to go through Amazon, they can maintain more control that way.
What does that have to do with anything? And still, so what?
Do the rich hate him because he exploits the working class? Because they think the way he got rich is obscene? No! It's because he won't shut up, and says the quiet parts out loud. They only hate his personality. You would know if they hated his policies, which they don't, because he'd be out on his senile ass before you could say dementia.
> That they even bothered to do all that stuff is good. That others don’t is bad
good and bad isn't what Meta and AWS is running with. If AWS trains willy nilly on user data like Meta does, AWS is toast. AWS is already taking a huge risk by now using their own take of AWS FDEs competing against their established ecosystem of consulting companies that used to recommend all 583 of AWS products to host a static webpage. Turning of more customers by training on their data is too much of a risk. That's the "good" - a risk analysis.
Meta doesn't care if you stop using Facebook, Whatsapp etc. Frankly, if you are embedded in the Facebook, Whatsapp ecosystem, you don't have a way out as a normie. Even if you are technically capable, good luck publishing your custom Mattermost build for iOS.
Meta has a significant amount of investment in hardware, originally due to Metaverse. The way to monetize that investment is inference and training. That's a do or die decision for Meta. Meta isn't releasing open-weight models because they are "good".
Meta is releasing open-weight models for the same reason Alibaba, NVIDIA or IBM does. Or Google releases Gemma.
There's no "good" or "bad" - the moment Alibaba, NVIDIA, IBM or Google's objective functions change, "Do no evil" will quickly morph into "Do as much evil as necessary without the costs of getting caught exceeding E(outcome)"
> Meta has a significant amount of investment in hardware, originally due to Metaverse.
Metaverse was 4-5 years ago already wasn't it? That hardware is verging on obsolete.
There's a reason companies tend to prefer to acquire over in-house. This is part of the calculus.
That explains a lot. They are anti “move fast and break things” which is great news for enterprises or anyone seeking stability but terrible for innovation.
I don’t condone the use of pirated content for training. But anything that was bought is above the board as far as I’m concerned. Can let the lawyers fight out the minutia and inevitable licensing specifics after the fact (book publishers are hawks).
Fun fact, did you know that every library in the world has an independent contract with every major book publisher?
In cases I am familiar with, they added a condition that a physical book can only be lent X times. After that, the library must purchase a new copy (even if the original copy is in pristine condition). Yeah, hawks.
Seems like what you would get if you were customer-centric and building a cloud platform for enterprise and govt to trust which was all set up pre-AI
What you are citing appears to me as a business use case of classical machine learning models not necessarily LLMs, and demand forecasting. Frontier AI is clearly not dependent on such data, and has many outside data sources and I'm even sure sensitive AWS data would be of good use as training data, not to mention the legal/contractual obligations AWS has in protecting that data, what am I missing?
That was just an example anecdote to highlight the culture around respecting privacy and security. Obviously AWS would never allow for training on customer data, but even for metadata or data of our own internal systems, things are super strict.
Public datasets that are liberal with licensed access is one thing, but the best frontier labs clearly went well beyond that.
this. the culture that makes AWS the gold standard in cloud security (yes, it is still the best in the business despite the one-off embarrassing CapitalOne incident) with a strong emphasis on locking down data, minimizing PII, and saying “no” by default, is the very opposite of what building frontier LLMs is all about, which is really around hoovering up vast amounts of other peoples data and moving fast before the rules catch up.
Amazon chose for itself a reputation as a place that nobody with a choice will work. I'm pleased to see that pay off.
| Country | Estimated full-time employees | Broad working range |
|----------------|------------------------------:|--------------------:|
| United States | 850,000 | 750,000–950,000 |
| India | 115,000 | 100,000–125,000 |
| United Kingdom | 68,000 | 55,000–75,000 |
| Canada | 40,000 | 30,000–45,000 |
| Germany | 36,000 | 30,000–40,000 |
| Spain | 27,000 | 23,000–30,000 |
| France | 23,000 | 19,000–25,000 |
| Italy | 17,000 | 14,000–19,000 |
| Poland | 17,000 | 14,000–19,000 |
| Japan | 13,000 | 11,000–16,000 |
| Mexico | 13,000 | 10,000–15,000 |
| Australia | 6,000 | 4,500–8,500 |
| Ireland | 6,000 | 5,500–6,500 |
| Singapore | 2,400 | 2,000–2,500 |
That's a lot of "nobody"
Not an employee, just have a "shit ton" of Amazon stock that has been beating inflation very well. The last few quarters of volatility has allowed me to buy and sell, often fully covering my monthly expenses. I'm very greatful for that. Far from a company "nobody" wants to work for. You have a better performing company than Amazon to recommend that I can use instead? I'm all ears and I'll even give you a kickback for your time!
ask any of those nobodies if they would rather work somewhere else instead lol
are those Amazon Web Services coders? AI experts?
or are they warehouse and package monkeys and logistics?
800k warehouse workers doesn't mean shit w/r/t AI development
This is a fair take. However, when it comes to warehouse automation/logistics, I constantly see what they're adopting in their hardware stack.
They're a good data point on where the robotics labor frontier is.
>I constantly see what they're adopting in their hardware stack.
like pee bottles.
That innovation has also mostly come in via acquisitions.
So it's a good place to work if you're a robot?
00000000: 6e6f 7420 6576 656e 2061 7320 6120 726f not .even as a ro
00000010: 626f 74
This is what my roomba said when it took me 3 days to find it and cut the hair rolled onto it's wheel.
This is what I've heard from my friends both there and at Meta. It definitely doesn't carry the prestige it once did. It's more like, "willing to get yelled at, be afraid of being put on a PIP every day, and trying to ensure output outpaces your peers". That's sad, but it's where the industry is at so many places right now.
Amazon offers good signing bonuses that pay out over two years, so it's very common to peace out right at the 2-year mark when your take-home pay abruptly goes way down and the grind is no longer worth it. That's what I did, and I noticed it almost everywhere: there's a constant revolving door of inexperienced people. I don't understand how they keep it going with so much turnover, but somehow they've built a system that kinda withstands it, except in frontier AI apparently.
I think it's coasting on that prestige of being FAANG. People still want it on their resume. I share this from time to time but I interviewed there at the same time I interviewed at Facebook (right before the name change). And the difference was night and day. Amazon truly treated me like cattle. Get in, do the automated Leetcode/HackerRank thing. Canned conversations. Facebook at least _seemed_ like they were rooting for my success the entire time.
I will say it’s an excellent place to learn on-the-job engineering fundamentals as a junior if you’re ok with the otherwise shitty culture for a year or two. The high turnover also means they’re really efficient at training new people.
They still pay a lot. The comment you replied to is mostly wrong about the 2 year cliff. Year 3 and 4 should be higher comp if you have good ratings.
Doesn't AWS stack rank? So having good ratings has a low relationship with your delivery.
Exact same experience.
Amazons interviews were so formulaic and it’s interviewers so robotic it was almost sickening.
Because all humans are 100% fungible with all other humans. So, you can take whatever old humans you have, throw them away (or make them want to leave), and then replace them with all new humans, with zero negative effect on anything. Rinse and repeat.
Human experience means nothing. Anything that does have meaning gets encoded in the system for the mindless humans to implement.
That’s my take on the view from the top, based on my time working at AWS.
Works great for the business too. I recently worked in a business unit with a 2 year vesting model. I loved the work and challenges.
.. and then got let go at 22 months in favour of the AI budget.
Gotta respect the hustle.
How is that a "signing bonus" and not just a pay cut?
If you chart money in your pocket per unit time, it takes a dip around 18 months where your average pay is less than your first month’s pay. (When I was there, using RSU numbers for that time.) Guess when average quitting time was?
HR swore it wasn’t on purpose and I was somehow measuring pay “wrong” by looking at money in my pocket over time; but knowing their HR, I’m sure the valleys in transition from signing bonus to vesting are intentional.
Is this weeding out long termers (willing to wait years to vest) vs the impatient?
This is where Bayes bites in practice: we can know that impatient and long-minded behaviors are correlated to outcomes, ie p(quit | impatient), without the outcome meaningfully informing which case we have, ie p(impatient | quit).
That’s because people are complicated and do things for many reasons, so people quitting when we cut their pay might not tell us they’re impatient.
I suspect the intent is what you say, but I don’t think the outcome is.
Was s3 the last time Amazon showed lab grade innovation? Lambda?
I could be wrong because I haven't paid much attention but Amazon has just fast followed everyone else innovation for a awhile so it's in like one ecosystem yeah?
I'm not trying to be snarky, I just haven't thought about aws as having any innovation for a while and I always figured it was because ruthless companies that churn through people as disposable commodities generally don't do tech innovation.
I'm talking on the AWS side, on the logistics side they clearly are doing insane things on supply chain perf optimization.
Dunno about that, but my experience with AWS is their stuff generally works, the other big 2 doesn't.
Generally speaking, on AWS you can buy compute, storage, network and other basic 'goods' and just like a supermarket where you can get either flour and eggs, a cake mix or a ready-made cake, AWS is willing to serve it to you in various levels of ready-ness, and you can start at the level you want, and build your own layers on top if you don't like AWS's solutions.
And AWS's solutions are generally built like that as well, there's no magic to Lambda or Fargate or EKS, its just they run the same EC2s, but with some proprietary magic that lifts some complexity from your shoulders, at the cost of generally some markup, and loss of some otherwise desirable features.
But the core thing is that AWS's offerings are generally solid, so as AI evolves and companies become more willing to take on more complexity, they will move to lower level services, but not necessarily out of AWS itself.
> I could be wrong because I haven't paid much attention but Amazon has just fast followed everyone else innovation for a awhile so it's in like one ecosystem yeah?
A lot of innovation at AWS is invisible on the outside. They pioneered hyperscale datacenters with publicly accessible capacity, software-defined networks, secure VMs, and so on.
> I'm not trying to be snarky, I just haven't thought about aws as having any innovation for a while and I always figured it was because ruthless companies that churn through people as disposable commodities generally don't do tech innovation.
I worked at AWS before COVID. It was really a varied experience, but it was not _bad_ overall. We prided ourselves on making sure our APIs are solid, stable, and backwards compatible. When we had to make a backwards-incompatible change, we actually contacted every affected customer and ensured that their workflows wouldn't be broken.
Oh for sure, these many years AWS has set a high bar in the service space for conscientiousness in offerings. When I compare to my personal work experiences with gcp and azure the amount of times I've been rug pulled over the years has been essentially zero for AWS.
Nitro?
They have no doubt realized that hosting third party models is far more profitable.
Let someone else take on the research and training costs, and charge a massive premium for your hardware.
There is intense competition in the AI industry, especially with AI firms in China driving down prices, so it seems likely that LLM's and software products may become fungible commodities that trade close to marginal cost = marginal revenue = minimum average total cost. In other words, most of the profits from AI and software development will be competed away, eventually.
Data center hardware, by contrast, is a scarce commodity with rapidly growing demand, and therefore likely to capture most of the profits from AI and software development, if current market conditions persist.
Today's IT business trends represent a remarkable change in the industry compared to the situation 50 years ago, when startups like Microsoft and Oracle, whose business models were based exclusively on software development, challenged and overthrew the dominant player, IBM, whose primary source of revenue was from hardware.
> Let someone else take on the research and training costs, and charge a massive premium for your hardware.
the linked article is from July, it is almost three months old.
Now there may be a very relevant recent story; it has the potential to reduce the flow of new open weight models. This could change quite a few expectations, which are based on open weight models:
"China’s STAR 50 Index Falls 40%, Erasing $480 Billion as AI Stocks Crash"
https://www.technology.org/2026/10/27/china-ai-stock-bubble-...
https://www.reuters.com/world/china/china-ai-bubble-has-alre...
Reuters says there is a run, but also deeper reasons:
"There has been no obvious selling trigger in China, although traders said high prices, tax bills and the threat of the US or other nations banning Chinese equipment in data centers all contributed."
So far I don't see any discussions of this story on HN, interestingly.
The article implies they are wrapping up their current models, and instead aiming to go all in on a frontier class model?
“Instead, labor and computing power are being diverted toward a singular “frontier-model effort””
Sounds like the opposite of what you're suggesting they're doing?
Seems like the smartest move. Microsoft went all in and have really not got much out of their efforts.
> Microsoft went all in and have really not got much out of their efforts.
The problem was rather that Microsoft had no real plan what they wanted to get out of AI. If they had a plan, they could have laser-focused their all-in on AI.
Instead, Microsoft just AI-slopped a lot of their bread-and-butter products, making them much worse than before. If AI is as revolutionizing and beloved by users as Microsoft believes, Microsoft could easily have created an offering like "Windows AI Pack" or "Microsoft AI" that should sell like hot cakes.
On the other hand, if you have to force AI functionality onto the users, it should be considered as a strong sign that perhaps it is not something that the users want.
They forced Teams on everyone and it played out well for them. Users not wanting it might not itself be a sign that it's bad for business.
Regular ppl i.e non-techies love the copilot integration into all office products. Since techies know better, they think microsoft messed up with the AI integration everywhere.
Regular people don’t even upgrade to Win 10/11 unless they are forced to.
Even tech-adjacent folk in areas like product, user research and enterprise architecture seem to love it.
The bulk of the hands-on-keyboard time for those disciplines now seems to be using Copilot 365 as "fancy autocomplete" and "make this presentation better", Copilot Notebooks for deeper work, and coming up with all sorts of Copilot integrations and agents for managing email, Teams meetings and chats.
It's almost as if "copilot" has already become the generic term for "professional LLM", and many genuinely can't understand why us techies find it so limiting.
> Regular ppl i.e non-techies love the copilot integration into all office products.
Do they, actually?
no regular person i have met loves AI integration with anything
3 of the 4 orgs I consult with have actively warned people not to use it, and/or to only use their approved AI tool (OpenAI/Claude/Gemini)
clippy 2.0 is not selling well
I, for one am very thankful for what Microsoft did with Windows 11. It has exactly the feature set, and AI value-add ... to inspire me to take the plunge to Fedora Workstation and I've never been happier. Even Steam games (kind of) work. More importantly dnf update -y becomes exciting.
Windows (and increasingly Apple) updates are more of a sigh and lip biting experience than an exciting one.
I'm really happy not to have touched Windows recently at all.
At work Microsoft's updates are buggy - Outlook and Teams are pretty awful on corporate Macs. Teams especially, it has a bunch of papercut type annoyances. And updates torture Corp IT.
Just as there is product-market fit, there is also product-company fit. Amazon as a company has their own cost of capital, earnings expectations, talent distribution, and organizational capacity. It is not a place where the best of the best work in mainline product development, nor is it a place that is willing or able to go through long periods of losing money in order to rapidly improve the product. The Amazon of old did that, and had different capabilities, but today's Amazon is not the same company.
Notice that you also see Google really struggling (and falling behind) in the AI race. This, despite massive resources and being responsible for key pioneering research. Same reason why IBM has failed in this area. The big established companies tend to shut their brightest people into research departments where they write papers and produce demos while the main cash cow areas remain undisturbed, so they have collections of bright people and they have money, but they rarely let their brightest people make big bets with the money, whereas startups do.
It's also why poor people spend more on lottery tickets than rich people.
The best of the best do work at Amazon. Their cloud infra is world class. They just cannot compete in the ai/ml space with different economics. It’s an operational company and not one to do tech innovation.
Basically you want to run an LLM, Amazon. You want to build an LLM not Amazon
handshake meme with Amazon and Apple
Either you are getting the smartest engineers, or offer the most freedom to pursue interesting goals that aren't on the frontier. Amazon has neither so they naturally aren't going anywhere in that domain.
Or AI has been over promising and under delivering for half a decade. Amazon is just one of the dominos. This is a hedge by Amazon.
On what planet has AI under-delivered since 2021? Because it certainly isn't planet Earth.
Where? I am not aware of any significant business improvement on the actual bottom line.
We all feel more productive. But did your rust rewrite or my fancy react dashboard produce more value?
I advise a B2B startup that went from 4 developers to just the founder, who is technical but not a developer. It is now profitable and delivering just as many features with arguably better security. N=1
So how is this startup going to be a value add long term? If they can cut all the devs, what moat is there? What's stopping their customers from just prompting their own model?
Seriously asking, why would this look like a good business model to be in? If they don't need anyone besides a technical non-developer to create the product, why would this look like a good business? If it's B2B, then most of their customers will have that type of IT person on staff.
A dry cleaner and a car wash can be a good business. Outsource things that are not your core competency. A moat means you can defend it better, but in this case your business can capture the value of them not having the IT person on staff and not having to spend the tokens. It’s a good old fashioned business.
a regular business is not a startup though. A startup implies a much higher ceiling on growth and profit. Worth investing in on a high risk, high multiple of return manner. An SME sized business is not that.
Wait... Are anthropic and openai just commodity suppliers? Because dry cleaners and car washes both need soap, but I've never heard of a trillion dollar soap company.
AWS, Azure and GCP supply a commodity -- compute -- yet each one of them could be a trillion dollar company in its own right. Even when on-prem is nominally much, much cheaper than cloud services.
Turns out there are ways to monetize commodities, to the tune of double-digit billions in revenue per quarter.
If it were true that what OpenAI and Anthropic offer were commodities, that there is no moat, Microsoft could trivially eat their lunch. There would be no OpenAI. Google with its nation-state money, extreme AI talent, chips, datacenters, could eat their lunch.
So mighty Google can't manage it. But it's a commodity that's easily copied.
Somehow HN can't reconcile the contradiction even though it's laughably obvious.
Hey anybody could go MVP a ride hailing app over the weekend. It's a commodity app. Should be super easy with LLMs.
Oh shit, wait, you mean I'd have to take a billion users away from GPT and getting those users is now 50x harder than it was four years ago? You mean it's drastically harder to peel users away from existing services than if you get to start fresh? Ohhhh.
They have gigantic moats and so long as they don't do anything too stupid, those moats will just get stronger with time.
No VC is giving you money to try to run down OpenAI and Anthropic. Nobody is writing that $100 billion check. It's already over, HN is just in its standard denial phase.
The Chinese could definitely eat their lunch if the US didn't decide to limit access to SOTA hardware.
So you could argue their moat is US government, not their model. I don't disagree with you, just saying what is their real moat.
OpenAI's moat is the userbase and service layer, which is gigantic. It is extremely difficult to pull users away from giant services.
The Chinese models have no great branding with the masses, they have no service layer that any average user understands. Where does Joe go to use the Chinese model that he doesn't even know the name of? Joe has no clue what the difference between DeepSeek and Kimi is, and Joe will never know that.
They all know ChatGPT, they have all been trained on how to use it and what it is. The inertia is enormous and HNers endlessly undercount how that works because deep tech users all want to think the masses view tools like they do and approach tech like they do (which is entirely false).
OpenAI's future is as an ad platform in terms of its business. That's at least 2x-4x larger as a business opportunity than anything they have going on now. Which is to say $80-$160 billion minimum. That requires they maintain the giant userbase, we'll see how that goes. Losing it requires someone take it from them. Joe isn't just going to wake up tomorrow and go seek out how to use Kimi.
The LLM space is worth a minimum of half a trillion dollars per year in ad revenue. It will subsume all of search. Search becomes merely a service of an LLM, which will perform the function on your behalf. Google is on top of that shift, so OpenAI has its work cut out for it competing with Google there.
Of the US big three, Anthropic is by far the one most threatened by the persistence of the Chinese models. Anthropic will probably never stop being chased by them and will have to endlessly race to try to stay ahead. Anthropic has to figure out how to build out the LLM+ equivalent of AWS before China figures out how to beat them, ie build a very deep service / tool moat around Claude that the userbase gets stuck to. In short dramatically increase the difficulty in peeling away users, it has to become a big chore to switch (which eventually this is exactly what someone will figure out in that area of LLM competition).
The hard lesson is that quality will be the new moat.
For decades, velocity, time to market and features all drove the industry. But AI puts speed in everyone's hands.
But quality is still hard. Maybe harder than ever.
Not to mention the possibility of 4 competitors popping up over night.
The question is "what business value is AI driving?" and the answer was "a solo founder cut all the devs and still delivered a product".
Separate question: "now that AI is here and development isn't a moat any more, how does a business defend itself from competition?"
That second question is a direct result of AI. Five years ago the amount of cost and effort spent on software development was a moat. Now it's not. So that answers the first question completely, I think.
As for the second question - market sector knowledge, customer contacts and industry reputation, all the usual non-technical things that make a moat. Also, we may now be living in a world where software companies cannot expect to be monopolies in their markets any more. This company will have to compete with many similar competitors for market share, like in most other markets. I think this is a good thing. Less enshittification will ensue.
No extra value was generated in the example. If anything, AI in this example reduces the price of the product AND employment.
Value was destroyed.
The hope is that all these unemployed engineers can somehow generate value? Even if they do they need to generate enough value that would employ 4 engineers.
I think this is Broken Window fallacy[0], though.
If a business can create software cheaper, then it can charge its customers less for that software (or, conversely, if a business can use an AI to create bespoke software for cheaper than it would cost to buy that software) then the customer business saves money. It, in turn, can use that money to improve its offering to its customers. They, in turn, and so on.
Having cheaper things means everyone gets more things. The value created is created further down the supply chain.
[0] https://en.wikipedia.org/wiki/Parable_of_the_broken_window
I understand what you are saying, it just seems that this technology in contrast to any other productivity related technology is deflationary, because there is no alternative avenue to employ the idle labor. Not now, not in the future.
Where will people work on if both blue and white collar jobs go away? In brothels?
Good question, and the question of our age, for sure.
I loved the article that was on HN a while back (original article here [0] be warned it's a quite a long read). It compared the current revolution we're undergoing to the Mercantilist revolution when we stopped being farm workers and started doing other things instead, driven by technological change in agriculture.
The answer they came up with: we don't know yet. Much like the move from subsistence farmers who started working in a factory had to rely on other people to feed them, we have to answer this question ourselves and it'll probably involve doing something very different. And wonderful - subsistence farming is a shit life (despite all the influencers saying how amazing being in touch with the land is) and we would all prefer to be working in an nice clean office than trudging knee-deep in muck in the rain trying to keep our crops alive and pest-free. The same will probably be true once the dust settles on this revolution and we'll all be profoundly glad that AI came along.
The big problem we have to face as a society is that we cannot allow all the value from this technology to be captured and retained by the wealthy few. Our ancestors had to fight the same conflict with factory owners during the Industrial Revolution, and they didn't manage to win that war completely despite all the blood shed and battles won.
[0] https://contraptions.venkateshrao.com/p/cognitive-mercantili...
the wealthy few now have drone armies and control of the social and information sphere. i am not optimistic.
meh, they had cavalry and muskets before, and most of us couldn't read. Still lost.
What are some businesses where software was really a moat but the software lacks sufficient complexity that AI can reproduce it?
I can't think of any, I'm sure there are some, but I would really like to know. I just don't think for most business the software is so much of a moat unless it's very complex.
Well, the most recent example would be the Adobe suite rewrite [0]
[0] https://www.afr.com/technology/ai-can-make-free-copies-of-ad...
Wasn't that just a literal copy of Photopea?
Nope
yup, it's happening. many of the CEOs/CTOs of PE owned ISVs have their marching orders: put in strong product managers, software architects and other senior roles who define what to build and how the software should work, and thin out the developer teams, as agentic coding becomes the norm. Am not saying this makes for quality software, but this is where the industry is heading.
So the price of the product will just fall by 80%, unless nobody else cares to compete.
That's still increased productivity even if the consumer benefits instead of the business owner.
This is why capitalism must always find new markets or die btw.
A company doing more with less sounds great, but I personally view a shrinking headcount as failing
It's going to be funny when AI soon costs 4x or more than it does now, and that non-developer CTO can't understand the slop codebase the AI created.
> It's going to be funny when AI soon costs 4x or more than it does now
What exactly will cause that? Hardware costs are (generally) going down, and open weight models are getting smarter. The subsidised subscription prices will go away, sure, but I don't see the average token getting more expensive.
I also hope that rising costs return software dev to an elite, lucrative career. I’m not making my 10 years plan based on that theory, though.
Watch what the open weight models can do. Once they can manage your codebase, you’re safe from gouging.
But there still remains the possibility of error/hallucination. Do you bet on a future where AI will never make any mistakes whatsoever?
I am often told humans make mistakes, too. But this is an elementary logical fallacy because the type, frequency and severity of the problems is never the same.
Also, humans are more likely to do as told, whereas AI often takes liberties (i compiled a book from a github repo and it did things on its own in the book though i had explicitly forbidden that).
Where I work, we take on way more exciting and ambitious projects than we would have when I was hired. It's exhilarating at times. Genuinely, AI in general (not just LLMs) has radically transformed the types of work we can conceivably pursue and deliver on. We're an NGO so we have different staff than a regular tech company, but we're highly tech-driven. I don't doubt that this is the case at many orgs like ours.
And it's measurable. We don't just feel more productive; we get grants, we build systems, and we make plans we simply couldn't have before.
I'm not sure if I'm more productive, but in my role where most of my deliverables are technical documents or emails I think my output quality has gone up. Now that I typically use LLMs as a research assistant and editor before sending anything significant to co-workers or customers I'm sure I make fewer mistakes. AI catches a lot of gaps and errors. That's a significant qualitative improvement although I can't quantify that in terms of profit impact.
I think you're letting the LLM write emails that are overly verbose that are shortened on the other side by another LLM and so there are 2 minus habens to both side of a communications that are communicating the same stuff as before but now are paying for altman's yacht in order to do it
Nah, that's not what I'm doing at all. Did you even read my comment? I use it more like a fact checker. It's not perfect but it catches a lot of my errors.
Maybe you could use an AI assistant to help you write better HN comments.
Im surprised people still have this 2024-esque take
i add more value to my company because it lets me ship much faster, debug issues faster, onboard new people faster
total enterprise ai spend is climbing https://ramp.com/data/ai-index#adoption#overall
i know multiple stealth startups with 9 figure revenues and profitable and growing
lab arr is climbing
given the recent crackdown on token spend and from speaking to execs they are very focused on the exact ROI they will get from AI
Note that business revenues in competitive markets may actually not change that much, because if everyone is using the same models there's no competitive advantage from using AI. but if one of them didn't use AI they would fall hopelessly behind
If you're getting more done but unsure of the resulting value, that is indicative of your role not the tools you're using.
Actually, I think that is the very obvious incentive structure of generative AI.
We ship features faster and workers are more independent. They can get the answers they need faster than ever. And i'm talking about the business itself if the business has enabled that. There are a ton of productivity gains.
But make no mistake. Being more productive does not equal higher profits because your customers think you've added value. Both value and productivity are highly subjective terms which is why it is measured differently depending on where you work.
Most businesses adapted to AI by shipping a lot more features in smaller increments of time. What they should have done is become much more ambitious and build moon shots in two quarters instead. You need to go big or go home if you're going all in on AI.
AI is not about productivity. It's about weaponizing the ability to ship fast go-to market features in the blink of an eye when it becomes necessary. If trends change fast and you can't adapt quickly with AI: you're dead. So you need to have AI ready to go, just in case.
How is shipping features fast not productivity?
Having a special Gemini button everywhere is "a new feature", but it isn't a useful feature, so the productivity needle doesn't budge.
This is what the parent post said:
ship fast go-to market features in the blink of an eye when it becomes necessary
Necessary go-to market features are useful
I know it sounds crazy but for the amout of investments AI has underdelivered.
GPT 3.5 is 2022. In the past ~18 months the majority of all human software development has been wiped out and the models keep getting better rapidly. AI has already radically overdelivered and the biggest returns are in the next 10, 20, 50 years.
It's 1987: The PC is underdelivering.
It's 2000: the Internet is underdelivering.
It's 2010: smartphones are underdelivering.
Models are finally good enough that I'm confident that I can repeatably build pretty much any software reliably in less than 2% of the time that I could before 2022. I wouldn't have made that claim 6 months ago.
Even quantized local models like Qwen3.8 are good enough to handle a lot of drudgery. For example, I hooked my wife's computer up to a local model, and now she finally has a clean desktop. She just drops spreadsheets or powerpoints or whatever on her desktop and automation takes care of everything.
The caveat is that I developed software for 30 years, so I understand most of what it produces and can guide it to make fewer mistakes and fix what it can't do. The biggest challenge has been keeping my requirements focused - it's very easy to gold plate everything and prematurely optimize.
The biggest question I ask myself is why am I even still doing this. The smart people are probably already trying to figure out how to pipe raw matter and energy to their homes to build replicators.
The future is already here, it's just not evenly distributed.
Build experiences that are user dependent. The value isn't in the software it's in the users. That's the ultimate moat. It's what isn't properly grasped about GPT's position, insofar as they don't mess up big: they have captured a zillion users, they're Kleenex. Ask GPT = Google it.
You don't want to be in the CD selling or radio business with the Internet & digital & streaming & smartphones & iPods bearing down on you. Go for concerts. Notice that humans are spending more than ever on live concerts. Disney World and Disneyland still command extraordinary pricing power, despite everybody hiding inside on their phones.
LLM clones of eg Photoshop will end up being worthless, like ideas generally. The software will be worthless for the same reason ideas are: they're too easy. Users are hard, software will be (relatively) easy.
Is the value in McDonalds in the food? Everybody knows it's not. McD captured consumers, their heft is extraordinarily difficult to displace. Ie habits, brand awareness, location, etc.
"LLM clones of eg Photoshop will end up being worthless, like ideas generally. The software will be worthless for the same reason ideas are: they're too easy. Users are hard, software will be (relatively) easy."
I doubt that. If a clone out there offers all the Photoshop's features for free or much lower cost, without additional learning curve, then many professionals will switch to save money.
McDonalds would be gone too if somebody opened a restaurant chain serving similar food for free or 80% lower price. But that's impossible to do profitably, while freeware software has existed for a long, long time.
Photoshop users could switch to GIMP tomorrow. They don't want to.
The many professionals are the ones that could most easily understand how to switch to GIMP, which is free to use. They could save enormous amounts of money. They prefer to spend money and stick with Photoshop instead. That has persisted for a very long time now.
> In the past ~18 months the majority of all human software development has been wiped out
What the hell does this even mean? Literally half of the code in operation I the world is still COBOL. The fuck is this nonsense wiped out
It means in corporations across the globe, the majority of code is no longer being written by humans. That is over and it will only keep dwindling by the quarter.
Writing lines of code by hand is all of human software development? Pretty sure in all of those companies its still software engineers writing the code, even if they're using LLMs to do it.
Unless you're making the claim that software engineers aren't involved or that only writing code is software development.
Yes it means in corporations across the globe, the majority of code was no longer being written by humans long before the majority of code was no longer being written by humans.
Also remember, the majority of all human software development has been wiped out 18 months ago but the dwindling will keep going by the quarter until the majority of all human software development has been wiped out.
Nonsense. Nearly every software house in the world has just as many or nearly as many programmers as they did 7 years ago when GPT-2 was "too dangerous to release." You live in a very tiny bubble if you think most businesses are building software without humans. Total horse shit.
Microsoft is laying off 60,000 people. That's just the early pin prick of the layoff gusher that is incoming.
One million software developers will lose their jobs in the US over the next ten years.
The big firing waves will begin when valuations decline as the initial AI boom slows. That has started already, although it's early. Companies like CoreWeave will basically collapse. Investors will demand & reward the layoffs, efficiency push, the end of rah rah times will prompt the inflection on employment in tech. And it'll never be like it was ever again.
Microsoft isn't laying off 60,000 people. They offered voluntary separation agreements, but nobody was laid off.
For 1 million software engineers in the US to lose their job you'd have to shrink the industry by 62.5% and nobody is doing that. We employ more software engineers this year than last year, which was higher than the year before which was higher than a year before. Get off the social media and look at real statistics and news.
This gleeful nihilism isn't health friend
Those 60,000 people are being eliminated from tech jobs. That's a gigantic number. Microsoft is pruning. They'll do it the hard way if they have to with literal firings. They'd like to avoid that if they can, and they're in a position currently where they can afford to. Most companies are not going to be so gentle.
HN is in denial. Just watch what happens over the next ~36 months.
I'm disengaging from this conversation since you seem unwilling to engage with facts. 60,000 software engineers are not being laid off at microsoft, full stop.
> HN is in denial. Just watch what happens over the next ~36 months.
In all likelihood, massive worldwide recession due to combination of oil issues and debt-ai bubble popping. That will be combined with instability due to democracies cracking up, wars popping up faster and faster all the while the richest and most powerful people are increasingly desperate to destroy democracies before it is too late for them.
seems like the opposite is occurring, job postings are climbing and so is comp
software is easier to build -> the world builds more software
But yes, the act of translating spec into code as a 'programmer' is gone for good.
All companies are trimming fat by reducing headcount and the cover for that is "AI"
> Literally half of the code in operation I the world is still COBOL.
There’s no way this is even remotely true. JavaScript alone is probably 90+%, considering it’s on almost every website.
There is definitely an unanswered question as to what the metric, but no, JavaScript is not 90+% by any useful metric. Most code is not a website, and JavaScript penetration outside of the client-side code on a website and some GUI applications on various operating systems is almost nonexistent.
Remember that all of the code in operation includes code like the microcontroller in your mouse, the hundreds of chips in your car doing things like keeping the engine running or "window goes up when I push the button," the DVD menu (which is actually Java code), not to mention all of the staid systems responsible for things like writing your paycheck every other week.
Most of the web is php, so JavaScript isn’t even the primary language on the web.
To be fair, most of those Wordpress / LAMP etc. sites probably also do have at least some client-side js, so they'd count for both?
Making your engineers use AI with little to no measurable improvement, but with very measurable high cost, is not delivering
Astra, Fable, Opus 5.5 are drastically beyond the capabilities of the median software developer. It's not remotely close.
The bottom 2/3 of the human market is entirely dead. Their jobs are gone (AI-shored) they just haven't all gotten the forced retirement or pink slips yet, while they click a few more prompts for a few more pay checks. The frontier pushing forward will knock out most of the remaining top 1/3 without breaking a sweat over the next few years. The really good developers will graduate into babysitting AI as managers.
It is legitimately sad, it's millions of high paying jobs just in the US alone. It's going to be brutal on the housing market. Automation came for another field.
Software engineering isn't unique, if this is true then it's 99% of all white collar work. Those same software engineers are going to help automate every other job on their way out.
Correct. Everything will disappear, even hardware jobs and the trades but the people responsible with the automation jobs (software developers) will be the last to go.
Do you, personally, have a plan for the future? Like what are you doing about this, or are you hoping to be in the 1%?
I am improving my Spanish and staring at the massive savings that I have built up from my SV job. When my job goes and the industry is in flames, I am moving to Bolivia.
If you have a big mortgage and no savings, it’s going to be tough. Stop taking the Waymo now.
My income is not dependent on LLMs not taking all the software etc jobs from humans.
My suggestion to anybody staring this down is: do something for yourself while you can, while we're in the early going. Most people still have no understanding of AI, most tech employees are doing absolutely nothing interesting with it other than prompt prompt prompt prompt while at work and effectively doodling at home.
Go high value and go for the users. Do things that don't scale, that actually rings more true now than ever. Focus on areas of tech where it's really hard to get the users, where you have to practically hand acquire them to get started. Users are the moat.
It's not build the software and they will come. That's what nearly everybody has wrong about what is going on right now. The value is not in the software. Users, users, users, users - they should be your primary focus.
Also consider looking at software more as a layer related to something else you do, not as The Thing you do. Related to another service you offer, improving that service.
Let's say you started consolidating in the physical self-storage space ten years ago. You read that it was a very wide open field, where the market was not yet highly concentrated, 3/4 of the market was mom & pop operators. Over the next ten years you built up a lot of storage locations. LLMs can amplify your business, they can help you automate, layer better software on top of your physical business. You know what LLMs can't do? They can't build storage units, and humans love their storage space. That's just one example out of a zillion out there.
I don't get how anyone actively using AI can believe this. Astra sucks ass.
What AI lab is profitable?
And in before ‘JumpCrissCross chimes in about inference being profitable while ignoring all the investment costs needed to get inference to where it is.
Profitability is an awfully narrow metric.
It's a powerful metric. It captures to what extent something is sustainably possible today.
The full balance sheet captures the info. If the AI companies suck up all of our salaries and spend that money on R&D/training, they still aren’t profitable, right?
That wouldn't be sustainable, which is all I'm saying.
You'd think here, of all places, we'd look more toward adoption, disruption, and potential for future revenue.
>> Profitability is an awfully narrow metric.
I mean, if anything summarizes where we have gotten to as an industry this quote is sure it. From Uber using VC funds to subsidize growth to where the AI players are at...
none (unless you count google and meta),
but profitability is a very narrow view on the labs, and investors are pricing in future free cash flow
you need to take into account the derivative, what is their growth? their opex and capex? their revenue growth? their moat? New product lines and applications?
Not saying that it's a homerun, but there is a case to be made for the labs being wildly profitable in 4-10 years
Anthropic as of a few months ago.
That explains the 80 Billion loss on their IPO disclosures.
Have you looked at the difference between Q1 and Q2? There's a trend change where revenues have grown materially compared with costs
I mean, it literally does. Something like 70+ billion of those 80 billion are accounting adjustments because their debt is supposed to be handled in stock and their stock price skyrocketed.
While I was being facetious, Anthropic is nowhere close to being profitable in the normal, i.e., GAAP meaning of the term. It's only using unicorn fantasy lalaland financials that they are "profitable."
Before someone else jumps in talking about "unit economics": unit economics only matters if you can sell the units long enough to make the initial (capitalized) investment (i.e., R&D) back. Models aren't commercially viable long enough for the unit economics to work.
You're arguing the second quarter isn't representative of what they'll be able to sustain... that their revenue isn't durable? Let's see. But it's a profitable quarter
Using GAAP or woo woo logic?
Why have they needed to worry about profitability?
They have been chasing extreme growth with cheap money. That enabled them to hyper scale at a pace the world has rarely seen before. They have made the correct choice so far.
The absolute dumbest thing they could have done up to this point is slow down to try to turn a profit. They have not needed to. Market capture is the sole thing they should be focused on. Here's a hint: how many users does GPT have now versus three years ago?
There appears to be very widespread confusion about what purpose turning a profit serves and how business operations actually work.
Go back in time and tell Uber in ~2013-2015 that it needs to immediately become profitable and not focus on capturing the market.
Market capture didn't work so well for Uber, and it won't work for AI, and even less so for AI because you can't get a driver in China to take you to LAX airport, but you can use cheaper Chinese AI.
Uber has to pay back all the billions of dollars it wasted trying to get people to use their platform, and now I can't afford most Uber or Lyft rides, it's way too expensive. So did market capture really work if they had to raise their prices so much as to make the service unworkable for most people? The only time I take uber is if my company pays for it, and that is getting less often.
AI is also going to have to become way too expensive so they can pay back the billions (trillions?) it is borrowing. And, when everyone is laid-off or fired because AI took their job, then who's going to be paying for AI? I guess the companies that lay off all the humans will, but when the wealthy business owners realize they've replaced everything with AI and nobody is buying what they are selling because there's no more jobs, then what?
Sounds like they should worry about profitability, and a lot of other things too.
> market capture really work if they had to raise their prices so much as to make the service unworkable for most people?
Hate to say it, but in this case you’re not the market so you are irrelevant.
Here’s data from Chicago, USA, showing Uber and Lyft dominate the market now, so yes, it worked.
https://toddwschneider.com/dashboards/chicago-taxi-ridehaili...
That's great that they dominate a shrinking market, because few people can afford to pay $80 to go 15 miles.
Uber isn't dealing with a shrinking market. They're becoming critical transportation infrastructure and their business keeps expanding year after year.
$32b -> $37b -> $44b -> $52b -> $57b
That's Uber's sales growth year by year. And now they're solidly profitable.
The sole threat to Uber is the Waymo / Tesla automation angle. A merger is most likely there.
Why do I need to care about profitability as a business if I can capture a shrinking market? /s
It feels like a related statement to someone willing to burn their own country to rule over the ashes.
Huh? uber is an amazing success story given their market dominance and enterprise value created. of course the next kid on the block (Waymo) is going to do the same thing
The price of a given point on the intelligence frontier is only going to get cheaper, likely 10-20x over the next few years.
The latest Claude models are spooky. About 100x faster then a senior developer snd utterly spooky in the speed and depth of analysis.
This isn’t the “hallucinate everything” style of model like the earlier GPT models…
Too dangerous to release was 2019. Today it's only very useful for coding and other niche industries. It promised to automate all work and to usher in a utopia. Instead it helps programmers further enshittify Big Tech offerings. That's well short of any promise or expectation set out by boosters, paid and otherwise, for the last 7-ish years. Where's the civilization upending change? Where's the Beef(tm)?
Can you name 3 ways is positively impacted the average non tech persons life in a meaningful way? Meaningful would be more than the invention of the microwave, but not as important as a vaccine.
How about 6:
- File taxes and find issues that "accredited", "certified" entities missed. In one instance, my federal refund increased by nearly $5k. At $20/mo, just the refund is two decades worth of value.
- Appeal health, home and car insurance claims successfully
- Find out details of interesting plants without forking out tens of dollars for an app that claims to do the same but fails to do so most of the time
- Summarize never ending email threads with 20 disinterested parties who would rather not be on the email but have to respond to show they are "engaged"
- Write a convincing email to my mother in law why I cannot meet her this weekend and hold her hand through the tough times she's having with her ethnic neighbor who annoys her with their "ethnic" music and "smell of fish" BBQ
- Locate the user manual for my microwave and what that rapid 3 beeps every 1s for 2 minutes that starts at 10AM since the last 2 days mean
I am not going to make up 3 things but it meaningfully replaced Google search that became unusable crap.
Downside is that OpenAI is already having ads on their chat interface, so I guess it will be crap any time soon.
Help with health issues is turning into a big one.
My mother-in-law has a complicated set of medical conditions and sees half a dozen different doctors. Fable with max thinking came up with a bunch of interactions between drugs and conditions that her doctors hadn't considered. We've run its recommendations by one doctor so far and he agreed with everything.
My brother has one friend who used a frontier AI to diagnose his wife's uncommon cancer, and insisted on a test for that. It was correct and she's fine now since they caught it early. Brother has another friend whose wife had back pain after surgery; medical team didn't find what was wrong, he uploaded the scan, and the AI said "oh they left in a staple," which turned out to be correct.
I've started using it to work on a cookbook for the medically prescribed diet I'm on.
I have mixed feelings about this.
Sure it has replaced Google for a lot of people. But was that driven more by Google breaking search and actively ranking down good results and putting blocks in the way of seeing even the bad results?
Google had (have?) people using their service out of habit but built a hostile enough environment. We have this "contradiction" where non-tech folks are supposed to be difficult to move off "what they know" yet here we are where they are using ChatGPT to search and be a doctor.
Microwave took decades from invention to being normal. VHS took weeks. The difference was pornography.
Microwaves were popular from the beginning after residential models became avaliable in the 1960s.
But not ubiquitous, we didn’t get one until the late 80’s. And OTOH we had internet in 1996, and were among the early adopters in my town.
The internet was around commercially in the 1980s...
Microwaves are still of limited utility.
Well of course. That's like saying you can't make toast in the kettle, but it doesn't stop the kettle being useful
Microwaves are incredibly useful if you can do anything besides 100% power.
I'd argue they're the most useful kitchen appliance, except possibly for air fryers. You can cook almost anything in a microwave, usually faster and with less cleaning up than otherwise.
What's your point? What doesn't have limited utility?
Microwave ovens are of extremely limited utility. Happy now?
So is a pacemaker. Still, what is your point?
Microwaves, or microwave ovens? Because I can name all sorts of ways that microwaves have improved communications. So many long-haul telco links, and remote radio/TV stations, have been accomplished by microwave. It's a powerful method of transmission.
Unless you're specifically meaning microwave ovens, which are of "limited utility" in a full-service kitchen. I'd have to agree there.
My previous microwave oven was so intensely powerful, that I needed to dial down the power to "7/10" so that it would not destroy my frozen meals. I could never run it at 10/10. My current appliance is very nice, and has an automatic button to run until doneness. Works every time now.
1. destruction of the digital arts (music, 2d/3d art) industry
2. greatest hacking tool in history
3. greatest corporate espionage tool in history (stealing of Navier-Stokes solution)
4. greatest accountability transfer tool in history (whoops it was the AI that shot those missiles)
5. greatest capital raising tool in history (we use AI in our startup, and you should give us money)
6. greatest scamming tool in history (cloning people voices for scam calls, etc..)
Edit:Whoops, I didn't read "positively"
We're at the dot com boom stage of AI. You could say it didn't deliver because boo.com didn't make a profit or because the average person still used paper maps, but that was just because of momentum.
It's the same with AI. The technology is here now. My friends in financial advice and market research have not lost their jobs immediately, because of momentum.
I agree with this point completely, I think mine is also true in October 2026.
Democratization of information. I think it's a similar jump a pre-internet search to internet search...
I find it kind of odd that you equate a small oligopoly of intermediaries gatekeeping information as "democratization". Similarly Google maybe made it easy to find for a while, but that was/is not democracy either.
google? anna's archive? arXiv?
"democratization of information", maybe if you were too lazy to click on a google link
This is democratization of information in the truest sense because the AI can not only find information for you, like Google does, but even patiently explain it to you. We never had that before.
Like, a normal person is not going to open up an arXiv preprint from Google search because for approximately the entire population, it's going to be way beyond the limits of their comprehension. They won't even glance at the link, if Google even serves it up as a result.
But, with a chatbot, they could actually ask questions and get answers in a format they can understand. They may get a very rough understanding of the topic, but I would bet it's 100 times better than the same reference explained by modern "science journalism," which insists on presenting the most clickbait-y interpretation they can find.
And this is not theoretical, I've seen my high-school level kids figure out undergrad (or higher) level concepts like locality sensitive hashing with the help of ChatGPT, and I know they understood it because they could sketch out working solutions using those concepts. They didn't get the Mathematical underpinnings, but they understood the high-level behavior and that was enough.
Everybody can now understand anything if they really want to. Nobody is doing it today because they don't know it's possible. But they can, and we should encourage them to do so.
Linux (the kernel) and Git have done more in this regard, but think of FOSS in general. Without it, there wouldn't be Android. Without it, Windows NT would've won server space in the same way Windows won desktop space.
It is tools which are the commons (such as FOSS) and tools such as Wikipedia. But also open standards. LLMs cannibalize on these tools.
Furthermore, no customer wants an AI as customer bot. Especially elder people who are a bit computer illiterate can't find the real support (dark patterns). Can AI help a customer support representative? Oh, absolutely. AI can help a skilled person become better/quicker at certain tasks. But it cannot replace them, and it shouldn't either. If we do, we get all these 'fantastic' tools like *claw.
Opus 5.5 came out around a month ago, I'd give it some time before coming to that conclusion
Why? There's always some model that came out a month ago. It's been three years, what can we conclude?
My conclusion is that this technology is operating in roughly the same way as the personal computer, and that it's going to take similar timelines for the effects to manifest. We still haven't nailed down all the stuff AI is good at, and it's capabilities in known-good domains are increasing consistently. Engineers on my team are chaining together fascinating workflows that I imagine could be entire products, but things just aren't mature enough yet.
Advances are still coming rapidly -- we have quite a bit of time before this settles.
Amazon owns a big chunk of Anthropic. Plus they benefit from the rise of open models. They're being prudent.
Half a decade? More like 60 years.
Actually AI has been over promising and under delivering for about 70 years. Whether or not you think the juice is finally worth the squeeze, the distance we've come is impressive.
This article was published on July 29th. I’m not saying it may not still be interesting or whatever but I thought that was worth pointing out.
Anything AI related is going to start needing [month] tags.
> Amazon Is Gutting Its AI Division [July]
Indeed. I read this news around that time. I thought just now they did second round of AI purge.
I just played with Nova after seeing this submission. I gave it some real problems for which I used Gemini. It markedly "dumb" in comparison, losing sight of facts that I presented in the first prompt of the chat, and other subsequently introduced, and its responses contain repetitions of the same point-form advice. It's like GPT-3 level or something.
Original Business Insider article was submitted several months ago: 6 upvotes, 2 comments:
https://news.ycombinator.com/item?id=49082344
This isn't a blip on anyone's radar.
Well except for the regular HN anti-AI crowd. Usually the same people that have wished for communism and never ever looked in detail into the 20+ states that failed that way.
In Soviet Capitalism, model employs YOU.
Note that to someone who's been unemployed for uncomfortably long under Regular Capitalism might be interested.
The day is approaching when Anthropic and Open AI will reign as the next generation of big tech. I guess it's an unavoidable cycle. Big tech companies, having grown too large, find it difficult to innovate quickly, and new generations emerge to become the new big tech players. What comes after AI?
Nobody can know for sure but I am thinking that in the next 5 years one of the 2 will be dead and the last one standing will be sort of still depending in one way or another by the tech behemoths of today.
But Amazon has so many Applied Scientists even Applied Science managers. Not sure what they do though.
their innovation seems to be limited to renaming the forced sidebar on amazon.com every few months and not allowing me to dismiss their useless features.
Ublock hides the sidebar from me, but it does still take up the whitespace on the side of the screen. Now it won't remember that I dismissed it and it pops back in on every new screen. I am just used to the screen being narrower now. But it is still annoying.
The chatbot sidebar seems to also be the only way of accessing certain Amazon features, like the price history. And it seems to be implemented in a particularly silly way - clicking the "price history" button prompts the chatbot to show you the price history, rather than just showing it.
I think the forced-chat price history thing is a dirty way of trying to get people used to talking to the chatbot. Can't think of any other reason it would be designed so stupidly
They also started calling me and asking if I wanted to update my Amazon account to an Amazon Business account.
oof the sidebar on mobile is killing me
> Instead, labor and computing power are being diverted toward a singular “frontier-model effort” led by Pieter Abbeel
Strange headline given that it seems they are actually just refocusing resources to train a frontier model?
I actually think Amazon is very well placed:
- Single point of billing and vendor is still king in enterprise - look at how much of Ant's revenue flows through AWS Marketplace
- With OSS, models may move to a more of an AWS-shaped problem: host with 5 9s, provide the infra and shovels, do it as cheap as possible, fit them neatly into rest of AWS stack. I think this is actually a huge risk to OpenAI and Anthropic, as more commodization gives hyperscalers more advantage
- Still owns a huge chunk of Anthropic and leverage over compute
With this in mind, I'm not sure why they need a frontier model vs. the playbook they did with Linux (i.e. Kimi-K3-AWS-Enterprise-Edition). They are kind of playing both sides right now I guess, but could really stir things up if they wanted to.
Just occurred to me that Amazon seems interestingly positioned relative to the book sourcing thing. I guess that's still not enough.
I'm not at all close to knowing their internals with books in particular but for most products Amazon has made a significant effort to remove themselves from direct product stocking wherever possible (instead preferring to warehouse other people's stock for efficient shipping). I would guess that they aren't particularly well positioned with publishers at this point... Also, most publishers probably loathe Amazon at this point for all the times Amazon has tried to fleece them w.r.t. Kindle.
Tomorrow (October 28th) is the 1 year anniversary of being laid off from the Amazon Devices team. Nearly all of the senior people on my team were laid off at the same time as part of the "pivot to AI" strategy. Hurray for "commitment to accessibility".
This outcome for their years of squandered effort honestly doesn't surprise me as, other than the Graviton/Trainium work, the Amazon efforts were scattershot, half-baked and underinvested. Only the Siri team is more pathetic than the Alexa team. Well maybe Co-pilot stands between those two somewhere.
Amazon Nova is their model? I worked for a company that was being pushed into trying to use AWS's "Nova Act" [0], which I guess was their python-based wrapper to do things in Playwright. I didn't think it used Nova the model under the hood though, or maybe it did. Either way, Nova Act was horrible in terms of performance - it was so...damn...slooooow. Much easier to just use Playwright.
[0] https://nova.amazon.com/act
Yeah. I gave it a try when it first came out and never touched it again. It's just too slooooooooow
I can’t even get past the popup on mobile to try it…
It would seem that they can experience most of the benefit of AI without most of the cost; anthropic is operating at the frontier and shows that even while supplying the best models and token sales to enterprise, they lose massive amounts of money.
Amazon makes 60B+ in profit per year, they don't need to tank that by losing it on training AI / selling tokens.
There are plenty of open weight models out there for it to use with most of the benefit and very little of the downside.
Anyone that was any good in the AI space has long since fled Amazon/AWS. It’s just a sea of mediocrity on AI. Thus nobody is surprised by this.
> Amazon’s standout AI model — organized under the name “Nova” — is about the farthest thing from a household name.
I have tried asking people if they've ever used an AI product from certain companies, and you only seem to get "no", or surprise that they have any AI products, for some.
> Instead, labor and computing power are being diverted toward a singular “frontier-model effort”
They are just changing their strategy to invest in a single model? It's not like their AI department is in shambles...
Amazon operates by capturing others margin, they’re just waiting for more to develop
Well lately they are capturing their customers' margin for sure.
any to develop?
far wiser to sell shovels in a gold rush. let the miners take the risk. the shovel seller gets paid either way.
as an amazon shareholder, I applaud this.
Story from July OP;
Source: https://www.businessinsider.com/amazon-overhauls-ai-strategy...
Couple comments then:
https://news.ycombinator.com/item?id=49082344
That oughta fix it.
“So… what happened to the previous team?”
Alexa+ is pretty terrible. It's surprising how no one has beat them in the home device market. Alexa stagnated and died a product death while still being the standard market option for 5+ years. I was hoping LLMs would improve it but I haven't seen any evidence, even after purchasing their new line.
I might try Google's home option again but I'm not a fan of giving Google second chances since they seem to care even less about committing to products.
so who is going to be picked up by Amazon to replace their AI?
Amazon is not going to pay for AI internally, and sooner or later they will have to add something internal.
I started seeing so many ads for their SDK strands or something on reddit, so badly wanting tbe community to pick it up
"With urgent questions swirling over whether LLMs can ever usher in a return on investment — let alone AGI"
It will always remain weird to me that a publication called Futurism is so outright negative towards our newest technologies.
It's possible for both a new technology to be hugely beneficial in the long run & for early investors to lose a lot of money funding it (if they over-invested / over-paid).
Because anyone can apply any label to anything.
Values drive behavior. Who owns / runs futurism and what are their values?
Journalism / media as activity needs to be sustainable and unfortunately in our current world it's seems very difficult to sustainably remain high integrity. Sometimes it may be greed, but most of the time I think it's survival.
In this case AI is part of what is threatening journalist survivability, so it kind of makes sense.
"Instead, labor and computing power are being diverted toward a singular “frontier-model effort”".
If true, Amazon is not really gutting its AI division.
When will GPU servers become affordable
Too much backstabbing from legacy employees inside amazon to allow for grassroots innovation. Good work will get stolen or stamped out by coworkers. Vicious employee base intent on collecting their paychecks
3 cheers for bezos!
not a fan of recent AI wave. but if I wanted to be long on it I'd pick robots, drones and AMI (essentially +1 on Yann LeCun). if Amazon were to be refocusing/doubling-down on those areas too I'd respect it
Hard to innovate on AI when you're firefighting 30+ sevs a week.
funny story actually. I was recruiting an engineer from another stressful team. I pitched to him that we have about 4-6 sevs a quarter, and I was worried he would balk.
He said "that's nothing, when I was at Amazon we had 30 Sevs a week" .
I didn't feel so bad .
My impression of Amazon is that it’s a doer and is scrappy and gets things done at scale quickly. I just don’t see them as a place that is at the forefront of research.
AI labs are first research stuff. We see the things that work, but we all know that a lot of stuff in research fails. Nobody publishes their failures.
This is something that requires an ethos completely different from how amazon works and the way jeff bezos sees the world.
I wonder if the best play now is not to play and wait until the landscape is clear. They are making partnerships now (e.g OpenAI), and investments (e.g. Anthropic).
It doesn't make too much sense for Amazon to invest too much of their own money into AI.
They already sell a lot of the shovels for training and inference and make ample money from that, and there are enough open weight models on the market to make it infeasible to build a large enough moat.
Amazon doesn’t seem to agree:
> Instead, labor and computing power are being diverted toward a singular “frontier-model effort”
It’s a consolidation, not a withdrawal.
The remainder of your quote matters more, I think:
> Instead, labor and computing power are being diverted toward a singular “frontier-model effort” led by Pieter Abbeel, director of the Berkeley Robot Learning Lab whose robotics company Covariant was hoovered up by Amazon in 2024. At the time Abbeel joined the tech giant, Covariant’s founders were working on AI models for robots, which lines up pretty well with Amazon’s push to automate everything it possibly can.
Amazon can't hope to compete in the LLM genAI (what is colloquially known as AI anyway) space. That is toast, the race is over for them, too much competition, no way to make money.
But industrial automation? Globally, Amazon employs about 1M people in fulfillment/operations roles, the utter majority of their headcount. If there is one company on this world that has the money and compute capacity to spare for a high performance, real world application of fusion between modern machine learning and robotics, it's Amazon - and to make life easier for Amazon, unlike every other competitor they don't have to pay or partner with another company for real world testing. They can just go and deploy a robot in their warehouse if they want to.
Achieve a breakthrough in a fully automated picker robot, and they can save half a million people on their payroll, if not more, they'd save shrink loss and handling mishaps as well. That is one hell of an opportunity to save money by R&D. And if they patent everything they do, they can lock their competitors out of that technology for a loooong time.
Despite it being an old article things for amazon haven't changed:
you want edge inference, from decision to small models.
That's it. It will be 2c, please.
You want to be edging.
Such a stupid comment.
And yet Amazon has Alexa. They have a user base for a smart chatbot. What's Alexa going to run on for hard questions?
They could revert to the pre-LLM craze where Alexa was actually able to answer prompts in a reasonable amount of time. Alexa is a glorified egg timer for nearly all users - it's super convenient to use a voice prompt to start/stop timers while cooking and being able to play music on voice demand is kinda alright. It genuinely doesn't need to answer hard questions.
The new AI powered Alexa beta basically can't do egg timer, music, or light switch duties as reliably as the old Alexa, which basically makes it useless.
You'd think with all the data collected by these tech companies, they'd understand the common usage scenarios of their products. But instead we have AI Alexa that can't egg timer, or Gemini Assistant that can't navigate or make phone calls.
Here's how to fix it: "Alexa, exit Alexa plus".
Alexa had already been using other models like Claude depending on the question, and the French version for example uses Mistral.
Basic pre-LLM speech-to-text and a passthrough to duckduckgo would beat their current product, so...
Alexa+ was their LLM based release and to my knowledge it was an utter disaster and failure of product development.
Latency is the #1 UX killer on voice apps, and the latency was terrible compared to Alexa. I used it for like 15 minutes and reverted.
All anyone was talking about was how much worse it was for common tasks.
Wait so Microsoft gutted their AI Division and Microsoft looks like it did as well from the list of "departments" that are in the approved buyout list. Does this mean they are just going to be resellers of the big models companies going forward?
Outdated, sensationalist reporting off July 29 numbers that's already useless in the fast pace nature of the AI space. This is endemic of the last 5 years of "journalism".
The title is clickbait - Amazon is redirecting resources toward another major AI project and that does not, by itself, establish an overall "retreat from AI". The last 5 years have been a time of flux and now companies are starting to focus on niches and gaps in the market.
AI takes substantial focus and investment and we are compute constrained - AWS is correctly consolidating and refocusing by scaling back several of its existing Nova projects (Canvas, Reel) and concentrating resources on a new flagship model effort led by Pieter Abbeel.
If the claim is "sustained failure", what failed against which objectives? Technical capabilities? customer adoption? economics? delivery? The article does little to establish any. Consumer name recognition is a weak substitute for evidence about an enterprise model business!
A good report would have included benchmarks, revenue, or profitability evidence supporting the article's broad failure claim - this lazy "vibecoded" report doesn't even come near.
It credits Bloomberg while linking to Business Insider. That is a straightforward sourcing error - a journalism 101 no no.
If this is the new generation of shoddy, sensationalist "reporting", good riddance!
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We detached this subthread from https://news.ycombinator.com/item?id=50268257 and marked it off topic.
Please don't accuse people of writing AI-generated comments. If you suspect it, please email us: hn@ycombinator.com.
alright. thanks.
It's just basic economic theory applied to current IT market conditions.
Thanks for the reply. Yes, indeed, it's a great analysis.
I use AI so much that I too started hearing myself using the same phrasing as AI... not happy about it.
same here :)
The frontier of AI has gotten so spicy that the delivery risk of pursuing this rabbit is astronomical. Knowing when to quit and use someone else's solution is critical at this scale.
If someone started from zero, how long do we think it would take for them to reach the cost/capability front currently provided by gpt-6.1-terra? How long until OAI figures out a way to distill that down again for pennies on the dollar?
Apple seems to have this sorted. You won't find them chasing OAI, Google and Anthropic around the playground.
https://blog.google/company-news/inside-google/company-annou...
I mean, you don't start from zero, you distill everyone else's models....