I've seen a rumor going around that OpenAI hasn't had a successful pre-training run since mid 2024. This seemed insane to me but if you give ChatGPT 5.1 a query about current events and instruct it not to use the internet it will tell you its knowledge cutoff is June 2024. Not sure if maybe that's just the smaller model or what. But I don't think it's a good sign to get that from any frontier model today, that's 18 months ago.
The SemiAnalysis article that you linked to stated:
"OpenAI’s leading researchers have not completed a successful full-scale pre-training run that was broadly deployed for a new frontier model since GPT-4o in May 2024, highlighting the significant technical hurdle that Google’s TPU fleet has managed to overcome."
Given the overall quality of the article, that is an uncharacteristically convoluted sentence. At the risk of stating the obvious, "that was broadly deployed" (or not) is contingent on many factors, most of which are not of the GPU vs. TPU technical variety.
This is a really great breakdown. With TPUs seemingly more efficient and costing less overall, how does this play for Nvidia? What's to stop them from entering the TPU race with their $5 trillion valuation?
It's not a rumor, it's confirmed by OpenAI. All "models" since 4o are actually just optimizations in prompting and a new routing engine. The actual -model- you are using with 5.1 is 4. Nothing has been pre-trained from scratch since 4o.
Their own press releases confirm this. They call 5 their best new "ai system", not a new model
I can believe this, Deepseek V3.2 shows that you can get close to "gpt-5" performance with a gpt-4 level base model just with sufficient post-training.
I don't think that counts as confirmation. 4.5 we know was a new base-model. I find it very very unlikely the base model of 4 (or 4o) is in gpt5. Also 4o is a different base model from 4 right? it's multimodal etc. Pretty sure people have leaked sizes etc and I don't think it matches up.
New AI system doesn't preclude new models. I thought when GPT 5 launched and users hated it the speculation was GPT 5 was a cost cutting model and the routing engine was routing to smaller, specialized dumber models that cost less on inference?
It certainly was much dumber than 4o on Perplexity when I tried it.
Maybe this is just armchair bs on my part, but it seems to me that the proliferation of AI-spam and just general carpet bombing of low effort SEO fodder would make a lot of info online from the last few years totally worthless.
Hardly a hot take. People have theorized about the ouroboros effect for years now. But I do wonder if that’s part of the problem
Every so often I try out a GPT model for coding again, and manage to get tricked by the very sparse conversation style into thinking it's great for a couple of days (when it says nothing and then finishes producing code with a 'I did x, y and z' with no stupid 'you're absolutely' right sucking up and it works, it feels very good).
But I always realize it's just smoke and mirrors - the actual quality of the code and the failure modes and stuff are just so much worse than claude and gemini.
I am a novice programmer -- I have programmed for 35+ years now but I build and lose the skills moving between coder to manager to sales -- multiple times. Fresh IC since last week again :) I have coded starting with Fortran, RPG and COBOL and I have also coded Java and Scala. I know modern architecture but haven't done enough grunt work to make it work or to debug (and fix) a complex problem. Needless to say sometimes my eyes glaze over the code.
And I write some code for my personal enjoyment, and I gave it to Claude 6-8 months back for improvement, it gave me a massive change log and it was quite risky so abandoned it.
I tried this again with Gemini last week, I was more prepared and asked it to improve class by class, and for whatever reasons I got better answers -- changed code, with explanations, and when I asked it to split the refactor in smaller steps, it did so. Was a joy working on this over the thanksgiving holidays. It could break the changes in small pieces, talk through them as I evolved concepts learned previously, took my feedback and prioritization, and also gave me nuanced explanation of the business objectives I was trying to achieve.
This is not to downplay claude, that is just the sequence of events narration. So while it may or may not work well for experienced programmers, it is such a helpful tool for people who know the domain or the concepts (or both) and struggle with details, since the tool can iron out a lot of details for you.
My goal now is to have another project for winter holidays and then think through 4-6 hour AI assisted refactors over the weekends. Do note that this is a project of personal interest so not spending weekends for the big man.
I'm starting with Claude at work but did have an okay experience with OpenAi so far. For clearly delimited tasks it does produce working code more often than not. I've seen some improvement on their side compared to say, last year. For something more complex and not clearly defined in advance, yes, it does produce plausible garbage and it goes off the rails a lot. I was migrating a project and asked ChatGPT to analyze the original code base and produce a migration plan. The result seemed good and encouraging because I didn't know much about that project at that time. But I ended up taking a different route and when I finished the migration (with bits of help from ChatGPT) I looked at the original migration plan out of curiosity since I had become more familiar with the project by now. And the migration plan was an absolutely useless and senseless hallucination.
On the contrary, I cannot use the top Gemini and Claude models because their outputs are so out place and hard to integrate with my code bases. The GPT 5 models integrate with my code base's existing patterns seamlessly.
At this point you are now forced to use the "AI"s as code search tools--and it annoys me to no end.
The problem is that the "AI"s can cough up code examples based upon proprietary codebases that you, as an individual, have no access to. That creates a significant quality differential between coders who only use publicly available search (Google, Github, etc.) vs those who use "AI" systems.
Same experience here. The more commonly known the stuff it regurgitates is, the fewer errors. But if you venture into RF electronics or embedded land, beware of it turning into a master of bs.
Which makes sense for something that isn’t AI but LLM.
I recall reading that Google had similar 'delay' issues when crawling the web in 2000 and early 2001, but they managed to survive. That said, OpenAI seems much less differentiated (now) than Google was back then, so this may be a much riskier situation.
The 25x revenue multiple wouldn't be so bad if they weren't burning so much cash on R&D and if they actually had a moat.
Google caught up quick, the Chinese are spinning up open source models left and right, and the world really just isn't ready to adopt AI everywhere yet. We're in the premature/awkward phase.
They're just too early, and the AGI is just too far away.
Doesn't look like their "advertising" idea to increase revenue is working, either.
I noticed this recently when I asked it whether I should play Indiana Jones on my PS5 or PC with a 9070 XT. It assumed I had made a typo until I clarified, then it went off to the internet and came back telling me what a sick rig I have.
OpenAI is the only SOTA model provider that doesn't have a cutoff date in the current year. That why it preforms bad at writing code for any new libraries or libraries that have had significant updates like Svelte.
State Of The Art is maybe a bit exaggerated. It's more like an early model that never really adapted, and only got watered down (smaller network, outdated information, and you cannot see thought/reasoning).
Also their models get dumber and dumber over time.
I asked ChatGPT 5.1 to help me solve a silly installation issue with the codex command line tool (I’m not an npm user and the recommended installation method is some kludge using npm), and ChatGPT told me, with a straight face, that codex was discontinued and that I must have meant the “openai” command.
The fundamental problem with bubbles like this, is that you get people like this who are able to take advantage of the The Gell-Mann amnesia effect, except the details that they’re wrong about are so niche that there’s a vanishingly small group of people who are qualified to call them out on it, and there’s simultaneously so much more attention on what they say because investors and speculators are so desperate and anxious for new information.
I followed him on Twitter. He said some very interesting things, I thought. Then he started talking about the niche of ML/AI I work near, and he was completely wrong about it. I became enlightened.
Funny, had it tell me the same thing twice yesterday and that was _with_ thinking + search enabled on the request (it apparently refused to carry out the search, which it does once in every blue moon).
I didn't make this connection that the training data is that old, but that would indeed augur poorly.
Just a minor correction, but I think it's important because some comments here seem to be giving bad information, but on OpenAI's model site it says that the knowledge cutoff for gpt-5 is Sept 30, 2024, https://platform.openai.com/docs/models/compare, which is later than the June 01, 2024 date of GPT-4.1.
Now I don't know if this means that OpenAI was able to add that 3 months of data to earlier models by tuning or if it was a "from scratch" pre-training run, but it has to be a substantial difference in the models.
Pre-training is just training, it got the name because most models have a post-training stage so to differentiate people call it pre-training.
Pre-training: You train on a vast amount of data, as varied and high quality as possible, this will determine the distribution the model can operate with, so LLMs are usually trained on a curated dataset of the whole internet, the output of the pre-training is usually called the base model.
Post-training: You narrow down the task by training on the specific model needs you want. You can do this through several ways:
- Supervised Finetuning (SFT): Training on a strict high quality dataset of the task you want. For example if you wanted a summarization model, you'd finetune the model on high quality text->summary pairs and the model would be able to summarize much better than the base model.
- Reinforcement Learning (RL): You train a separate model that ranks outputs, then use it to rate the output of the model, then use that data to train the model.
- Direct Preference Optimizaton (DPO): You have pairs of good/bad generations and use them to align the model towards/away the kinds of responses you want.
Post-training is what makes the models able to be easily used, the most common is instruction tuning that teaches to model to talk in turns, but post-training can be used for anything. E.g. if you want a translation model that always translates a certain way, or a model that knows how to use tools, etc. you'd achieve all that through post-training. Post-training is where most of the secret sauce in current models is nowadays.
The first step in building a large language model. That's when the model is initiated and trained on a huge dataset to learn patterns and whatnot. The "P" in "GPT" stands for "pre-trained."
> Q: Are the releases aligned with pre-training efforts?
> A: There used to be a time not that long ago, maybe half a year, distant past, where the models would align with RL runs or pretraining runs ... now the naming is by capability. GPT5 is a capable model; 5.1 is a more capable model
I doubt it's that important that their dataset of current events is up to date. At this stage, I believe private and synthetic data comprises a large fraction of pretraining. Web search substitutes for current event pretraining.
I’m a GPT‑4‑based model that OpenAI released on March 14 2023.
The underlying training data goes up to early 2023, and the model was trained in the months leading up to that release. If you’re asking about the ChatGPT product that ships the model to users, it went live in November 2022 and has since received updates (GPT‑3.5, GPT‑4, etc.) that keep it current.
I’m a language model created by OpenAI. The current generation (GPT‑4) that powers this chat was first released in March 2023 and has been updated and fine‑tuned up through the end of 2024. My training data runs up to the beginning of June 2025, so I’m built on knowledge available up to that point.
OpenAI is basically just Netscape at this point. An innovative product with no means of significant revenue generation.
One one side it's up against large competitors with an already established user base and product line that can simply bundle their AI offerings into those products. Google will do just what Microsoft did with Internet Explorer and bundle Gemini in for 'Free' with their already other profitable products and established ad-funded revenue streams.
At the same time, Deepseek/Qwen, etc. are open sourcing stuff to undercut them on the other side. It's a classic squeeze on their already fairly dubious business model.
anecdotal, but my wife wasn't interested in switching to claude from chatgpt. as far as she's concerned chatgpt knows her, and she's got her assistant perfectly tuned to her liking.
> Google will do just what Microsoft did with Internet Explorer and bundle Gemini in for 'Free' with their already other profitable products and established ad-funded revenue streams.
“will do”? Is there any Google product they haven't done that with already?
Oh God I love the analogy of OpenAI being Netscape. As someone who was an adult in the 1990s, this is so apt. Companies at that time were trying to build a moat around the World Wide Web. They obviously failed. I've thought that OpenAI too would fail but I've never thought about it like Netscape and WWW.
OpenAI should be looking at how Google built a moat around search. Anyone can write a Web crawler. Lots of people have. But no one else has turned search into the money printing machine that Google has. And they've used that to fund their search advantage.
I've long thought the moat-buster here will be China because they simply won't want the US to own this future. It's a national security issue. I see things like DeepSeek is moat-busting activity and I expect that to intensify.
Currently China can't buy the latest NVidia chips or ASML lithography equipment. Why? Because the US said so. I don't expect China to tolerate this long term and of any country, China has desmonstrated the long-term commitment to this kind of project.
Literally got an email this morning from Google, to say my Google One plan now 'includes AI benefits' - including
"More access to Gemini 3 Pro, our most capable model
More access to Deep Research in the Gemini app
Video generation with limited access to Veo 3.1 Fast in the Gemini app
More access to image generation with Nano Banana Pro
Additional AI credits for video generation in Flow and Whisk
Access Gemini directly in Google apps like Gmail and Docs" [Thanks but no thanks]
I know it's been said before but it's slightly insane they're trying to compete on a hot new tech with a company with 1) a top notch reputation for AI and 2) the largest money printer that has ever existed on the planet.
Feel like the end result would always be that while Google is slow to adjust, once they're in the race they're in it it.
OpenAI has tons of funnels for their products. Azure’s AI smoke and mirrors offerings uses openAI behind the scenes, big with enterprise users (who has a lot of money)
> Google will do just what Microsoft did with Internet Explorer and bundle Gemini in for 'Free' with their already other profitable products and established ad-funded revenue streams.
Just some numbers to show what OpenAI is against:
GMail users: nearing 2 billion
Youtube MAU: 2.5 billion
active Android devices: 4 billion (!)
Market cap: 3.8 trillion (at a P/E of 31)
So on one side you've got this behemoth with, compared to OpenAI's size, unlimited funding. The $25 bn per year OpenAI is after is basically a parking ticket for Google (only slightly exaggerating). Behemoth who came with Gemini 3 Pro "thinking" and Nano Banana (that name though) who are SOTA.
And on the other side you've got the open-source weights you mentioned.
When OpenAI had its big moment HN was full of comments about how it was game over for Google for search was done for. Three years later and the best (arguably the best) model gives the best answer when you search... Using Google search.
Funny how these things turns out.
Google is atm the 3rd biggest cap in the world: only Apple and NVidia are slightly ahead. If Google is serious about its AI chips (and it looks like they are) and see the fuck-ups over fuck-ups by Apple, I wouldn't be surprised at all if Alphabet was to regain the number one spot.
That's the company OpenAI is fighting: a company that's already been the biggest cap in the entire world and that's probably going to regain that spot rather sooner than later and that happens to have crushed every single AI benchmark when Gemini 3 Pro came out.
I had a ChatGPT subscription. Now I'm using Gemini 3 Pro.
The way I've experienced "Code Red" is mostly as a euphemism for "on-going company-wide lack of focus" and a band-aid for mid-level management having absolutely no clue how to meaningfully make progress, upper management panicking, and ultimately putting engineers and ICs on the spot to bear the brunt of that organizational mess.
Interestingly enough, apart from Google, I've never seen an organization take the actual proper steps (fire mid-management and PMs) to prevent the same thing from happening again. Will be interesting to see how OAI handles this.
> fire mid-management and PMs to prevent the same thing from happening again
Firing PMs and mid-management would not prevent any of code reds you may have read about from Google or OAI lately. This is a very naive perspective of how decision making is done at the scale of those two companies. I'm sorry you had bad experiences working with people in those positions and I wish you have the opportunity to collab with great ones in the future.
>I've never seen an organization take the actual proper steps (fire mid-management and PMs) to prevent the same thing from happening again.
One time, in my entire career have I seen this done, and it is as successful as you imagine it to be. Lots of weird problems coming out from having done it, but those are being treated as "Wow we are so glad we know about this problem" rather than "I hope those idiots come back to keep pulling the wool over my eyes".
People sure are quick to say, "I hope you get to work with better management". Man, me too, but I find that dismissive of a legitimate concern: There is A LOT of incompetent management, especially in enterprise. The sad truth is that it is often the blind leading the sighted. When I was growing up I thought that the manager was someone with experience doing the job of those they managed, but across jobs I've had, this is the case about 20% of the time.
This code red also has the convenient benefit of giving an excuse to stop work on more monetization features... Which, when implemented, would have the downside of tethering OpenAI's valuation to reality.
The one successful example I can think of is Bill Gates writing a memo to re-orient Microsoft to put the Internet at the center of everything they were doing.
Your proper steps are also missing out on firing the higher level executives. But then new ones would be hired, a re-org will occur, and another Code Red will occur in a few months
The real code red here is less that Google just one-upped OpenAI but that they demonstrated there’s no moat to be had here.
Absent a major breakthrough all the major providers are just going to keep leapfrogging each other in the most expensive race to the bottom of all time.
Good for tech, but a horrible business and financial picture for these companies.
They’re absolutely going to get bailed out and socialize the losses somehow. They might just get a huge government contract instead of an explicit bailout, but they’ll weasel out of this one way or another and these huge circular deals are to ensure that.
Absolutely. I don't understand why investors are excited about getting into a negative-margin commodity. It makes zero sense.
I was an OpenAI fan from GPT 3 to 4, but then Claude pulled ahead. Now Gemini is great as well, especially at analyzing long documents or entire codebases. I use a combination of all three (OpenAI, Anthropic & Google) with absolutely zero loyalty.
I think the AGI true believers see it as a winner-takes-all market as soon as someone hits the magical AGI threshold, but I'm not convinced. It sounds like the nuclear lobby's claims that they would make electricity "too cheap to meter."
Maybe there's no tangible moat still, but did Gemini 3's exceptional performance actually funnel users away from ChatGPT? The typical Hacker News reader might be aware of its good performance on benchmarks, but did this convert a significant number of ChatGPT users to Gemini? It's not obvious to me either way.
Especially if we're approaching a plateau, in a couple years there could be a dozen equally capable systems. It'll be interesting to see what the differentiators turn out to be.
(My apologies if this was already asked - this thread is huge and Find-In-Page-ing for variations of "pre-train", "pretrain", and "train" turned up nothing about this. If this was already asked I'd super-appreciate a pointer to the discussion :) )
Genuine question: How is it possible for OpenAI to NOT successfully pre-train a model?
I understand it's very difficult, but they've already successfully done this and they have a ton of incredibly skilled and knowledgeable, well-paid and highly knowledgeable employees.
I get that there's some randomness involved but it seems like they should be able to (at a minimum) just re-run the pre-training from 2024, yes?
Maybe the process is more ad-hoc (and less reproducible?) than I'm assuming? Is the newer data causing problems for the process that worked in 2024?
Any thoughts or ideas are appreciated, and apologies again if this was asked already!
> Genuine question: How is it possible for OpenAI to NOT successfully pre-train a model?
The same way everyone else fails at it.
Change some hyper parameters to match the new hardware (more params), maybe implement the latest improvements in papers after it was validated in a smaller model run. Start training the big boy, loss looks good, 2 months and millions of dollars later loss plateaus, do the whole SFT/RL shebang, run benchmarks.
It's not much better than the previous model, very tiny improvements, oops.
I’m not sure what ‘successfully’ means in this context. If it means training a model that is noticeably better than previous models, it’s not hard to see how that is challenging.
You don't train the next model by starting with the previous one.
A company's ML researchers are constantly improving model architecture. When it's time to train the next model, the "best" architecture is totally different from the last one. So you have to train from scratch (mostly... you can keep some small stuff like the embeddings).
The implication here is that they screwed up bigly on the model architecture, and the end result was significantly worse than the mid-2024 model, so they didn't deploy it.
> the company will be delaying initiatives like ads, shopping and health agents, and a personal assistant, Pulse, to focus on improving ChatGPT
There's maybe like a few hundred people in the industry who can truly do original work on fundamentally improving a bleeding-edge LLM like ChatGPT, and a whole bunch of people who can do work on ads and shopping. One doesn't seem to get in the way of the other.
Far be it from me to backseat drive for Sam Altman, but is the problem really that the core product needs improvement, or that it needs a better ecosystem? I can't imagine people are choosing they're chatbots based on providing the perfect answers, it's what you can do with it. I would assume google has the advantage because it's built into a tool people already use every day, not because it's nominally "better" at generating text. Didn't people prefer chatgpt 4 to 5 anyways?
There are two layers here: 1) low level LLM architecture 2) applying low level LLM architecture in novel ways. It is true that there are maybe a couple hundred people who can make significant advances on layer 1, but layer 2 constantly drives progress on whatever level of capability layer 1 is at, and it depends mostly on broad and diverse subject matter expertise, and doesn't require any low level ability to implement or improve on LLM architectures, only understanding how to apply them more effectively in new fields. The real key thing is finding ways to create automated validation systems, similar to what is possible for coding, that can be used to create synthetic datasets for reinforcement learning. Layer 2 capabilities do feed back into improved core models, even if you have the same core architecture, because you are generating more and improved data for retraining.
ha what an incredible consumer-friendly outcome! Hopefully competition keeps the focus on improving models and prevents irritating kinds of monetization
>There's maybe like a few hundred people in the industry
My guess is that it's smaller than that. Only a few people in the world are capable of pushing into the unknown and breaking new ground and discoveries
OpenAI has already lined up enormous long-term commitments — over $500 billion through initiatives like Stargate for U.S. data centers, $250 billion in spending on Microsoft Azure cloud services, and tens of billions on AMD’s plan to deliver 6 GW of Instinct GPUs.
Meanwhile, Oracle has financed its role in Stargate with at least $18 billion in corporate bonds plus another $9.6 billion in bank loans, and analysts expect its total capital need for these AI data centers could climb toward $100 billion.
The risk is straightforward: if OpenAI falls behind or can’t generate enough revenue to support these commitments, it would struggle to honor its long-term agreements. That failure would cascade. Oracle, for example, could be left with massive liabilities and no matching revenue stream, putting pressure on its ability to service the debt it already issued.
Given the scale and systemic importance of these projects — touching energy grids, semiconductor supply chains, and national competitiveness — it’s not hard to imagine a future where government intervention becomes necessary. Even though Altman insists he won’t seek a bailout, the incentives may shift if the alternative is a multi-company failure with national-security implications.
"Even though Altman insists he won’t seek a bailout"
No matter what Sam Altman's future plans are, the success of those future plans is entirely dependent on him communicating now that there is a 0% chance those future plans will include a bailout.
OpenAI doesn't have $500 billion in commitments lined up, it's promising to spend that much over 5 years... That's a helluva big difference than having $500B in revenue incoming.
> the incentives may shift if the alternative is a multi-company failure with national-security implications.
Sounds like a golden opportunity for GOOG to step over the corpse of OpenAI and take over for cents on the dollar all of the promises the now defunct ex-leader of AI made.
What about OpenAI would rate a bailout? There's too much competition. If they ever do end up in a deep hole and plead for a rescue, I would imagine that gov will just force a sale of assets. Surely Google, MS and Amazon can make use of their infrastructure in exchange for taking on some portion of their debts.
"it would struggle to honor its long-term agreements. That failure would cascade. Oracle, for example, could be left with massive liabilities and no matching revenue stream,"
No, there's a not of noise about this but these are just 'statements of intent'.
Oracle very intimately understands OpenAI's ability to pay.
They're not banking $50B in chips and then waking up naively one morning to find out OpenAI has no funding.
What will 'cascade' is maybe some sentiment, or analysts expectations etc.
Some of it, yes, will be a problem - but at this point, the data centre buildout is not an OpenAI driven bet - it's a horizontal be across tech.
There's not that much risk in OpenAI not raising enough to expand as much as it wants.
Frankly - a CAPEX slowdown will hit US GDP growth and freak people out more than anything.
This is all based on the LLM architecture that likely can't reach AGI.
If they aren't developing in parallel an alternative architecture than can reach AGI, when a/some companies develop such a new model, OpenAI are toast and all those juicy contracts are kaput.
Heard all the news how Gemini 3 is passing everyone on benchmarks, so quickly tested and still find it a far cry from ChatGPT in real world use when testing questions on both platforms. But importantly the ChatGPT app experience at least for iPhone/Mac users is drastically superior vs Google which feels very Google still. So Gemini would have to be drastically better answer wise than ChatGPT to lure users from a better UI/UX experience to Gemini. But glad to see competition since certainly don't want only one winner in this race.
That's really fascinating. Every real world use case I've tried on Gemini (especially math-related) absolutely slaughtered the performance of ChatGPT in speed and quality, not even close. As an Android user, the Gemini app is also far superior, since the ChatGPT app still doesn't properly display math equations, among plenty of other bugs.
> But importantly the ChatGPT app experience at least for iPhone/Mac users is drastically superior vs Google which feels very Google still. So Gemini would have to be drastically better answer wise than ChatGPT to lure users from a better UI/UX experience to Gemini.
Yes, the ChatGPT experience is much better. No, Gemini doesn't need to make a better product to take market share.
I've never had the ChatGPT app. But my Android phone has the Gemini app. For free, I can do a lot with it. Granted, on my PC I do a lot more with all the models via paid API access - but on the phone the Gemini app is fine enough. I have nothing to gain by installing the ChatGPT app, even if it is objectively superior. Who wants to create another account?
And that'll be the case for most Android users. As a general hint: If someone uses ChatGPT but has no idea about gpt-4o vs gpt-5 vs gpt-5.1 etc, they'll do just fine with the Gemini app.
Now the Gemini app actually sucks in so many ways (it doesn't seem to save my chats). Google will fix all these issues, but can overtake ChatGPT even if they remain an inferior product.
It's Slack vs Teams all over again. Teams one by a large margin. And Teams still sucks!
Well I have been using Gemini and ChatGPT side by side for over 6 months now.
My experience is Gemini has significantly improved its UX and performs better that requires niche knowledge, think of some ancient gadgets that have been out of production for 4-5 decades. Gemini can produce reliable manuals, but ChatGPT hallucinates.
UX wise ChatGPT is still superior and for common queries it is still my go to. But for hard queries, I am team Gemini and it hasn’t failed me once
I've been a paying high volume user of ChatGPT for a while. I found the transition to Gemini to be seamless. I've been pleasantly surprised. I bounce between the two. I'm at about 60% Gemini, 40% ChatGPT.
I had a similar experience, signing up for the first time to give Gemini a test drive on my side project after a long time using ChatGPT. The latter has a native macOS client which "just works" integrating with Xcode buffers. I couldn't figure out how to integrate Gemini with Xcode quickly enough so I'm resorting to pasting back & forth from the browser. A few of the exchanges I've had "felt smarter" — but, on the whole, it feels like maybe it wasn't as well trained on Swift/SwiftUI as the OpenAI model. I haven't decided one way or another yet, but those are my initial impressions.
> But importantly the ChatGPT app experience at least for iPhone/Mac users is drastically superior vs Google which feels very Google still. So Gemini would have to be drastically better answer wise than ChatGPT to lure users from a better UI/UX experience to Gemini.
Opposite is true for a larger market. Gemini is great and available with one button click on most consumer phones. OpenAI will never crack most Android users by this logic of yours
Its really hard to measure these things. Personally I switched to Gemini a few months ago since it was half the cost of ChatGPT (Verizon has a $10/month Google AI package). I feel like I've subconsciously learned to prompt it slightly differently and now using OpenAI products feels disappointing. Gemini tends to give me the answer I expect, Claude follows close behind, I get "meh" results from OpenAI.
What are your primary usecases? Are you mostly using it as a chatbot?
I find gemini excels in multimodal areas over chatgpt and anthropic. For example, "identify and classify this image with meta data" or "ocr this document and output a similar structure in markdown"
Curiously, I had the opposite experience, except for Deep Research mode where after the latest update the OpenAI offering has become genuinely amazing. This is doubly ironic because Gemini has direct API access to Google search!
they're deep into a redesign of the gemini app, idk when it will be released or if its going to be good, but at least they agree with you and are putting significant resources into fixing it.
I couldn't even get ChatGPT to let me download code it claimed to program for me. It kept saying the files were ready but refused to let me access or download anything. It was the most basic use case and it totally bombed. I gave up on ChatGPT right then and there.
It's amazing how different people have wildly varying experiences with the same product.
This is exactly my experience. And it's funny -- this crowd is so skeptical of OpenAI... so they prefer _Google_ to not be evil? It's funny how heroes and villains are being re-cast.
Yeah, hate to say but for me a big thing is i still couldn't separate my Gemini chats into folders. I had ChatGPT export some profiles and history and moved it into Gemini, and 1) when Gemini gave me answers i was more pleased but 2) Gemini was a bit more rigorous on guard rails, which seems a bit overly cautious. I was asking some pretty basic non-controversial stuff.
For regular consumers, Gemini's AI pro plan is a tough one to beat. The chat quality has gotten much better, I am able to share my plan with a couple more people in my family leading to proper individual chat histories, I get 2 TB of extra storage (which is also sharable), plus some really nice stuff like NotebookLM, which has been amazing for doing research. Veo/Nanobanana are nice bonuses.
It's easily worth the monthly cost, and I'm happy to pay - something which I didn't even consider doing a year ago. OpenAI just doesn't have the same bundle effect.
Obviously power users and companies will likely consider Anthropic. I don't know what OpenAI's actual product moat is any more outside of a well-known name.
Gemini also will answer most queries where ChatGpt won't do a lot of things. Example: "Create an image of Snow white". This will give the stand "Violates our content policy" even though the story was written hundreds of years ago. You can even point out the story is in the public domain and it still won't do it.
I strongly advise never using Google's Drive storage. They're known to scan all content, and to disable all access if even a single file is "problematic", often misclassified by a bot. If you do use the storage, do backup all your files, and be ready to lose access at any time, with no way to reach any intelligent human.
Through my work I have access to Google's, Anthropic's, and OpenAI's products, and I agree with you, I barely touch OpenAI's models/products for some reason even though I have total freedom to choose.
Do you happen to know if the AI features of the Google One 5TB plan is equivalent to the 2TB AI pro plan? It is so difficult to understand what actually comes with their plans, and I want to have the 5 TB storage for backups.
If we stop for a while and really consider the value of AI tools, then comparing them on price doesn't make much sense. Any of these tools give hundreds, thousands, or tens of thousands of dollars of value per month to the user. With that in consideration they should mostly be compared on quality.
WSJ: Altman said OpenAI would be pushing back work on other initiatives, such as advertising, AI agents for health and shopping, and a personal assistant called Pulse.
These plus working with Jony Ive on hardware, makes it sound like they took their eyes off the ball.
it in't about taking eyes off the ball, it is about playing very different ball - they de-facto became commercial entity with short term plans/goals/targets/metrics and all the management games creeping in. Beating Google, such a large company who has been successfully playing that game for quarter of century is very hard, if not impossible until Google would make serious error itself.
And pure tech-wise - they seem to have went all-in on corp management understandable way of doing things - hardware(money) scaling which, while unavoidable in this game, must be accompanied by theoretic-algorithmic improvements as pure hardware scale game is again where Google is hardly beatable.
I don't think this is about Google. This is about advertising being the make or break moment for OpenAI.
The problem with ChatGPT advertising is that it's truly a "bet the farm" situation, unlike any of their projects in the past:
- If it works and prints money like it should, then OpenAI is on a path to become the next Mag 7 company. All the money they raised makes sense.
- If it fails to earn the expected revenue numbers, the ceiling has been penciled in. Sam Altman can't sell the jet pack / meal pill future anymore. Reality becomes cold and stark, as their most significant product has actual revenue numbers attached to it. This is what matters to the accountants, which is the lens through which OpenAI will be evaluated with from this point forward. If it isn't delivering revenue, then they raised way too much money - to an obscene degree. They won't be able to sell the wild far future vision anymore, and will be deleteriously held back by how much they've over-sold themselves.
The other problems that have been creeping up:
- This is the big bet. There is no AGI anymore.
- There is no moat on anything. Google is nipping at their heels. The Chinese are spinning up open source models left and right.
- Nothing at OpenAI is making enough money relative to the costs.
- Selling "AI" to corporate and expecting them to make use of it hasn't been working. Those contracts won't last forever. When they expire, businesses won't renew them.
My guess is that they've now conducted small scale limited tests of advertising and aren't seeing the engagement numbers they need. It's truly a nightmare scenario outcome for them, if so.
They're declaring "code red" loudly and publicly to distract the public from this and to bide more time. Maybe even to raise some additional capital (yikes).
They're saying other things are more important than "working on advertising" right now. And they made sure to mention "advertising" lots so we know "advertising" is on hold. Which is supposedly the new golden goose.
Why drop work on a money printer? What could be more important? Unless the money printer turned out to be a dud.
Didn't we kind of already know advertising would fail on a product like this? Didn't Amazon try to sell via Alexa and have that totally flop? I'm not sure why ChatGPT would be any different from that experience. It's not a "URL bar" type experience like Google has. They don't own every ingress to the web like Google, and they don't own a infinite scroll FOMO feed of fashion like Meta. The ad oppo here is like Quora or Stack Overflow - probably not great.
I have never once asked ChatGPT for shopping ideas. But Google stands in my search for products all the time. Not so much as a "product recommendation engine", but usually just a bridge troll collecting its toll.
IMHO Gemini surpassed ChatGPT by quite a bit - I switched. Gemini is faster, the thinking mode gives me reliably better answers and it has a more "business like" conversation attitude which is refreshing in comparison to the over-the-top informal ChatGPT default.
> [Gemini] has a more "business like" conversation attitude which is refreshing in comparison to the over-the-top informal ChatGPT default.
Maybe "business like" for Americans. In most of the world we don't spend quite so much effort glazing one another in the workplace. "That's an incredibly insightful question and really gets to the heart of the matter". No it isn't. I was shocked they didn't fix this behavior in v3.
I've found Gemini 3.0 Pro to be bad at multi turn conversation and instruction following. It ignores your follow up question unless you draw attention to it with caps or something.
Not a major complaint for technical work where you don't even want to do much multi turn conversation. Just an observation.
Is there a replacement for ChatGPT projects in Gemini yet?
That's the only ChatGPT feature keeping me from moving to Gemini. Specifically, the ability to upload files and automatically make them available as context for a prompt.
Ironically, the thing that annoys me most about Gemini is the Discord-esque loading messages in the CLI. Twee is one thing: mixing twee with serious hints is worse.
I think we are finally seeing the effects of the steady stream of departures of top researchers and leaders from OpenAI since last year. Sure you can declare a "code red", but who is going to lead the effort? Set the direction? Do the heavy lifting? Chart the path forward? Sam Altman is a salesman, not a researcher. Ilya is no longer around. Most of the other top brass has been poached by Google/Meta/Anthropic or left to start their own thing. The people left behind are probably good at iterating, but can they really make the next leap forward on their own?
I see google partnering with different companies to mine their data for AI, but I don't see that with OpenAI. They had a good thing going with Microsoft but it looks like that relationship is a bit sour now?
Surely they know that they can't just keep scraping the internet to train models.
If I don't use a Microsoft product, I'd have to go out of my way to use an OpenAI service. But they don't have a specialized "service" (like anthropic and developers) either. Gemini is there by default with Google/Reddit. To retain their first-to-market advantage, they'd need to be the default in more places, or invest in models and services that cater to very specific audiences.
I think their best best is to partner with different entities. But they lost reddit and twitter, and FB is doing their own thing too, so who's left? linkedin? school systems (but ChromeBook has them beat there), perhaps telecoms preloading chatgpt apps into phones?
In my layperson's opinion, I think they have an access problem. Windows 11/Copilot (Github and in windows) seems to be the main access stream and people hate both, and they don't have branding there either, just back-end. There is no device you can buy, service you can get that has an OpenAI branded thing on it as a value added feature.
I'm sure they'll do ok, but i keep hearing they need to do a lot more than just 'ok'.
No, I don't think they'll be okay. A long slow death perhaps, but I would be surprised if they can dig themselves out of this hole.
You can't beat Google on high-quality data for pretraining; at scale, that's what really matters most, both in theory and practice. Other companies like Anthropic and DeepSeek are keeping up by taking advantage of smarter RL approaches, but I just don't see anyone at OpenAI with the research credentials to do that kind of work as they all left in the last mass exodus. They have been too complacent and let much of their high-quality talent go to their competition.
It's all about the chip economics. I don't know how the _manufacturing cost_ of Google's TPUs compares to Nvidia's GPUs, for inference of equivalent token throughput.
But at the moment Nvidia's 75-80% gross margin is slowly killing its customers like OpenAI. Eventually Nvidia will drop its margins, because non-0 profit from OpenAI is better than the 0 it'll be if OpenAI doesn't survive. Will be interesting to see if, say, 1/3 the chip cost would make OpenAI gross margin profitable... numbers bandied in this thread of $20B revenue with $115B cost imply they need 1/6 the chip cost, but I doubt those numbers are right (hard to get accurate $ numbers for a private company for the benefit of us arm-chair commenters).
Yes, from the first principles perspective this AI thingy is just about running electricity through some wires printed on silicon by a Taiwanese company using a Dutch machine. Which means, up until the Taiwanese you have plenty of room to cut margins up until that point the costs are mostly greed based. That is Nvidia is asking for the highest price the customer can pay and they have quite a way to the cost that define their min price. Which means AI companies can actually keep getting better deals until the devices delivered to them are priced close to TSMCs bulk wafer printing prices.
Crazy how we went from google feeling like they were a dinasour who could never catch up to openai, to almost feeling like the opposite in terms of being able to catch up. All within just 1-2 years.
Thats like innovators dillema in action. Google had one of the strongest ML teams years before majoriry of AI companies was founded, but no desire to make a product that will compete with their search.
OpenAI was founded to hedge against Google dominating AI and with it the future. It makes me sad how that was lost for pipe dreams (AGI) and terrible leadership.
I fear a Google dystopia. I hope DeepSeek or somebody else will counter-balance their power.
That goal has wildly succeeded -- there are now several well financed companies competing against Google.
The goal was supposed to be an ethical competitor as implied by the word "Open" in their name. When Meta and the Chinese are the most ethical of the competitors, you know we're in a bad spot...
Doesn’t it seem likely that it all depends on who produces the next AIAYN? Things go one way if it’s an academic, and another way if it’s somebody’s trade secret.
The primary reason I have switched is that creative writing has plummeted on ChatGPT. It is overly eager to censor output that isn't adult but might vaguely be adult if taken incorrectly. This severely limits creative freedom. On the other hand, Gemini happily writes my stories.
I am not sure who OpenAI aims to please by nerfing their own product in this way. It can't be paying customers.
there was that teen who died after chat supposedly encouraged him to do bad things and his parents are suing now. so maybe more controls are being put in place to reduce risk.
This is probably not a core concern for most HN readers, but at work we do multilingual testing for synthetic text data generation and natural language processing. Emphasis on multilingual. Gemini has made some serious leaps from 1.5 to 2.5 and now 3.0, and is actually proficient in languages that other models can only dream of. On the other hand, GPT-5 has a really mixed performance in a lot of categories.
This goes way back. Even back in the 1.5 days it was the best multilingual model, when HN still treated it as entirely uncompetitive all-around. Just because, exactly as you're saying, it's not a core concern of people here. The two fields Gemini models have been number one at for years now are A. multilinguality B. image understanding. At no point since the release of Gemini 1.5 Pro way back has any Anthropic or OpenAI model done performed better at either.
Even those who have zero experience with different (human) languages could've known this if they liked, from the fact that on the LMArena leaderboards, Gemini models have consistently ranked much higher in non-English languages than in English. This gap has actually shrunk a lot over time! In the 1.5 Pro days this advantage was huge, it would be like 10th in English and 2nd in many other languages.
Nevertheless, it still depends on the specific language you're targeting. Gemini isn't the winner on every single one of them. If you're only going to choose one model for use with many languages, it should be Gemini. But if the set of languages isn't too large, optimizing model selection per language is worth it.
This "all hands on deck" thing is a classic tactic managers use when they don't actually know what to do or have the domain expertise to allocate resources intelligently and help their employees do their jobs.
Is it really a race? It feels more like a slog. I continue to try to use AI (google, openai, and anthropic), and it continues to be a pain in the ass. Their consumer interfaces are garbage, both being buggy/bloated and clunky to work over multiple threads, with its "memory" being nearly nonexistent outside a single thread. They randomly fail to do the thing they did successfully 5 minutes ago. I struggle to get them to do basic things while other things they do effortlessly. They're bad at logic, spatial reasoning/engineering, and I have to constantly correct them. Often they'll do things in agents that I never asked them to do, and I have to then undo it... The time I used to spend doing things manually, I now spend in fixing the thing that's supposed to be automating the manual work... and no matter how I try to fix it, it finds a new way to randomly fail. I am much happier just doing things by hand.
It sounds like you have found an approach that works for you, and that's great. In my experience I've had to devote a lot of time to learning to use AI tools. Most of this learning is understanding how to create the necessary context for success and getting an intuition for what questions to ask.
Google literally publish the attention paper. Have people not been paying attention? Google has been the only company I’ve been watching that really understands what they are doing.
I never understood this line of reasoning. I found it much more impressive that OpenAI's ML researchers realized this is the thing and bet big on it first, than to come up with it in the first place. It's underappreciated how much talent and insight it takes to see the obvious.
IMO Google struggles to productize things, so they sit on great ideas a while or do the wrong thing with them, but OpenAI really showed the way and Google can probably take it from here.
When I was playing poker for living there was a spreadsheet meme. There was always some guy who was losing consistently but declared everything will change from tomorrow because he now made a spreadsheet with an exact plan going forward.
The spreadsheet usually contained general things like 8 hours of sleep, healthy food, "be disciplined", "study the game for 2 hours a day" etc.
Of course it never worked because if he knew what he should be doing he would be doing it already instead of hoping for spreadsheet magic to change the course.
>>There will be a daily call for those tasked with improving the chatbot, the memo said, and Altman encouraged temporary team transfers to speed up development.
I have (rather, had) a paid subscription to ChatGPT. I work at my home in the Sierra foothills, and on alternate weeks in my office in San Jose.
Last month, I used ChatGPT while in SJ. I needed a function that's only available to paying customers, and which had worked well from my home. ChatGPT refused to recognize me as a paid-up customer. I had correct login creds + ancillary identifying info, but no go. Over the course of about half an hour, ChatGPT told me in several different ways it wouldn't (not couldn't) attempt to verify my customer status.
Weird. I’ve traveled across Europe and used ChatGPT paid account from my phone and my laptop in multiple countries on various connections. Mobile data, home WiFi, hotel WiFi, coffee shops, etc. I always get an email to confirm the login with a code but they’ve never denied my login or prevented me from using my account thankfully.
I would be surprised if bad customer experience handling were the reason OpenAI loses to Google. It's not like Google is known for their customer experience.
Of course Google is mature enough that this particular failure mode probably won’t happen, but there may be other more concerning failure modes for individuals who are reliant on a broad swath of Google services.
Diversity of tech companies is an important consideration for me, one that definitely outweighs one-time issues, especially in a field where credible competition is limited.
So you experienced a bug, which happens on software. I've traveled a lot and have never had an issue with my ChatGPT subscription. I'm not doubting you, but I don't think your anecdote adds much to the conversation of OpenAI vs Google.
I remember, maybe 2-3 years ago, chuckling at Google with their Bard naming and being late to the game and so on. It seems like I was very wrong and that they caught up quickly enough. I was also wrong in thinking MS doing well, when their recent Copilot moves across Office, Windows, and GitHub have been a joke.
Altman should know better. This sends terrible signals to employees, stakeholders and customers.
You don’t solve quality problems by scrambling teams and increasing pressure.
This reeks of terrible management. I can imagine Stanford graduates grinding it past midnight for “the mission”. If any if you is reading this: don’t do it. Altman is screwing you over. There are plenty of other places that won’t code-red your christmas season while having hundreds of billions of dollars in cash.
This will keep going around the table, next it might be a Chinese company that demos 98% of the capability at 1/4 the price. The objective of being at the cutting edge of LLM performance seems like more of a marketing advantage in the game of sucking in more capital for a moatless technology.
Which makes me think they are getting the strategy exactly backwards. My problem is usually not something that would be solved by the AI being better but instead by it being more integrated into my life.
Gemini app is pretty solid and aistudio is a good dev focused offering. GCP and Vertex AI is still a bit of a mess but I wouldn't say the overall UX is too bad at this point
Most comments here seem to discuss coding results. I know these are compared against industry benchmarks, but does anyone have experience using these with non CS related tasks? For example the other day I was brainstorming a kayak trip with both ChatGPT and Gemini 3.0. ChatGPT was off the rails. Trying to convince me the river flowed a different sirection than it does, and all sorts of weirdness. Gemini didn't provide information nearly as well as a human with experience, but it wasn't _useless_ information. The OpenAI model was a catasrophe at this. I'd be curious how the different models rate for the general audience, and if that plays into it at all.
The current situation of OpenAI is difficult. At present time, even the giants (Meta, MS, Apple, AMZN) with deep pockets would find it extremely challenging to compete against Google in the AI race, let alone a VC-funded startup.
•Google has data, a lot of private data actually (YT, Gmail, Workspace, Search Queries.. you name it) •Google has a lot of money •Google has top-talented AI engineers (Eying on DeepMind & Demis Hassabis staff) •Google has a huge userbase
With $20B in ARR and hundreds of billions in funding, would OpenAI be able to make its own remontada as Google did? I'm not sure, but it would be a long challenging journey.
To be honest, this is the first month in almost a year when I didn't pay for ChatGPT Pro and instead went for Gemini Ultra. It's still not there for programming, where I use Claude Max, but for my 'daily driver' (count this, advice on that, 'is this cancer or just a headache' kind of thing), Gemini has finally surpassed ChatGPT for me. And I used to consider it to be the worst of the bunch.
I used to consider Gemini the worst of the bunch, it constantly refused to help me in the past, but not only has it improved, ChatGPT seems to have gone down the 'nerfing' road where it now flat out refuses to do what I ask it to do quite often.
Personally I find the current Google products mediocre almost on all aspects. The killer feature of chat bots is voice chat and ChatGPT works great, and Gemini is extremely quiet without a way to increase volume. It's also difficult to figure out how to sign up for Gemini, or even the keyboard that I'm typing is making so many incorrect predictions.
I just don't trust Google. To me they're pure marketing and their engineering excellence ended a few years ago.
We are in a pretty amazing situation. If you're willing to go down 10% in benchmark scores, you easily 25% your costs. Now with Deepseek 3.2 another shot across the bow.
But if the ML, if SOTA intelligence becomes basically a price war, won't that mean that Google (and OpenAI and Microsoft and any other big model) lose big? Especially Google, as the margin even Google cloud (famously a lot lower than Google's other businesses) requires to survive has got to be sizeable.
Google trains its own AI with TPU's, which are designed in house. Google doesn't have to pay retail rates for Nvidia GPUs, like other hyperscalers in the AI rat race. Therefore, Google trains its AI for cheaper than everyone else. I think everyone else "loses big" other than Google.
> We will attempt to directly build safe and beneficial AGI, but will also consider our mission fulfilled if our work aids others to achieve this outcome.
They must be really glad to have so much competition then.
> If a value-aligned, safety-conscious project comes close to building AGI before we do, we commit to stop competing with and start assisting this project.
I wonder if OpenAI will start assisting Google now?
Last week there we had a customer request that landed in our support on a feature that I partially wrote and wrote a pile of public documentation on. Support engineer ran customer query through Claude (trained on our public and internal docs) and it very, very confidently made a bunch of stuff up in the response. It was quite plausible sounding and it would have been great if it worked that way, but it didn't. While explaining why it was wrong in a Slack thread with support engineer and another engineer who also worked on that feature, he ran Augment (that has full source code of the feature) which promptly and also very confidently made up more stuff (but different!). Some choice bleeding eye emojis were exchanged. I'm going to continue to use my own intelligence, thank you.
Relying on the model’s own “memory” to answer factual queries is almost always a mistake. Fine-tuning is almost always a more complex, more expensive and less effective method to give a model access to a knowledge base.
However using the model as a multi-hop search robot, leveraging it’s general background knowledge to guide the research flow and interpret findings, works exceedingly well.
Training with RL to optimize research tool use and reasoning is the way forward, at least until we have proper Stateful LLMs that can effectively manage an internal memory (as in Neural Turing Machines, and such).
"trained on our public and internal docs" trained how? Did you mean fine-tuned haiku? Did you actually fine tune correctly? Its not even a recommended architecture.
Or did you just misuse basic terminology about LLMs and are now saying it misbehaved, likely because your org did something very bad with?
Title should really be OpenAI declares 'code red' as OpenAI falls behind in the AI race. Google, Anthropic, Mistral, DeepSeek, Tencent, Alibaba, Moonshot, Zai, etc have all made great strides. OpenAI has been falling behind in terms of velocity while everyone else is moving faster
> Altman said the company will be delaying initiatives like ads, shopping and health agents, and a personal assistant, Pulse, to focus on improving ChatGPT
It's so telling that they're delaying these "festures" because the know full well people don't want them.
I don't understand this view. I think most people would be happy to use the best models for free in exchange for seeing ads. That's basically what google and many others successfully do for decades.
Listen, I just had to go through numerous prompt cycles to 'prove' to 5.1 that we had a new Pope. ChatGPT was dead set that I was reading 'unreliable sources'. The data is _old_.
I work with Gemini 3 daily, and I think the hype is unwarranted. It takes shortcuts, hallucinates and its UI seems way behind. And what's with the small fonts?
Is anyone actually getting good results out of GPT Pro? For coding problems, GPT Thinking seems faster and more accurate. Pro has given me some very dumb answers actually, totally misunderstanding the question. Once I asked it do design a reverse osmosis system for our home, and it suggested a 7k system that can produce 400 liters per minute. Even though I explicitly told it that a couple liters per minute suffice.
>realize antitrust heat is rising faster than stock buybacks can hide
>notice a small lab called OpenAI making exotic tech and attracting political fascination
>calculate that nothing freezes regulators like an unpredictable new frontier
>decide to treat OpenAI as an accidental firebreak
>let them sprint ahead unchecked
watch lawmakers panic about hypothetical robot uprisings instead of market concentration
>antitrust hearings shift from “break up the giants” to “what is AGI and should we fear it”
>Google emerges looking ancient, harmless, almost quaint
>pressure dissipates
>execute phase two: acceleration
roll out model updates in compressed cycles
>flood the web with AI-powered services
>redefine “the internet” as “whatever Google’s infrastructure indexes”
>regulators exhausted from chasing OpenAI’s shadow
>Google walks back onto the throne, not by hiding power, but by reframing it as inevitability
conspiracy theorists argue whether this was 5D chess or simple opportunism
>Google search trends spike for “how did this happen”
It's a fun idea but there's ample public reporting about how Google reacted to the rise of ChatGPT. There is reporting that Google was taken by surprise. You can be skeptical of that, but that's what the reporting says. ChatGPT went viral in Nov/Dec 2022, and by February or March Google was scrambling to stand up Bard as a viable competitor.
there is enough proof that they had a chatbot internally which was quite competitive but was not pushed through for all these fears, it seems they were always confident that they could catch up and scaling laws were their internal defense.
The question now though is neither might have expected Chinese labs to catch up so fast.
The first models were really bad, but the new models are very good—both text and image. They were able to clean up the embarrassing start and catch up. It's very interesting/scary that a giant corporation can develop things that new startups generated and deliver an alternative product on par with them.
What are devs using to run Gemini agents in vscode? 2.5pro on Cline/Roo was pretty buggy compared to Claude/gpt4/5 (also using Cline /roo), kept getting stuck in loops outputting repeated text and many editing issues, and much much worse than Claude code or codex. Has it gotten better? Is there a better way of using Gemini in vscode?
Most discussion focused on capabilities. But I wonder does OpenAI's "make a even big and costly model" strategy even work in long term? They are already losing money at current size. Unless we have some break though in chip efficiency.(which didn't seem to be likely for now) They are only going to loss even more.
In one of the Indian movies, there is a rather funny line that goes like this "tu jiss school se padh kar aaya hai mein uss school ka headmaster hoon". It would translate like this "The school from which you studied and came? I am the principal of that school". Looks like Google is about to show who the true principal is
"Eh-de-de-de-de. Don't quote me regulations... I co-chaired the committee that reviewed the recommendation to revise the color of the book that regulation is in. We kept it gray."
Google fragmented into multiple competing companies as well, that's where OpenAI itself came from. The problem is even after shedding employees into all these startups or established competitors trying to catch up, Google has way more people, money, and compute to throw at things and see what works than the rest of the industry. It's demoralizing and tempting for people to go back, which is also demoralizing
I don’t understand why anyone would think LLMs have a good moat. There’s no evidence to suggest that’s the case, and plenty of evidence to the contrary. Maybe hubris?
ChatGPT seems like a huge distraction for OpenAI if their goal is transformative AI
IMO: the largest value creation from AGI won’t come from building a better shopping or travel assistant. The real pot of gold is in workflow / labor automation but obviously they can’t admit that openly.
I don't read AI news or follow the industry, and from my perspective as a chatgpt user from day 1 is it's stalled for a long time now without improvements. The model feels old at this point. Claude Code highly impressed me, though.
AI creates the possibility to disrupt existing power structures - this is the only reason it gathers so much focus. If it were merely tool that increased efficiency of work, few would care so much. We already frequently get such tools which draw far less attention.
So far all it has done is entrench existing power structures by dis-empowering people who are struggling the most in current economic conditions. How exactly do you suppose that's going to change in the future if currently it's simply making the rich richer & the poor poorer?
It's just me or this article looks like propaganda? A traditional advertising nice is to plant news attacking your adversaries. This empty article looks like just part of the advertising machine of new Google model release.
> What will it do to Jony Ive’s legacy if his OpenAI device is no more successful than Snapchat’s foray into hardware?
Well, in my opinion his legacy is already pretty tarnished by his last few years at Apple, his Love From company, and his partnership with OpenAI. If he somehow knocks it out of the park with OpenAI (something I don’t think will happen nor do I want it to) then maybe he can redeem himself a little bit but, again IMHO, he is already about as low as he can go. Whatever respect I had left for him vanished after the OpenAI/IO announcement video.
A hardware device from OpenAI is exactly why I would prefer it over Anthropic or Google. Why give up on differentiation? I would assume the model team is separate from the consumer hardware team.
Certainly not the only one making things worse. Software has become an enemy of the people in the last 10 years. Remember when the internet was nominated for Nobel Peace price?
The fate of OpenAI is effectively sealed - it will go bankrupt and the scraps will get absorbed by Microsoft, for further enshitification. Not necessarily the "end" of AI, but enjoy your account while it's useful.
The problem is, there is a whole ecosystem of businesses operating as OpenAI API wrappers, and those are gonna get screeeeewed.
I take this code red as a red flag. Open AI should continue to concern itself with where it will be 5 years from now, not lose sight over concern about where it will 5 months from now.
open ai is at risk of complete collapse if it cannot fulfill its financial obligations. if people willing to give them money don't have faith in their ability to win the AI race anymore, then they're going out of business.
Back in the day before Adobe bought Macromedia, there was a constant back and forth between Illustrator and Freehand where each release would better the competitor at least until the competitor's next release.
Googling OPAI.PVT brings me to https://finance.yahoo.com/quote/OPAI.PVT , which has links to equityzen and forgeglobal. How accurate are those valuations though?
There will be a daily call for those tasked
with improving the chatbot, the memo said,
and Altman encouraged temporary team transfers
to speed up development.
Truly brilliant software development management going on here. Daily update meetings and temporary staff transfers. Well known strategies for increasing velocity!
Don't forget scuttling all the projects the staff has been working overtime to complete so that they can focus on "make it better!" waves hands frantically
I've had ideas for how to improve all the different chatbots for like 3 years, nobodys has implemented any of them (usually my ideas get implemented in software somehow the devs read my mind, but AI seems to be stuck with the same UI for LLMs), none of these AI shops are ran by people with vision it feels like. Everyone's just remaking a slightly better version of SmarterChild.
> There will be a daily call for those tasked with improving the chatbot, the memo said, and Altman encouraged temporary team transfers to speed up development.
It's incredible how 50 year-old advice from The Mythical Man-Month are still not being heed. Throw in a knee-jerk solution of "daily call" (sound familiar?) for those involved while they are wading knee-deep through work and you have a perfect storm of terrible working conditions. My money is Google, who in my opinion have not only caught up, but surpassed OpenAI with their latest iteration of their AI offerings.
> It's incredible how 50 year-old advice from The Mythical Man-Month are still not being heed.
A lot of advice is that way, which is why it is advice. If following it were easy everyone would just do it all the time, but if it's hard or there are temptations in the other direction, it has to be endlessly repeated.
Plus, there are always those special-snowflake guys who are "that's good advice for you, but for me it's different!"
Also it wouldn't surprise me if Sam Altman's talents aren't in management or successfully running a large organization, but in machiavellian manipulation and maneuvering.
All these engineers working 70 hour weeks for world class sociopaths in some sort of fucked up space race to create a technology that is supposed to make all of them unemployed.
I think most people are aligned on AI being in a bubble right now with the disagreement being over which companies (if any) will weather the storm through the burst and come out profitable on the far side.
OpenAI, imo, is absolutely going to crash and burn - it has absolutely underwhelming revenue and model performance compared to others and has made astronomical expenditure commitments. It's very possible that a government bailout partially covers those debts but the chance of the company surviving the burst when it has dug such a deep hole seems slim to none.
I am genuinely surprised that generally fiscally conservative and grounded people like Jensen are still accepting any of that crash risk.
"Code red" feels like theater. Competition is healthy - Google's compute advantage was always going to matter once they got serious. The real question isn't who's ahead this quarter, but whether anyone can maintain a moat when the underlying tech is rapidly commoditizing.
It was always clear that the insane technological monopoly of Google would always eventually allow them to surpass OpenAI once they stopped messing around and built a real product. It seems this is that moment. There is no healthy competition here because the two are not even remotely on the same footing.
"Code red" sounds about right. I don't see any way they can catch up. Their engineers at the moment (since many of the good researchers left) are not good enough to overcome the tech advantage. The piling debts of OpenAI just make it all worse.
"Who is ahead this quarter" is pretty much all that the market and finance types care about. Maybe "who will be ahead next year" as a stretch. Nobody looks beyond a few quarters. Given how heavily AI is currently driven by (and driving!) the investment space, it's not surprising that they'll find themselves yanked around by extremely short term thinking.
It feels like (to me) that Google's TPU advantage (speculation is Meta is buying a bunch) will be one of the last things to be commoditized, which gives them a larger moat. Normal chips are hard enough to come by for this stuff.
Word needs need OpenAI and Anthropic like startups to drive AI forward. Think about only Google, Meta, MS, AWS is only have these capabilities. They will never able to do that in one hand, other hand it will be monopolistics. We need more AI startups, not monopolies.
I've seen a rumor going around that OpenAI hasn't had a successful pre-training run since mid 2024. This seemed insane to me but if you give ChatGPT 5.1 a query about current events and instruct it not to use the internet it will tell you its knowledge cutoff is June 2024. Not sure if maybe that's just the smaller model or what. But I don't think it's a good sign to get that from any frontier model today, that's 18 months ago.
SemiAnalysis said it last week and AFAIK it wasn't denied.
https://newsletter.semianalysis.com/p/tpuv7-google-takes-a-s...
The SemiAnalysis article that you linked to stated:
"OpenAI’s leading researchers have not completed a successful full-scale pre-training run that was broadly deployed for a new frontier model since GPT-4o in May 2024, highlighting the significant technical hurdle that Google’s TPU fleet has managed to overcome."
Given the overall quality of the article, that is an uncharacteristically convoluted sentence. At the risk of stating the obvious, "that was broadly deployed" (or not) is contingent on many factors, most of which are not of the GPU vs. TPU technical variety.
This is a really great breakdown. With TPUs seemingly more efficient and costing less overall, how does this play for Nvidia? What's to stop them from entering the TPU race with their $5 trillion valuation?
That is.... actually a seriously meaty article from a blog I've never heard of. Thanks for the pointer.
Dylan Patel joined Dwarkesh recently to interview Satya Nadella: https://www.dwarkesh.com/p/satya-nadella-2
It's not a rumor, it's confirmed by OpenAI. All "models" since 4o are actually just optimizations in prompting and a new routing engine. The actual -model- you are using with 5.1 is 4. Nothing has been pre-trained from scratch since 4o.
Their own press releases confirm this. They call 5 their best new "ai system", not a new model
https://openai.com/index/introducing-gpt-5/
I can believe this, Deepseek V3.2 shows that you can get close to "gpt-5" performance with a gpt-4 level base model just with sufficient post-training.
I don't think that counts as confirmation. 4.5 we know was a new base-model. I find it very very unlikely the base model of 4 (or 4o) is in gpt5. Also 4o is a different base model from 4 right? it's multimodal etc. Pretty sure people have leaked sizes etc and I don't think it matches up.
New AI system doesn't preclude new models. I thought when GPT 5 launched and users hated it the speculation was GPT 5 was a cost cutting model and the routing engine was routing to smaller, specialized dumber models that cost less on inference?
It certainly was much dumber than 4o on Perplexity when I tried it.
Well then 5.x is pretty impressive
Maybe this is just armchair bs on my part, but it seems to me that the proliferation of AI-spam and just general carpet bombing of low effort SEO fodder would make a lot of info online from the last few years totally worthless.
Hardly a hot take. People have theorized about the ouroboros effect for years now. But I do wonder if that’s part of the problem
Every so often I try out a GPT model for coding again, and manage to get tricked by the very sparse conversation style into thinking it's great for a couple of days (when it says nothing and then finishes producing code with a 'I did x, y and z' with no stupid 'you're absolutely' right sucking up and it works, it feels very good).
But I always realize it's just smoke and mirrors - the actual quality of the code and the failure modes and stuff are just so much worse than claude and gemini.
I am a novice programmer -- I have programmed for 35+ years now but I build and lose the skills moving between coder to manager to sales -- multiple times. Fresh IC since last week again :) I have coded starting with Fortran, RPG and COBOL and I have also coded Java and Scala. I know modern architecture but haven't done enough grunt work to make it work or to debug (and fix) a complex problem. Needless to say sometimes my eyes glaze over the code.
And I write some code for my personal enjoyment, and I gave it to Claude 6-8 months back for improvement, it gave me a massive change log and it was quite risky so abandoned it.
I tried this again with Gemini last week, I was more prepared and asked it to improve class by class, and for whatever reasons I got better answers -- changed code, with explanations, and when I asked it to split the refactor in smaller steps, it did so. Was a joy working on this over the thanksgiving holidays. It could break the changes in small pieces, talk through them as I evolved concepts learned previously, took my feedback and prioritization, and also gave me nuanced explanation of the business objectives I was trying to achieve.
This is not to downplay claude, that is just the sequence of events narration. So while it may or may not work well for experienced programmers, it is such a helpful tool for people who know the domain or the concepts (or both) and struggle with details, since the tool can iron out a lot of details for you.
My goal now is to have another project for winter holidays and then think through 4-6 hour AI assisted refactors over the weekends. Do note that this is a project of personal interest so not spending weekends for the big man.
I'm starting with Claude at work but did have an okay experience with OpenAi so far. For clearly delimited tasks it does produce working code more often than not. I've seen some improvement on their side compared to say, last year. For something more complex and not clearly defined in advance, yes, it does produce plausible garbage and it goes off the rails a lot. I was migrating a project and asked ChatGPT to analyze the original code base and produce a migration plan. The result seemed good and encouraging because I didn't know much about that project at that time. But I ended up taking a different route and when I finished the migration (with bits of help from ChatGPT) I looked at the original migration plan out of curiosity since I had become more familiar with the project by now. And the migration plan was an absolutely useless and senseless hallucination.
On the contrary, I cannot use the top Gemini and Claude models because their outputs are so out place and hard to integrate with my code bases. The GPT 5 models integrate with my code base's existing patterns seamlessly.
NME at all - 5.1 codex has been the best by far.
I've been getting great results from Codex. Can be a bit slow, but gets there. Writes good Rust, powers through integration test generation.
So (again) we are just sharing anecdata
You're absolutely right!
Somehow it doesn't get on my nerves (unlike Gemini with "Of course").
Can you give some concrete example of programming problem task GPT fails to solve?
Interested, because I’ve been getting pretty good results with different tasks using the Codex.
I find for difficult questions math and design questions GPT5 tends to produce better answers than Claude and Gemini.
At this point you are now forced to use the "AI"s as code search tools--and it annoys me to no end.
The problem is that the "AI"s can cough up code examples based upon proprietary codebases that you, as an individual, have no access to. That creates a significant quality differential between coders who only use publicly available search (Google, Github, etc.) vs those who use "AI" systems.
Same experience here. The more commonly known the stuff it regurgitates is, the fewer errors. But if you venture into RF electronics or embedded land, beware of it turning into a master of bs.
Which makes sense for something that isn’t AI but LLM.
OpenAI is in the "don't look behind the curtain" stage with both their technology and finances.
I recall reading that Google had similar 'delay' issues when crawling the web in 2000 and early 2001, but they managed to survive. That said, OpenAI seems much less differentiated (now) than Google was back then, so this may be a much riskier situation.
Google didn't raise at a $500 billion valuation.
The 25x revenue multiple wouldn't be so bad if they weren't burning so much cash on R&D and if they actually had a moat.
Google caught up quick, the Chinese are spinning up open source models left and right, and the world really just isn't ready to adopt AI everywhere yet. We're in the premature/awkward phase.
They're just too early, and the AGI is just too far away.
Doesn't look like their "advertising" idea to increase revenue is working, either.
The differentiation should be open source, nonprofit, and ethical.
As a shady for-profit, there is none. That's the problem with this particular fraud.
Yes, the story was something like Google hadn’t rebuilt their index for something like 8 months if I recall correctly
I noticed this recently when I asked it whether I should play Indiana Jones on my PS5 or PC with a 9070 XT. It assumed I had made a typo until I clarified, then it went off to the internet and came back telling me what a sick rig I have.
OpenAI is the only SOTA model provider that doesn't have a cutoff date in the current year. That why it preforms bad at writing code for any new libraries or libraries that have had significant updates like Svelte.
State Of The Art is maybe a bit exaggerated. It's more like an early model that never really adapted, and only got watered down (smaller network, outdated information, and you cannot see thought/reasoning).
Also their models get dumber and dumber over time.
im not sure why we need to go off rumours, the knowledge cutoff for each openai model is clearly listed in the table:
https://platform.openai.com/docs/models/compare?model=gpt-5....
I asked ChatGPT 5.1 to help me solve a silly installation issue with the codex command line tool (I’m not an npm user and the recommended installation method is some kludge using npm), and ChatGPT told me, with a straight face, that codex was discontinued and that I must have meant the “openai” command.
"with a straight face"
Don’t forget SemiAnalysis’s founder Dylan Patel is supposedly roommates with Anthropics RL tech lead Sholto..
The fundamental problem with bubbles like this, is that you get people like this who are able to take advantage of the The Gell-Mann amnesia effect, except the details that they’re wrong about are so niche that there’s a vanishingly small group of people who are qualified to call them out on it, and there’s simultaneously so much more attention on what they say because investors and speculators are so desperate and anxious for new information.
I followed him on Twitter. He said some very interesting things, I thought. Then he started talking about the niche of ML/AI I work near, and he was completely wrong about it. I became enlightened.
Funny, had it tell me the same thing twice yesterday and that was _with_ thinking + search enabled on the request (it apparently refused to carry out the search, which it does once in every blue moon).
I didn't make this connection that the training data is that old, but that would indeed augur poorly.
Just a minor correction, but I think it's important because some comments here seem to be giving bad information, but on OpenAI's model site it says that the knowledge cutoff for gpt-5 is Sept 30, 2024, https://platform.openai.com/docs/models/compare, which is later than the June 01, 2024 date of GPT-4.1.
Now I don't know if this means that OpenAI was able to add that 3 months of data to earlier models by tuning or if it was a "from scratch" pre-training run, but it has to be a substantial difference in the models.
What is a pre-training run?
Pre-training is just training, it got the name because most models have a post-training stage so to differentiate people call it pre-training.
Pre-training: You train on a vast amount of data, as varied and high quality as possible, this will determine the distribution the model can operate with, so LLMs are usually trained on a curated dataset of the whole internet, the output of the pre-training is usually called the base model.
Post-training: You narrow down the task by training on the specific model needs you want. You can do this through several ways:
- Supervised Finetuning (SFT): Training on a strict high quality dataset of the task you want. For example if you wanted a summarization model, you'd finetune the model on high quality text->summary pairs and the model would be able to summarize much better than the base model.
- Reinforcement Learning (RL): You train a separate model that ranks outputs, then use it to rate the output of the model, then use that data to train the model.
- Direct Preference Optimizaton (DPO): You have pairs of good/bad generations and use them to align the model towards/away the kinds of responses you want.
Post-training is what makes the models able to be easily used, the most common is instruction tuning that teaches to model to talk in turns, but post-training can be used for anything. E.g. if you want a translation model that always translates a certain way, or a model that knows how to use tools, etc. you'd achieve all that through post-training. Post-training is where most of the secret sauce in current models is nowadays.
If you've an hour to spare this Karpathy video is good at explaining how it all works https://youtu.be/7xTGNNLPyMI
The first step in building a large language model. That's when the model is initiated and trained on a huge dataset to learn patterns and whatnot. The "P" in "GPT" stands for "pre-trained."
Łukasz Kaiser basically confirmed it in a podcast:
https://youtu.be/3K-R4yVjJfU?si=JdVyYOlxUbEcvEEo&t=2624
> Q: Are the releases aligned with pre-training efforts?
> A: There used to be a time not that long ago, maybe half a year, distant past, where the models would align with RL runs or pretraining runs ... now the naming is by capability. GPT5 is a capable model; 5.1 is a more capable model
I wonder if the failures to pretrain are the result of our understanding of neural networks being more akin to alchemy rather than chemistry
I doubt it's that important that their dataset of current events is up to date. At this stage, I believe private and synthetic data comprises a large fraction of pretraining. Web search substitutes for current event pretraining.
That would explain why it’s so bad with new Swift features and more recent ast-grep rules.
Usually current events get taught through mid-training, so even with old pre-training current events still could be added
It has no idea what it's own knowledge cutoff is.
Any data after that is contaminated with vast amount of AI slop. Is anyone training on anything newer..?
Interesting enough today I found that https://huggingface.co/openai/gpt-oss-20b when downloaded an running locally and asked:
====
when have you been built?
I’m a GPT‑4‑based model that OpenAI released on March 14 2023. The underlying training data goes up to early 2023, and the model was trained in the months leading up to that release. If you’re asking about the ChatGPT product that ships the model to users, it went live in November 2022 and has since received updates (GPT‑3.5, GPT‑4, etc.) that keep it current.
====
But when supposedly running it from https://huggingface.co/chat/models/openai/gpt-oss-20b:
====
when have you been built?
I’m a language model created by OpenAI. The current generation (GPT‑4) that powers this chat was first released in March 2023 and has been updated and fine‑tuned up through the end of 2024. My training data runs up to the beginning of June 2025, so I’m built on knowledge available up to that point.
====
And that makes me thinking that although https://huggingface.co/chat claims to be using the models available to public at https://huggingface.co , it doesn't seems to be true and I raised this question here https://huggingface.co/ggml-org/gpt-oss-20b-GGUF/discussions... , https://github.com/huggingface/inference-playground/issues/1... and https://github.com/ggml-org/llama.cpp/discussions/15396#disc... .
OpenAI is basically just Netscape at this point. An innovative product with no means of significant revenue generation.
One one side it's up against large competitors with an already established user base and product line that can simply bundle their AI offerings into those products. Google will do just what Microsoft did with Internet Explorer and bundle Gemini in for 'Free' with their already other profitable products and established ad-funded revenue streams.
At the same time, Deepseek/Qwen, etc. are open sourcing stuff to undercut them on the other side. It's a classic squeeze on their already fairly dubious business model.
> with no means of significant revenue generation.
OpenAI will top $20 billion in ARR this year, which certainly seems like significant revenue generation. [1]
[1] https://www.cnbc.com/2025/11/06/sam-altman-says-openai-will-...
It would be funny if OpenAI turns for-profit, faceplants, and then finds new life (as Mozilla did) as a non-profit sharing its tools for free.
anecdotal, but my wife wasn't interested in switching to claude from chatgpt. as far as she's concerned chatgpt knows her, and she's got her assistant perfectly tuned to her liking.
> Google will do just what Microsoft did with Internet Explorer and bundle Gemini in for 'Free' with their already other profitable products and established ad-funded revenue streams.
“will do”? Is there any Google product they haven't done that with already?
Oh God I love the analogy of OpenAI being Netscape. As someone who was an adult in the 1990s, this is so apt. Companies at that time were trying to build a moat around the World Wide Web. They obviously failed. I've thought that OpenAI too would fail but I've never thought about it like Netscape and WWW.
OpenAI should be looking at how Google built a moat around search. Anyone can write a Web crawler. Lots of people have. But no one else has turned search into the money printing machine that Google has. And they've used that to fund their search advantage.
I've long thought the moat-buster here will be China because they simply won't want the US to own this future. It's a national security issue. I see things like DeepSeek is moat-busting activity and I expect that to intensify.
Currently China can't buy the latest NVidia chips or ASML lithography equipment. Why? Because the US said so. I don't expect China to tolerate this long term and of any country, China has desmonstrated the long-term commitment to this kind of project.
Literally got an email this morning from Google, to say my Google One plan now 'includes AI benefits' - including
"More access to Gemini 3 Pro, our most capable model More access to Deep Research in the Gemini app Video generation with limited access to Veo 3.1 Fast in the Gemini app More access to image generation with Nano Banana Pro Additional AI credits for video generation in Flow and Whisk Access Gemini directly in Google apps like Gmail and Docs" [Thanks but no thanks]
I know it's been said before but it's slightly insane they're trying to compete on a hot new tech with a company with 1) a top notch reputation for AI and 2) the largest money printer that has ever existed on the planet.
Feel like the end result would always be that while Google is slow to adjust, once they're in the race they're in it it.
Maybe? But you could have written this same thing in 1999 with OpenAI and Google replaced by Google and Yahoo, respectively.
OpenAI has tons of funnels for their products. Azure’s AI smoke and mirrors offerings uses openAI behind the scenes, big with enterprise users (who has a lot of money)
Gemini can't be bundled for free unless they figure out how to make gemini flash 3.0 significantly cheaper to inference than 2.5
I don't think the Government would let them fail, so long as the specter of the Chinese becoming dominant in AI is a thing.
> Google will do just what Microsoft did with Internet Explorer and bundle Gemini in for 'Free' with their already other profitable products and established ad-funded revenue streams.
Just some numbers to show what OpenAI is against:
So on one side you've got this behemoth with, compared to OpenAI's size, unlimited funding. The $25 bn per year OpenAI is after is basically a parking ticket for Google (only slightly exaggerating). Behemoth who came with Gemini 3 Pro "thinking" and Nano Banana (that name though) who are SOTA.And on the other side you've got the open-source weights you mentioned.
When OpenAI had its big moment HN was full of comments about how it was game over for Google for search was done for. Three years later and the best (arguably the best) model gives the best answer when you search... Using Google search.
Funny how these things turns out.
Google is atm the 3rd biggest cap in the world: only Apple and NVidia are slightly ahead. If Google is serious about its AI chips (and it looks like they are) and see the fuck-ups over fuck-ups by Apple, I wouldn't be surprised at all if Alphabet was to regain the number one spot.
That's the company OpenAI is fighting: a company that's already been the biggest cap in the entire world and that's probably going to regain that spot rather sooner than later and that happens to have crushed every single AI benchmark when Gemini 3 Pro came out.
I had a ChatGPT subscription. Now I'm using Gemini 3 Pro.
> An innovative product with no means of significant revenue generation.
OpenAI has annualized revenue of $20bn. That's not Google, but it's not insignificant.
The way I've experienced "Code Red" is mostly as a euphemism for "on-going company-wide lack of focus" and a band-aid for mid-level management having absolutely no clue how to meaningfully make progress, upper management panicking, and ultimately putting engineers and ICs on the spot to bear the brunt of that organizational mess.
Interestingly enough, apart from Google, I've never seen an organization take the actual proper steps (fire mid-management and PMs) to prevent the same thing from happening again. Will be interesting to see how OAI handles this.
> fire mid-management and PMs to prevent the same thing from happening again
Firing PMs and mid-management would not prevent any of code reds you may have read about from Google or OAI lately. This is a very naive perspective of how decision making is done at the scale of those two companies. I'm sorry you had bad experiences working with people in those positions and I wish you have the opportunity to collab with great ones in the future.
>I've never seen an organization take the actual proper steps (fire mid-management and PMs) to prevent the same thing from happening again.
One time, in my entire career have I seen this done, and it is as successful as you imagine it to be. Lots of weird problems coming out from having done it, but those are being treated as "Wow we are so glad we know about this problem" rather than "I hope those idiots come back to keep pulling the wool over my eyes".
"Code Red" if implemented correctly should provide a single priority for the company. Engineers will be moved to the most important project(s).
Fully agree. I've been through a number of code red panics in my career.
But somehow, even in startups with short remaining runway, "code red" rarely means anything.
You still have to attend all the overhead meetings, run through approval circles, deal with HR etc etc.
People sure are quick to say, "I hope you get to work with better management". Man, me too, but I find that dismissive of a legitimate concern: There is A LOT of incompetent management, especially in enterprise. The sad truth is that it is often the blind leading the sighted. When I was growing up I thought that the manager was someone with experience doing the job of those they managed, but across jobs I've had, this is the case about 20% of the time.
This code red also has the convenient benefit of giving an excuse to stop work on more monetization features... Which, when implemented, would have the downside of tethering OpenAI's valuation to reality.
The one successful example I can think of is Bill Gates writing a memo to re-orient Microsoft to put the Internet at the center of everything they were doing.
Your proper steps are also missing out on firing the higher level executives. But then new ones would be hired, a re-org will occur, and another Code Red will occur in a few months
"Software engineer complains bearing the burden of everything and concludes everything would be fixed by firing everybody except themselves."
The real code red here is less that Google just one-upped OpenAI but that they demonstrated there’s no moat to be had here.
Absent a major breakthrough all the major providers are just going to keep leapfrogging each other in the most expensive race to the bottom of all time.
Good for tech, but a horrible business and financial picture for these companies.
> for these companies
They’re absolutely going to get bailed out and socialize the losses somehow. They might just get a huge government contract instead of an explicit bailout, but they’ll weasel out of this one way or another and these huge circular deals are to ensure that.
Absolutely. I don't understand why investors are excited about getting into a negative-margin commodity. It makes zero sense.
I was an OpenAI fan from GPT 3 to 4, but then Claude pulled ahead. Now Gemini is great as well, especially at analyzing long documents or entire codebases. I use a combination of all three (OpenAI, Anthropic & Google) with absolutely zero loyalty.
I think the AGI true believers see it as a winner-takes-all market as soon as someone hits the magical AGI threshold, but I'm not convinced. It sounds like the nuclear lobby's claims that they would make electricity "too cheap to meter."
Maybe there's no tangible moat still, but did Gemini 3's exceptional performance actually funnel users away from ChatGPT? The typical Hacker News reader might be aware of its good performance on benchmarks, but did this convert a significant number of ChatGPT users to Gemini? It's not obvious to me either way.
Especially if we're approaching a plateau, in a couple years there could be a dozen equally capable systems. It'll be interesting to see what the differentiators turn out to be.
So why did Google stock increase massively since about when Gemini 2.5 Pro was released, their first competitive model?
It drives me a bit crazy when people say OpenAI has no moat.
Yes, companies like Google can catch up and overtake them, but a moat is merely making it hard and expensive.
99.999.. perc of companies can't dream of competing with OpenAI.
Yep, I thought they might have some secret sauce in terms of training techniques, but that doesn't seem to be the case.
> Good for tech, but a horrible business and financial picture for these companies.
That’s not a bubble at all is it?
Did Google actually train a new model? The cutoff dates for Gemini 3 and 2.5 are the same.
(My apologies if this was already asked - this thread is huge and Find-In-Page-ing for variations of "pre-train", "pretrain", and "train" turned up nothing about this. If this was already asked I'd super-appreciate a pointer to the discussion :) )
Genuine question: How is it possible for OpenAI to NOT successfully pre-train a model?
I understand it's very difficult, but they've already successfully done this and they have a ton of incredibly skilled and knowledgeable, well-paid and highly knowledgeable employees.
I get that there's some randomness involved but it seems like they should be able to (at a minimum) just re-run the pre-training from 2024, yes?
Maybe the process is more ad-hoc (and less reproducible?) than I'm assuming? Is the newer data causing problems for the process that worked in 2024?
Any thoughts or ideas are appreciated, and apologies again if this was asked already!
> Genuine question: How is it possible for OpenAI to NOT successfully pre-train a model?
The same way everyone else fails at it.
Change some hyper parameters to match the new hardware (more params), maybe implement the latest improvements in papers after it was validated in a smaller model run. Start training the big boy, loss looks good, 2 months and millions of dollars later loss plateaus, do the whole SFT/RL shebang, run benchmarks.
It's not much better than the previous model, very tiny improvements, oops.
I’m not sure what ‘successfully’ means in this context. If it means training a model that is noticeably better than previous models, it’s not hard to see how that is challenging.
You don't train the next model by starting with the previous one.
A company's ML researchers are constantly improving model architecture. When it's time to train the next model, the "best" architecture is totally different from the last one. So you have to train from scratch (mostly... you can keep some small stuff like the embeddings).
The implication here is that they screwed up bigly on the model architecture, and the end result was significantly worse than the mid-2024 model, so they didn't deploy it.
GPT4.5 was allegedly such a pre-train. It just didn’t perform good enough to announce and product it as such.
> the company will be delaying initiatives like ads, shopping and health agents, and a personal assistant, Pulse, to focus on improving ChatGPT
There's maybe like a few hundred people in the industry who can truly do original work on fundamentally improving a bleeding-edge LLM like ChatGPT, and a whole bunch of people who can do work on ads and shopping. One doesn't seem to get in the way of the other.
The bottleneck isn’t the people doing the work but the leadership’s bandwidth for strategic thinking
Far be it from me to backseat drive for Sam Altman, but is the problem really that the core product needs improvement, or that it needs a better ecosystem? I can't imagine people are choosing they're chatbots based on providing the perfect answers, it's what you can do with it. I would assume google has the advantage because it's built into a tool people already use every day, not because it's nominally "better" at generating text. Didn't people prefer chatgpt 4 to 5 anyways?
There are two layers here: 1) low level LLM architecture 2) applying low level LLM architecture in novel ways. It is true that there are maybe a couple hundred people who can make significant advances on layer 1, but layer 2 constantly drives progress on whatever level of capability layer 1 is at, and it depends mostly on broad and diverse subject matter expertise, and doesn't require any low level ability to implement or improve on LLM architectures, only understanding how to apply them more effectively in new fields. The real key thing is finding ways to create automated validation systems, similar to what is possible for coding, that can be used to create synthetic datasets for reinforcement learning. Layer 2 capabilities do feed back into improved core models, even if you have the same core architecture, because you are generating more and improved data for retraining.
Delaying doesn't necessarily mean they stop working on it. Also it might be a question of compute resource allocation as well.
ha what an incredible consumer-friendly outcome! Hopefully competition keeps the focus on improving models and prevents irritating kinds of monetization
I for one would say, the later they add the "ads" feature, the better...
>There's maybe like a few hundred people in the industry
My guess is that it's smaller than that. Only a few people in the world are capable of pushing into the unknown and breaking new ground and discoveries
OpenAI has already lined up enormous long-term commitments — over $500 billion through initiatives like Stargate for U.S. data centers, $250 billion in spending on Microsoft Azure cloud services, and tens of billions on AMD’s plan to deliver 6 GW of Instinct GPUs. Meanwhile, Oracle has financed its role in Stargate with at least $18 billion in corporate bonds plus another $9.6 billion in bank loans, and analysts expect its total capital need for these AI data centers could climb toward $100 billion.
The risk is straightforward: if OpenAI falls behind or can’t generate enough revenue to support these commitments, it would struggle to honor its long-term agreements. That failure would cascade. Oracle, for example, could be left with massive liabilities and no matching revenue stream, putting pressure on its ability to service the debt it already issued.
Given the scale and systemic importance of these projects — touching energy grids, semiconductor supply chains, and national competitiveness — it’s not hard to imagine a future where government intervention becomes necessary. Even though Altman insists he won’t seek a bailout, the incentives may shift if the alternative is a multi-company failure with national-security implications.
"Even though Altman insists he won’t seek a bailout"
No matter what Sam Altman's future plans are, the success of those future plans is entirely dependent on him communicating now that there is a 0% chance those future plans will include a bailout.
Last week's announced Genesis Mission from the Department of Energy could be the vehicle for this bailout.
1. Government will "partner" (read: foot the bill) for these super-strategic datacenters and investments promised by OpenAI.
2. The investments are not actually sound and fail, but it's the taxpayer that suffers.
3. Mr. Altman rides off into the sunset.
OpenAI doesn't have $500 billion in commitments lined up, it's promising to spend that much over 5 years... That's a helluva big difference than having $500B in revenue incoming.
I'm hoping for Congressional gridlock to save us from bailing out a cascading failure. The harder it hits, the better.
> the incentives may shift if the alternative is a multi-company failure with national-security implications.
Sounds like a golden opportunity for GOOG to step over the corpse of OpenAI and take over for cents on the dollar all of the promises the now defunct ex-leader of AI made.
most of them are non binding letters of intent, i don't think it's as trite as you put it
What about OpenAI would rate a bailout? There's too much competition. If they ever do end up in a deep hole and plead for a rescue, I would imagine that gov will just force a sale of assets. Surely Google, MS and Amazon can make use of their infrastructure in exchange for taking on some portion of their debts.
"it would struggle to honor its long-term agreements. That failure would cascade. Oracle, for example, could be left with massive liabilities and no matching revenue stream,"
No, there's a not of noise about this but these are just 'statements of intent'.
Oracle very intimately understands OpenAI's ability to pay.
They're not banking $50B in chips and then waking up naively one morning to find out OpenAI has no funding.
What will 'cascade' is maybe some sentiment, or analysts expectations etc.
Some of it, yes, will be a problem - but at this point, the data centre buildout is not an OpenAI driven bet - it's a horizontal be across tech.
There's not that much risk in OpenAI not raising enough to expand as much as it wants.
Frankly - a CAPEX slowdown will hit US GDP growth and freak people out more than anything.
Isn't the NVIDIA-TSMC duopoly the problem here?
The cost of these data centers and ongoing inference is mostly the outrageous cost of GPUs, no?
I don't understand why the entire industry isn't looking to diversify the GPU constraint so that the hardware makers drop prices.
Why no industry initiative to break NVIDIA's strangehold and next TSMC's?
Or are GPUs a small line item in the outrageous spend companies like OpenAI are committing to?
At first I read “enormous longterm commitments” as customers committing to OpenAI. But you are saying it’s the reverse.
This is all based on the LLM architecture that likely can't reach AGI.
If they aren't developing in parallel an alternative architecture than can reach AGI, when a/some companies develop such a new model, OpenAI are toast and all those juicy contracts are kaput.
Heard all the news how Gemini 3 is passing everyone on benchmarks, so quickly tested and still find it a far cry from ChatGPT in real world use when testing questions on both platforms. But importantly the ChatGPT app experience at least for iPhone/Mac users is drastically superior vs Google which feels very Google still. So Gemini would have to be drastically better answer wise than ChatGPT to lure users from a better UI/UX experience to Gemini. But glad to see competition since certainly don't want only one winner in this race.
That's really fascinating. Every real world use case I've tried on Gemini (especially math-related) absolutely slaughtered the performance of ChatGPT in speed and quality, not even close. As an Android user, the Gemini app is also far superior, since the ChatGPT app still doesn't properly display math equations, among plenty of other bugs.
> But importantly the ChatGPT app experience at least for iPhone/Mac users is drastically superior vs Google which feels very Google still. So Gemini would have to be drastically better answer wise than ChatGPT to lure users from a better UI/UX experience to Gemini.
Yes, the ChatGPT experience is much better. No, Gemini doesn't need to make a better product to take market share.
I've never had the ChatGPT app. But my Android phone has the Gemini app. For free, I can do a lot with it. Granted, on my PC I do a lot more with all the models via paid API access - but on the phone the Gemini app is fine enough. I have nothing to gain by installing the ChatGPT app, even if it is objectively superior. Who wants to create another account?
And that'll be the case for most Android users. As a general hint: If someone uses ChatGPT but has no idea about gpt-4o vs gpt-5 vs gpt-5.1 etc, they'll do just fine with the Gemini app.
Now the Gemini app actually sucks in so many ways (it doesn't seem to save my chats). Google will fix all these issues, but can overtake ChatGPT even if they remain an inferior product.
It's Slack vs Teams all over again. Teams one by a large margin. And Teams still sucks!
Well I have been using Gemini and ChatGPT side by side for over 6 months now.
My experience is Gemini has significantly improved its UX and performs better that requires niche knowledge, think of some ancient gadgets that have been out of production for 4-5 decades. Gemini can produce reliable manuals, but ChatGPT hallucinates.
UX wise ChatGPT is still superior and for common queries it is still my go to. But for hard queries, I am team Gemini and it hasn’t failed me once
Benchmaxxing galore by lots of teams in this space.
I've been a paying high volume user of ChatGPT for a while. I found the transition to Gemini to be seamless. I've been pleasantly surprised. I bounce between the two. I'm at about 60% Gemini, 40% ChatGPT.
I had a similar experience, signing up for the first time to give Gemini a test drive on my side project after a long time using ChatGPT. The latter has a native macOS client which "just works" integrating with Xcode buffers. I couldn't figure out how to integrate Gemini with Xcode quickly enough so I'm resorting to pasting back & forth from the browser. A few of the exchanges I've had "felt smarter" — but, on the whole, it feels like maybe it wasn't as well trained on Swift/SwiftUI as the OpenAI model. I haven't decided one way or another yet, but those are my initial impressions.
> But importantly the ChatGPT app experience at least for iPhone/Mac users is drastically superior vs Google which feels very Google still. So Gemini would have to be drastically better answer wise than ChatGPT to lure users from a better UI/UX experience to Gemini.
Opposite is true for a larger market. Gemini is great and available with one button click on most consumer phones. OpenAI will never crack most Android users by this logic of yours
Gemini comes with the 1.99 Google One plan. So I use that
> So Gemini would have to be drastically better answer wise than ChatGPT to lure users from a better UI/UX experience to Gemini.
or cheaper/free
Its really hard to measure these things. Personally I switched to Gemini a few months ago since it was half the cost of ChatGPT (Verizon has a $10/month Google AI package). I feel like I've subconsciously learned to prompt it slightly differently and now using OpenAI products feels disappointing. Gemini tends to give me the answer I expect, Claude follows close behind, I get "meh" results from OpenAI.
I am using Gemini 3 Pro, I rarely use Flash.
What are your primary usecases? Are you mostly using it as a chatbot?
I find gemini excels in multimodal areas over chatgpt and anthropic. For example, "identify and classify this image with meta data" or "ocr this document and output a similar structure in markdown"
Curiously, I had the opposite experience, except for Deep Research mode where after the latest update the OpenAI offering has become genuinely amazing. This is doubly ironic because Gemini has direct API access to Google search!
they're deep into a redesign of the gemini app, idk when it will be released or if its going to be good, but at least they agree with you and are putting significant resources into fixing it.
I couldn't even get ChatGPT to let me download code it claimed to program for me. It kept saying the files were ready but refused to let me access or download anything. It was the most basic use case and it totally bombed. I gave up on ChatGPT right then and there.
It's amazing how different people have wildly varying experiences with the same product.
Training and gaming for the benchmarks is different than actual use.
This is exactly my experience. And it's funny -- this crowd is so skeptical of OpenAI... so they prefer _Google_ to not be evil? It's funny how heroes and villains are being re-cast.
Yeah, hate to say but for me a big thing is i still couldn't separate my Gemini chats into folders. I had ChatGPT export some profiles and history and moved it into Gemini, and 1) when Gemini gave me answers i was more pleased but 2) Gemini was a bit more rigorous on guard rails, which seems a bit overly cautious. I was asking some pretty basic non-controversial stuff.
I'm confused as well, it hallucinated like crazy
like it seems great, but then it's just bullshitting about what it can do or whatever
For regular consumers, Gemini's AI pro plan is a tough one to beat. The chat quality has gotten much better, I am able to share my plan with a couple more people in my family leading to proper individual chat histories, I get 2 TB of extra storage (which is also sharable), plus some really nice stuff like NotebookLM, which has been amazing for doing research. Veo/Nanobanana are nice bonuses.
It's easily worth the monthly cost, and I'm happy to pay - something which I didn't even consider doing a year ago. OpenAI just doesn't have the same bundle effect.
Obviously power users and companies will likely consider Anthropic. I don't know what OpenAI's actual product moat is any more outside of a well-known name.
Gemini also will answer most queries where ChatGpt won't do a lot of things. Example: "Create an image of Snow white". This will give the stand "Violates our content policy" even though the story was written hundreds of years ago. You can even point out the story is in the public domain and it still won't do it.
I remember when it wouldn't even give me the lyrics to the star spangled banner. https://news.ycombinator.com/item?id=44832990#44833365
I strongly advise never using Google's Drive storage. They're known to scan all content, and to disable all access if even a single file is "problematic", often misclassified by a bot. If you do use the storage, do backup all your files, and be ready to lose access at any time, with no way to reach any intelligent human.
Through my work I have access to Google's, Anthropic's, and OpenAI's products, and I agree with you, I barely touch OpenAI's models/products for some reason even though I have total freedom to choose.
Do you happen to know if the AI features of the Google One 5TB plan is equivalent to the 2TB AI pro plan? It is so difficult to understand what actually comes with their plans, and I want to have the 5 TB storage for backups.
If we stop for a while and really consider the value of AI tools, then comparing them on price doesn't make much sense. Any of these tools give hundreds, thousands, or tens of thousands of dollars of value per month to the user. With that in consideration they should mostly be compared on quality.
WSJ: Altman said OpenAI would be pushing back work on other initiatives, such as advertising, AI agents for health and shopping, and a personal assistant called Pulse.
These plus working with Jony Ive on hardware, makes it sound like they took their eyes off the ball.
if you want to compete with google it seems like ad space is the single most important thing to push out quickly.
no matter what openai does if its not accepting customers the ad budgets will flow to meta amaz and goog and be used as weapons against it.
it in't about taking eyes off the ball, it is about playing very different ball - they de-facto became commercial entity with short term plans/goals/targets/metrics and all the management games creeping in. Beating Google, such a large company who has been successfully playing that game for quarter of century is very hard, if not impossible until Google would make serious error itself.
And pure tech-wise - they seem to have went all-in on corp management understandable way of doing things - hardware(money) scaling which, while unavoidable in this game, must be accompanied by theoretic-algorithmic improvements as pure hardware scale game is again where Google is hardly beatable.
Didn't they announce all kinds of other things? A social network like X, and a browser, at least.
100%. Especially if it’s just ads and a new Siri/Alexa that they’ve got cooking.
I don't think this is about Google. This is about advertising being the make or break moment for OpenAI.
The problem with ChatGPT advertising is that it's truly a "bet the farm" situation, unlike any of their projects in the past:
- If it works and prints money like it should, then OpenAI is on a path to become the next Mag 7 company. All the money they raised makes sense.
- If it fails to earn the expected revenue numbers, the ceiling has been penciled in. Sam Altman can't sell the jet pack / meal pill future anymore. Reality becomes cold and stark, as their most significant product has actual revenue numbers attached to it. This is what matters to the accountants, which is the lens through which OpenAI will be evaluated with from this point forward. If it isn't delivering revenue, then they raised way too much money - to an obscene degree. They won't be able to sell the wild far future vision anymore, and will be deleteriously held back by how much they've over-sold themselves.
The other problems that have been creeping up:
- This is the big bet. There is no AGI anymore.
- There is no moat on anything. Google is nipping at their heels. The Chinese are spinning up open source models left and right.
- Nothing at OpenAI is making enough money relative to the costs.
- Selling "AI" to corporate and expecting them to make use of it hasn't been working. Those contracts won't last forever. When they expire, businesses won't renew them.
My guess is that they've now conducted small scale limited tests of advertising and aren't seeing the engagement numbers they need. It's truly a nightmare scenario outcome for them, if so.
They're declaring "code red" loudly and publicly to distract the public from this and to bide more time. Maybe even to raise some additional capital (yikes).
They're saying other things are more important than "working on advertising" right now. And they made sure to mention "advertising" lots so we know "advertising" is on hold. Which is supposedly the new golden goose.
Why drop work on a money printer? What could be more important? Unless the money printer turned out to be a dud.
Didn't we kind of already know advertising would fail on a product like this? Didn't Amazon try to sell via Alexa and have that totally flop? I'm not sure why ChatGPT would be any different from that experience. It's not a "URL bar" type experience like Google has. They don't own every ingress to the web like Google, and they don't own a infinite scroll FOMO feed of fashion like Meta. The ad oppo here is like Quora or Stack Overflow - probably not great.
I have never once asked ChatGPT for shopping ideas. But Google stands in my search for products all the time. Not so much as a "product recommendation engine", but usually just a bridge troll collecting its toll.
> advertising, AI agents for health and shopping,
Um.
- Advertising. "We'll get back to working on your problem in a moment, but first, a word from our sponsor, NordVPN." It's not a good fit.
- Health. Sounds like unlicensed medical practice. That will require a big bribe to Trump.
- Shopping. Can pretty much do that now, in that ChatGPT can call Google. Will Google let OpenAI call Google Search?
IMHO Gemini surpassed ChatGPT by quite a bit - I switched. Gemini is faster, the thinking mode gives me reliably better answers and it has a more "business like" conversation attitude which is refreshing in comparison to the over-the-top informal ChatGPT default.
> [Gemini] has a more "business like" conversation attitude which is refreshing in comparison to the over-the-top informal ChatGPT default.
Maybe "business like" for Americans. In most of the world we don't spend quite so much effort glazing one another in the workplace. "That's an incredibly insightful question and really gets to the heart of the matter". No it isn't. I was shocked they didn't fix this behavior in v3.
I've found Gemini 3.0 Pro to be bad at multi turn conversation and instruction following. It ignores your follow up question unless you draw attention to it with caps or something.
Not a major complaint for technical work where you don't even want to do much multi turn conversation. Just an observation.
Is there a replacement for ChatGPT projects in Gemini yet?
That's the only ChatGPT feature keeping me from moving to Gemini. Specifically, the ability to upload files and automatically make them available as context for a prompt.
Ironically, the thing that annoys me most about Gemini is the Discord-esque loading messages in the CLI. Twee is one thing: mixing twee with serious hints is worse.
I think we are finally seeing the effects of the steady stream of departures of top researchers and leaders from OpenAI since last year. Sure you can declare a "code red", but who is going to lead the effort? Set the direction? Do the heavy lifting? Chart the path forward? Sam Altman is a salesman, not a researcher. Ilya is no longer around. Most of the other top brass has been poached by Google/Meta/Anthropic or left to start their own thing. The people left behind are probably good at iterating, but can they really make the next leap forward on their own?
I see google partnering with different companies to mine their data for AI, but I don't see that with OpenAI. They had a good thing going with Microsoft but it looks like that relationship is a bit sour now?
Surely they know that they can't just keep scraping the internet to train models.
If I don't use a Microsoft product, I'd have to go out of my way to use an OpenAI service. But they don't have a specialized "service" (like anthropic and developers) either. Gemini is there by default with Google/Reddit. To retain their first-to-market advantage, they'd need to be the default in more places, or invest in models and services that cater to very specific audiences.
I think their best best is to partner with different entities. But they lost reddit and twitter, and FB is doing their own thing too, so who's left? linkedin? school systems (but ChromeBook has them beat there), perhaps telecoms preloading chatgpt apps into phones?
In my layperson's opinion, I think they have an access problem. Windows 11/Copilot (Github and in windows) seems to be the main access stream and people hate both, and they don't have branding there either, just back-end. There is no device you can buy, service you can get that has an OpenAI branded thing on it as a value added feature.
I'm sure they'll do ok, but i keep hearing they need to do a lot more than just 'ok'.
No, I don't think they'll be okay. A long slow death perhaps, but I would be surprised if they can dig themselves out of this hole.
You can't beat Google on high-quality data for pretraining; at scale, that's what really matters most, both in theory and practice. Other companies like Anthropic and DeepSeek are keeping up by taking advantage of smarter RL approaches, but I just don't see anyone at OpenAI with the research credentials to do that kind of work as they all left in the last mass exodus. They have been too complacent and let much of their high-quality talent go to their competition.
It's all about the chip economics. I don't know how the _manufacturing cost_ of Google's TPUs compares to Nvidia's GPUs, for inference of equivalent token throughput.
But at the moment Nvidia's 75-80% gross margin is slowly killing its customers like OpenAI. Eventually Nvidia will drop its margins, because non-0 profit from OpenAI is better than the 0 it'll be if OpenAI doesn't survive. Will be interesting to see if, say, 1/3 the chip cost would make OpenAI gross margin profitable... numbers bandied in this thread of $20B revenue with $115B cost imply they need 1/6 the chip cost, but I doubt those numbers are right (hard to get accurate $ numbers for a private company for the benefit of us arm-chair commenters).
Yes, from the first principles perspective this AI thingy is just about running electricity through some wires printed on silicon by a Taiwanese company using a Dutch machine. Which means, up until the Taiwanese you have plenty of room to cut margins up until that point the costs are mostly greed based. That is Nvidia is asking for the highest price the customer can pay and they have quite a way to the cost that define their min price. Which means AI companies can actually keep getting better deals until the devices delivered to them are priced close to TSMCs bulk wafer printing prices.
Crazy how we went from google feeling like they were a dinasour who could never catch up to openai, to almost feeling like the opposite in terms of being able to catch up. All within just 1-2 years.
Thats like innovators dillema in action. Google had one of the strongest ML teams years before majoriry of AI companies was founded, but no desire to make a product that will compete with their search.
And now they actually have competitors.
Google (generalist/media) > Anthropic (code) > x.AI (excellent price/quality balance).
ChatGPT is a bit late now (even behind DeepSeek with DeepThink I believe)
OpenAI was founded to hedge against Google dominating AI and with it the future. It makes me sad how that was lost for pipe dreams (AGI) and terrible leadership.
I fear a Google dystopia. I hope DeepSeek or somebody else will counter-balance their power.
That goal has wildly succeeded -- there are now several well financed companies competing against Google.
The goal was supposed to be an ethical competitor as implied by the word "Open" in their name. When Meta and the Chinese are the most ethical of the competitors, you know we're in a bad spot...
AGI was the thing from the start. From the OpenAI Charter:
>OpenAI’s mission is to ensure that artificial general intelligence (AGI) ... benefits all of humanity.
I agree with you on the leadership.
Doesn’t it seem likely that it all depends on who produces the next AIAYN? Things go one way if it’s an academic, and another way if it’s somebody’s trade secret.
The primary reason I have switched is that creative writing has plummeted on ChatGPT. It is overly eager to censor output that isn't adult but might vaguely be adult if taken incorrectly. This severely limits creative freedom. On the other hand, Gemini happily writes my stories.
I am not sure who OpenAI aims to please by nerfing their own product in this way. It can't be paying customers.
there was that teen who died after chat supposedly encouraged him to do bad things and his parents are suing now. so maybe more controls are being put in place to reduce risk.
This is probably not a core concern for most HN readers, but at work we do multilingual testing for synthetic text data generation and natural language processing. Emphasis on multilingual. Gemini has made some serious leaps from 1.5 to 2.5 and now 3.0, and is actually proficient in languages that other models can only dream of. On the other hand, GPT-5 has a really mixed performance in a lot of categories.
This goes way back. Even back in the 1.5 days it was the best multilingual model, when HN still treated it as entirely uncompetitive all-around. Just because, exactly as you're saying, it's not a core concern of people here. The two fields Gemini models have been number one at for years now are A. multilinguality B. image understanding. At no point since the release of Gemini 1.5 Pro way back has any Anthropic or OpenAI model done performed better at either.
Even those who have zero experience with different (human) languages could've known this if they liked, from the fact that on the LMArena leaderboards, Gemini models have consistently ranked much higher in non-English languages than in English. This gap has actually shrunk a lot over time! In the 1.5 Pro days this advantage was huge, it would be like 10th in English and 2nd in many other languages.
Nevertheless, it still depends on the specific language you're targeting. Gemini isn't the winner on every single one of them. If you're only going to choose one model for use with many languages, it should be Gemini. But if the set of languages isn't too large, optimizing model selection per language is worth it.
Very good to know. I use Gemini for many translation related work, the 1m windows is very helpful too.
This "all hands on deck" thing is a classic tactic managers use when they don't actually know what to do or have the domain expertise to allocate resources intelligently and help their employees do their jobs.
Is it really a race? It feels more like a slog. I continue to try to use AI (google, openai, and anthropic), and it continues to be a pain in the ass. Their consumer interfaces are garbage, both being buggy/bloated and clunky to work over multiple threads, with its "memory" being nearly nonexistent outside a single thread. They randomly fail to do the thing they did successfully 5 minutes ago. I struggle to get them to do basic things while other things they do effortlessly. They're bad at logic, spatial reasoning/engineering, and I have to constantly correct them. Often they'll do things in agents that I never asked them to do, and I have to then undo it... The time I used to spend doing things manually, I now spend in fixing the thing that's supposed to be automating the manual work... and no matter how I try to fix it, it finds a new way to randomly fail. I am much happier just doing things by hand.
It sounds like you have found an approach that works for you, and that's great. In my experience I've had to devote a lot of time to learning to use AI tools. Most of this learning is understanding how to create the necessary context for success and getting an intuition for what questions to ask.
Google literally publish the attention paper. Have people not been paying attention? Google has been the only company I’ve been watching that really understands what they are doing.
I never understood this line of reasoning. I found it much more impressive that OpenAI's ML researchers realized this is the thing and bet big on it first, than to come up with it in the first place. It's underappreciated how much talent and insight it takes to see the obvious.
The company didn't publish the paper, employees did. And all of them have since moved on to other companies, including OpenAI.
IMO Google struggles to productize things, so they sit on great ideas a while or do the wrong thing with them, but OpenAI really showed the way and Google can probably take it from here.
Google has great technology, their ability to make and focus on great product development without getting distracted is the issue
If Google wasn’t threatened by OpenAI et al., it wouldn’t be making Gemini today though.
When I was playing poker for living there was a spreadsheet meme. There was always some guy who was losing consistently but declared everything will change from tomorrow because he now made a spreadsheet with an exact plan going forward. The spreadsheet usually contained general things like 8 hours of sleep, healthy food, "be disciplined", "study the game for 2 hours a day" etc.
Of course it never worked because if he knew what he should be doing he would be doing it already instead of hoping for spreadsheet magic to change the course.
>>There will be a daily call for those tasked with improving the chatbot, the memo said, and Altman encouraged temporary team transfers to speed up development.
Sam Altman clearly didn't get the memo.
Since the release of Google Gemini 3 two weeks ago, the seven-day moving average of ChatGPT's daily unique active users has declined by 6%.
https://www.moomoo.com/news/post/62341840/why-has-openai-ini...
Kids off school for thanksgiving?
I have (rather, had) a paid subscription to ChatGPT. I work at my home in the Sierra foothills, and on alternate weeks in my office in San Jose.
Last month, I used ChatGPT while in SJ. I needed a function that's only available to paying customers, and which had worked well from my home. ChatGPT refused to recognize me as a paid-up customer. I had correct login creds + ancillary identifying info, but no go. Over the course of about half an hour, ChatGPT told me in several different ways it wouldn't (not couldn't) attempt to verify my customer status.
I'm now a former ChatGPT customer.
Weird. I’ve traveled across Europe and used ChatGPT paid account from my phone and my laptop in multiple countries on various connections. Mobile data, home WiFi, hotel WiFi, coffee shops, etc. I always get an email to confirm the login with a code but they’ve never denied my login or prevented me from using my account thankfully.
I would be surprised if bad customer experience handling were the reason OpenAI loses to Google. It's not like Google is known for their customer experience.
Of course Google is mature enough that this particular failure mode probably won’t happen, but there may be other more concerning failure modes for individuals who are reliant on a broad swath of Google services.
Diversity of tech companies is an important consideration for me, one that definitely outweighs one-time issues, especially in a field where credible competition is limited.
How do you handle family obligations and a super commute like that?
I mean, cool story bro.
So you experienced a bug, which happens on software. I've traveled a lot and have never had an issue with my ChatGPT subscription. I'm not doubting you, but I don't think your anecdote adds much to the conversation of OpenAI vs Google.
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I remember, maybe 2-3 years ago, chuckling at Google with their Bard naming and being late to the game and so on. It seems like I was very wrong and that they caught up quickly enough. I was also wrong in thinking MS doing well, when their recent Copilot moves across Office, Windows, and GitHub have been a joke.
Code red?
Altman should know better. This sends terrible signals to employees, stakeholders and customers.
You don’t solve quality problems by scrambling teams and increasing pressure.
This reeks of terrible management. I can imagine Stanford graduates grinding it past midnight for “the mission”. If any if you is reading this: don’t do it. Altman is screwing you over. There are plenty of other places that won’t code-red your christmas season while having hundreds of billions of dollars in cash.
why couldn't GPT5.1 improve itself? Last I heard, it can produce original math and has phd level intelligence.
I believe it was Sam Altman that said software engineers wouldn't have jobs by the end of the year. They still have a few weeks to make good on that.
That was their gamble. Seems it didn't play out.
C'mon man. You know why...
OpenAI is toast. Google has a model advantage, hardware advantage (TPUs), and business advantage (I hear they are good at selling ads).
It is all physics from here.
They are also good at selling cloud hosting and services like LLMs (despite their horrible billing practices where there is no limit)
Source: https://www.wsj.com/tech/ai/openais-altman-declares-code-red... (https://news.ycombinator.com/item?id=46118396)
This will keep going around the table, next it might be a Chinese company that demos 98% of the capability at 1/4 the price. The objective of being at the cutting edge of LLM performance seems like more of a marketing advantage in the game of sucking in more capital for a moatless technology.
Which makes me think they are getting the strategy exactly backwards. My problem is usually not something that would be solved by the AI being better but instead by it being more integrated into my life.
"We’re currently experiencing issues" https://status.openai.com/
That looks pretty... amateurish. I can't imagine selling customer a service that doesn't even hit the third nine
They don't have much to worry about as long as Google keeps focusing on the models and neglecting the experience of actually using them.
Gemini app is pretty solid and aistudio is a good dev focused offering. GCP and Vertex AI is still a bit of a mess but I wouldn't say the overall UX is too bad at this point
Most comments here seem to discuss coding results. I know these are compared against industry benchmarks, but does anyone have experience using these with non CS related tasks? For example the other day I was brainstorming a kayak trip with both ChatGPT and Gemini 3.0. ChatGPT was off the rails. Trying to convince me the river flowed a different sirection than it does, and all sorts of weirdness. Gemini didn't provide information nearly as well as a human with experience, but it wasn't _useless_ information. The OpenAI model was a catasrophe at this. I'd be curious how the different models rate for the general audience, and if that plays into it at all.
The current situation of OpenAI is difficult. At present time, even the giants (Meta, MS, Apple, AMZN) with deep pockets would find it extremely challenging to compete against Google in the AI race, let alone a VC-funded startup.
•Google has data, a lot of private data actually (YT, Gmail, Workspace, Search Queries.. you name it) •Google has a lot of money •Google has top-talented AI engineers (Eying on DeepMind & Demis Hassabis staff) •Google has a huge userbase
With $20B in ARR and hundreds of billions in funding, would OpenAI be able to make its own remontada as Google did? I'm not sure, but it would be a long challenging journey.
TIL the phrase remontada -- thank you :)
Slang term for comeback
They also control their own hardware stack with TPUs.
But hey they dumped $6.4 billion on Jony Ive. Surely he'll solve all their problems.
To be honest, this is the first month in almost a year when I didn't pay for ChatGPT Pro and instead went for Gemini Ultra. It's still not there for programming, where I use Claude Max, but for my 'daily driver' (count this, advice on that, 'is this cancer or just a headache' kind of thing), Gemini has finally surpassed ChatGPT for me. And I used to consider it to be the worst of the bunch.
I used to consider Gemini the worst of the bunch, it constantly refused to help me in the past, but not only has it improved, ChatGPT seems to have gone down the 'nerfing' road where it now flat out refuses to do what I ask it to do quite often.
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Personally I find the current Google products mediocre almost on all aspects. The killer feature of chat bots is voice chat and ChatGPT works great, and Gemini is extremely quiet without a way to increase volume. It's also difficult to figure out how to sign up for Gemini, or even the keyboard that I'm typing is making so many incorrect predictions. I just don't trust Google. To me they're pure marketing and their engineering excellence ended a few years ago.
We are in a pretty amazing situation. If you're willing to go down 10% in benchmark scores, you easily 25% your costs. Now with Deepseek 3.2 another shot across the bow.
But if the ML, if SOTA intelligence becomes basically a price war, won't that mean that Google (and OpenAI and Microsoft and any other big model) lose big? Especially Google, as the margin even Google cloud (famously a lot lower than Google's other businesses) requires to survive has got to be sizeable.
Google trains its own AI with TPU's, which are designed in house. Google doesn't have to pay retail rates for Nvidia GPUs, like other hyperscalers in the AI rat race. Therefore, Google trains its AI for cheaper than everyone else. I think everyone else "loses big" other than Google.
> We will attempt to directly build safe and beneficial AGI, but will also consider our mission fulfilled if our work aids others to achieve this outcome.
They must be really glad to have so much competition then.
> If a value-aligned, safety-conscious project comes close to building AGI before we do, we commit to stop competing with and start assisting this project.
I wonder if OpenAI will start assisting Google now?
This will be the premise under which MS will acquire OAI talent after all the money has disappeared.
Funny that they did not declare "code red" when the CEO committed to 1.4T investments with only 13B in revenue to show?
Last week there we had a customer request that landed in our support on a feature that I partially wrote and wrote a pile of public documentation on. Support engineer ran customer query through Claude (trained on our public and internal docs) and it very, very confidently made a bunch of stuff up in the response. It was quite plausible sounding and it would have been great if it worked that way, but it didn't. While explaining why it was wrong in a Slack thread with support engineer and another engineer who also worked on that feature, he ran Augment (that has full source code of the feature) which promptly and also very confidently made up more stuff (but different!). Some choice bleeding eye emojis were exchanged. I'm going to continue to use my own intelligence, thank you.
How is that comment relevant to this story about OpenAI's response to perceptions that Google has gained in market share?
Relying on the model’s own “memory” to answer factual queries is almost always a mistake. Fine-tuning is almost always a more complex, more expensive and less effective method to give a model access to a knowledge base.
However using the model as a multi-hop search robot, leveraging it’s general background knowledge to guide the research flow and interpret findings, works exceedingly well.
Training with RL to optimize research tool use and reasoning is the way forward, at least until we have proper Stateful LLMs that can effectively manage an internal memory (as in Neural Turing Machines, and such).
"trained on our public and internal docs" trained how? Did you mean fine-tuned haiku? Did you actually fine tune correctly? Its not even a recommended architecture.
Or did you just misuse basic terminology about LLMs and are now saying it misbehaved, likely because your org did something very bad with?
All depends on the tasks and the prompting engineers.
Even with your intelligence you would need years to deliver something like this: https://github.com/7mind/jopa
The outcome will be better for sure, but you won't do anything like that in a couple of weeks. Even if you have a team of 10. Or 50.
And I'm not an LLM proponent. Just being an empirical realist.
I don't know man.
My code runs in 0.11s
Gemini's code runs in 0.5s.
Boss wants an explanation. ¯\_(ツ)_/¯
Yeah, LLMs are not really good about things that can't be done.
At some point you'll be better off with implementing features they hallucinated. Some people with public APIs already took this approach.
I declared 'code red' at my house as Google, OpenAI and Anthropic catch up in my software development career race.
Related:
TPUs vs. GPUs and why Google is positioned to win AI race in the long term
https://news.ycombinator.com/item?id=46069048
Google, Nvidia, and OpenAI
https://news.ycombinator.com/item?id=46108437
Title should really be OpenAI declares 'code red' as OpenAI falls behind in the AI race. Google, Anthropic, Mistral, DeepSeek, Tencent, Alibaba, Moonshot, Zai, etc have all made great strides. OpenAI has been falling behind in terms of velocity while everyone else is moving faster
> Altman said the company will be delaying initiatives like ads, shopping and health agents, and a personal assistant, Pulse, to focus on improving ChatGPT
It's so telling that they're delaying these "festures" because the know full well people don't want them.
I don't understand this view. I think most people would be happy to use the best models for free in exchange for seeing ads. That's basically what google and many others successfully do for decades.
How have OpenAI only just realized this?
ChatGPT is very complementary so they were probably high on their own supply.
If Gemini 3 had been a flop it wouldn't have been so bad for them.
Listen, I just had to go through numerous prompt cycles to 'prove' to 5.1 that we had a new Pope. ChatGPT was dead set that I was reading 'unreliable sources'. The data is _old_.
I work with Gemini 3 daily, and I think the hype is unwarranted. It takes shortcuts, hallucinates and its UI seems way behind. And what's with the small fonts?
Is anyone actually getting good results out of GPT Pro? For coding problems, GPT Thinking seems faster and more accurate. Pro has given me some very dumb answers actually, totally misunderstanding the question. Once I asked it do design a reverse osmosis system for our home, and it suggested a 7k system that can produce 400 liters per minute. Even though I explicitly told it that a couple liters per minute suffice.
Conspiracy time.
>be Google
>watch regulators circle like vultures
>realize antitrust heat is rising faster than stock buybacks can hide
>notice a small lab called OpenAI making exotic tech and attracting political fascination
>calculate that nothing freezes regulators like an unpredictable new frontier
>decide to treat OpenAI as an accidental firebreak
>let them sprint ahead unchecked watch lawmakers panic about hypothetical robot uprisings instead of market concentration
>antitrust hearings shift from “break up the giants” to “what is AGI and should we fear it”
>Google emerges looking ancient, harmless, almost quaint
>pressure dissipates
>execute phase two: acceleration roll out model updates in compressed cycles
>flood the web with AI-powered services
>redefine “the internet” as “whatever Google’s infrastructure indexes”
>regulators exhausted from chasing OpenAI’s shadow
>Google walks back onto the throne, not by hiding power, but by reframing it as inevitability conspiracy theorists argue whether this was 5D chess or simple opportunism
>Google search trends spike for “how did this happen”
>the answer sits in plain sight:
>attention is all you need
It's a fun idea but there's ample public reporting about how Google reacted to the rise of ChatGPT. There is reporting that Google was taken by surprise. You can be skeptical of that, but that's what the reporting says. ChatGPT went viral in Nov/Dec 2022, and by February or March Google was scrambling to stand up Bard as a viable competitor.
https://web.archive.org/web/20221221100606/https://www.nytim...
https://web.archive.org/web/20230512133437/https://www.theve...
That would be believable if you forget the sheer incompetence and bureaucracy Google was/is filled with
there is enough proof that they had a chatbot internally which was quite competitive but was not pushed through for all these fears, it seems they were always confident that they could catch up and scaling laws were their internal defense.
The question now though is neither might have expected Chinese labs to catch up so fast.
This is one conspiracy theory I've actually considered. Google waited until the Chrome outcome to come out swinging.
How does Anthropic fit into this? It's much smaller but feels like they have a much clearer product definition with their Claude Code.
Yes I’m wondering the same. I guess the news here is that google is finally getting the edge over OpenAI when they should have had the lead all along.
The first models were really bad, but the new models are very good—both text and image. They were able to clean up the embarrassing start and catch up. It's very interesting/scary that a giant corporation can develop things that new startups generated and deliver an alternative product on par with them.
What are devs using to run Gemini agents in vscode? 2.5pro on Cline/Roo was pretty buggy compared to Claude/gpt4/5 (also using Cline /roo), kept getting stuck in loops outputting repeated text and many editing issues, and much much worse than Claude code or codex. Has it gotten better? Is there a better way of using Gemini in vscode?
Most discussion focused on capabilities. But I wonder does OpenAI's "make a even big and costly model" strategy even work in long term? They are already losing money at current size. Unless we have some break though in chip efficiency.(which didn't seem to be likely for now) They are only going to loss even more.
In one of the Indian movies, there is a rather funny line that goes like this "tu jiss school se padh kar aaya hai mein uss school ka headmaster hoon". It would translate like this "The school from which you studied and came? I am the principal of that school". Looks like Google is about to show who the true principal is
I think the most relevant quote is from Futurama:
"Eh-de-de-de-de. Don't quote me regulations... I co-chaired the committee that reviewed the recommendation to revise the color of the book that regulation is in. We kept it gray."
Probably all of the ML foundation like transformers which OpenAI used to create its chatbot was originally developed at Google.
OpenAI fragmented into multiple companies that are now competing against them. OpenAI is buying compute and data.
Meanwhile, Google consolidated their AI operations under Google Deepmind and doubled down on TPUs.
The strategy "solve AGI and then solve everything else" is an all-in gamble that somehow AGI is within reach. This is not true.
Google fragmented into multiple competing companies as well, that's where OpenAI itself came from. The problem is even after shedding employees into all these startups or established competitors trying to catch up, Google has way more people, money, and compute to throw at things and see what works than the rest of the industry. It's demoralizing and tempting for people to go back, which is also demoralizing
This sounds like the wrong move- focusing on the product layer and counter positioning on ads is the way to beat G
Google is too big to fail. It's the backbone of the Internet. Just YouTube is synonymous with online video.
I don’t understand why anyone would think LLMs have a good moat. There’s no evidence to suggest that’s the case, and plenty of evidence to the contrary. Maybe hubris?
ChatGPT seems like a huge distraction for OpenAI if their goal is transformative AI
IMO: the largest value creation from AGI won’t come from building a better shopping or travel assistant. The real pot of gold is in workflow / labor automation but obviously they can’t admit that openly.
That boat sailed a long time ago
I don't read AI news or follow the industry, and from my perspective as a chatgpt user from day 1 is it's stalled for a long time now without improvements. The model feels old at this point. Claude Code highly impressed me, though.
AI creates the possibility to disrupt existing power structures - this is the only reason it gathers so much focus. If it were merely tool that increased efficiency of work, few would care so much. We already frequently get such tools which draw far less attention.
So far all it has done is entrench existing power structures by dis-empowering people who are struggling the most in current economic conditions. How exactly do you suppose that's going to change in the future if currently it's simply making the rich richer & the poor poorer?
It's just me or this article looks like propaganda? A traditional advertising nice is to plant news attacking your adversaries. This empty article looks like just part of the advertising machine of new Google model release.
OpenAI was founded a non-profit to benefit humanity. Why does the "race" matter?
OpenAI is for-profit: https://www.theguardian.com/technology/2025/oct/28/openai-fo...
They gave up on that a long time ago.
What will it do to Jony Ive’s legacy if his OpenAI device is no more successful than Snapchat’s foray into hardware?
If OpenAI becomes an also-ran by the time the hardware is released, this seems like a real possibility no matter how well-designed it is.
> What will it do to Jony Ive’s legacy if his OpenAI device is no more successful than Snapchat’s foray into hardware?
Well, in my opinion his legacy is already pretty tarnished by his last few years at Apple, his Love From company, and his partnership with OpenAI. If he somehow knocks it out of the park with OpenAI (something I don’t think will happen nor do I want it to) then maybe he can redeem himself a little bit but, again IMHO, he is already about as low as he can go. Whatever respect I had left for him vanished after the OpenAI/IO announcement video.
Not sure what you mean. His legacy to date is ruining the iphone because he couldn’t think of anything to do beyond “thinner”.
Did he come up with the butterfly keyboard as well?
This sounds like their medicine might be worse than what they're currently doing...
I’ve preferred Claude over ChatGPT for over a year so not sure what he’s on about.
A hardware device from OpenAI is exactly why I would prefer it over Anthropic or Google. Why give up on differentiation? I would assume the model team is separate from the consumer hardware team.
Honest question: What could a hardware device do that your phone can't do already?
what do you mean "catches up"
Gemini has been as good as GPT for more than a year
OpenAI still somehow gets the edge on the initial veneer of hype, and that's running thin
it's hard to get invested into anything google when they've been non stop killing products or making them worse for over a decade.
Certainly not the only one making things worse. Software has become an enemy of the people in the last 10 years. Remember when the internet was nominated for Nobel Peace price?
Does anyone have a link to the contents of the memo?
If OpenAI is smart here, they would figure out that you can make more money on a flop than with a hit. I bet an AI would figure that out.
As for my use cases, google and especially anthropic are not "catching up". They are better for long time already
Fix: Bring back Ilya, fire Sam Altman.
Ilya’s doing fine raking in billions for what’s effectively a D&D campaign
This is the system working.
Competition is all you need.
It’s funny because it wasn’t long ago Open Ai was telling everyone else it’s game over.
Surely they can just use AI to go faster and attend their daily calls for them...
I have the research to win the race. These people are masters of the fog.
History doesn't always repeat... but it sure as hell rhymes.
The fate of OpenAI is effectively sealed - it will go bankrupt and the scraps will get absorbed by Microsoft, for further enshitification. Not necessarily the "end" of AI, but enjoy your account while it's useful.
The problem is, there is a whole ecosystem of businesses operating as OpenAI API wrappers, and those are gonna get screeeeewed.
They will just have to change of LLM provider.
I take this code red as a red flag. Open AI should continue to concern itself with where it will be 5 years from now, not lose sight over concern about where it will 5 months from now.
open ai is at risk of complete collapse if it cannot fulfill its financial obligations. if people willing to give them money don't have faith in their ability to win the AI race anymore, then they're going out of business.
Back in the day before Adobe bought Macromedia, there was a constant back and forth between Illustrator and Freehand where each release would better the competitor at least until the competitor's next release.
Does anyone in AI think about 5 years from now?
isn't MSFT the one screwed here. Who is on the line to provide more compute for them .
Going short OPAI.PVT 10x leverage.
Googling OPAI.PVT brings me to https://finance.yahoo.com/quote/OPAI.PVT , which has links to equityzen and forgeglobal. How accurate are those valuations though?
This is great for customers.
Don't forget scuttling all the projects the staff has been working overtime to complete so that they can focus on "make it better!" waves hands frantically
"The results of this quarter were already baked in a couple of quarters ago"
- Jeff Bezos
Quite right tbh.
…someone even wrote a book about this. Something about “mythical men”… :D
I've had ideas for how to improve all the different chatbots for like 3 years, nobodys has implemented any of them (usually my ideas get implemented in software somehow the devs read my mind, but AI seems to be stuck with the same UI for LLMs), none of these AI shops are ran by people with vision it feels like. Everyone's just remaking a slightly better version of SmarterChild.
What if they make 2 daily calls, that would surely improve the velocity by 2 times!
Its easy to dismiss it but what would you do instead?
The beatings will continue until morale^H^H^H^H^H^H chatGPT improves...
Why doesnt he ask chat gpt to solve it all? He sells it saying it does everything!
> There will be a daily call for those tasked with improving the chatbot, the memo said, and Altman encouraged temporary team transfers to speed up development.
It's incredible how 50 year-old advice from The Mythical Man-Month are still not being heed. Throw in a knee-jerk solution of "daily call" (sound familiar?) for those involved while they are wading knee-deep through work and you have a perfect storm of terrible working conditions. My money is Google, who in my opinion have not only caught up, but surpassed OpenAI with their latest iteration of their AI offerings.
Besides, can't they just allocate more ChatGPT instances to accelerating their development?
> It's incredible how 50 year-old advice from The Mythical Man-Month are still not being heed.
A lot of advice is that way, which is why it is advice. If following it were easy everyone would just do it all the time, but if it's hard or there are temptations in the other direction, it has to be endlessly repeated.
Plus, there are always those special-snowflake guys who are "that's good advice for you, but for me it's different!"
Also it wouldn't surprise me if Sam Altman's talents aren't in management or successfully running a large organization, but in machiavellian manipulation and maneuvering.
Also, google has plenty of (unmatched?) proprietary data and their own money tree to fuel the money furnace.
There is always a daily call if a U.S. startup fails. Soon there will be quadrants and Ikigai Venn diagrams on the internal Slack.
Imho it just shows how relatively simple this technology really is, and nobody will have a moat. The bubble will pop.
the thought that this might be done one recommendation of ChatGPT has me rolling
think about it, with how much bad advice is out there in certain topics it's guaranteed that ChatGPT will promote common bad advice in many cases
Don't forget the bleak subtext of all this.
All these engineers working 70 hour weeks for world class sociopaths in some sort of fucked up space race to create a technology that is supposed to make all of them unemployed.
Wait, shouldn't their internal agents be able to do all this work by now?
I think most people are aligned on AI being in a bubble right now with the disagreement being over which companies (if any) will weather the storm through the burst and come out profitable on the far side.
OpenAI, imo, is absolutely going to crash and burn - it has absolutely underwhelming revenue and model performance compared to others and has made astronomical expenditure commitments. It's very possible that a government bailout partially covers those debts but the chance of the company surviving the burst when it has dug such a deep hole seems slim to none.
I am genuinely surprised that generally fiscally conservative and grounded people like Jensen are still accepting any of that crash risk.
Jensen cashed out on a billion dollars. Why would he even care anymore at this point?
For once, capitalism works
You can't make a baby in 1 month with 9 women, Sam.
"Code red" feels like theater. Competition is healthy - Google's compute advantage was always going to matter once they got serious. The real question isn't who's ahead this quarter, but whether anyone can maintain a moat when the underlying tech is rapidly commoditizing.
It was always clear that the insane technological monopoly of Google would always eventually allow them to surpass OpenAI once they stopped messing around and built a real product. It seems this is that moment. There is no healthy competition here because the two are not even remotely on the same footing.
"Code red" sounds about right. I don't see any way they can catch up. Their engineers at the moment (since many of the good researchers left) are not good enough to overcome the tech advantage. The piling debts of OpenAI just make it all worse.
Yeah, but now it's questionable whether the insane investments will ever pay off.
"Who is ahead this quarter" is pretty much all that the market and finance types care about. Maybe "who will be ahead next year" as a stretch. Nobody looks beyond a few quarters. Given how heavily AI is currently driven by (and driving!) the investment space, it's not surprising that they'll find themselves yanked around by extremely short term thinking.
It feels like (to me) that Google's TPU advantage (speculation is Meta is buying a bunch) will be one of the last things to be commoditized, which gives them a larger moat. Normal chips are hard enough to come by for this stuff.
Declaring a “code red” seems to be a direct result of strong competition?
Sure, from an outsider’s perspective, competition is fine.
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Google is shivering! /s
It’s actually code yellow
or maybe even code brown
Word needs need OpenAI and Anthropic like startups to drive AI forward. Think about only Google, Meta, MS, AWS is only have these capabilities. They will never able to do that in one hand, other hand it will be monopolistics. We need more AI startups, not monopolies.