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OpenAI declares 'code red' as Google catches up in AI race

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Re: OpenAI declares 'code red' as Google catches up in AI race

#481
post #5

> 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.

ha what an incredible consumer-friendly outcome! Hopefully competition keeps the focus on improving models and prevents irritating kinds of monetization

If they don't start on ads and shopping, they're going to go out of business.

I'd rather a product that exists with ads, over one that's disappeared.

The fact is, personal subscriptions don't cover the bills if you're going to keep a free tier. Ads do. I don't like it any more than you do, but I'm a realist about it.

Re: OpenAI declares 'code red' as Google catches up in AI race

#482

Earlier quoted context omitted.

This analogy only really works for companies whose gross margin is negative, which as far as I know isn’t the case for OpenAI (though I could be wrong). It’s an especially good analogy if there is no plausible path to positive gross margin (e.g. the old MoviePass) which I think is even less likely to be true for OpenAI.

Why is it that I feel like your confidence in OpenAI's path to profitability exceeds Sam Altman's?

I'm not confident at all. I didn't say "there is definitely a path". I said the existence of such a path is plausible. I'm sure Sam Altman believes that too, or he'd have changed jobs ages ago.

Re: OpenAI declares 'code red' as Google catches up in AI race

#483
post #461

Earlier quoted context omitted.

By learning to parallelize my work. This also solved my problem with slow Xcode builds.

Well you can’t edit files while Xcode is building or the compiler will throw up, so I‘m wondering what you mean here. You can’t even run swift test in 2 agents at the same time, because swift serializes access for some reason. Whenever I have more than 1 agent run Swift tests in a loop to fix things, and another one to build something, the latter will disturb the former and I need to cancel. And then there’s a lot of…

I use the web ui, easy to parallelize stuff to 90% done. manually finish the last 10% and a quick test

Re: OpenAI declares 'code red' as Google catches up in AI race

#484
post #415

Earlier quoted context omitted.

You think a company the size of OAI should have a single priority? That makes no sense, that’s putting all their eggs on one basket.

All their services depend on their models. Their main priority should be that. If they're too thin, it gets affected. What can openai do that, even if their models lag behind, will let them keep their competitive advantage?

There are many reasons:

1. ChatGPT has a better UX than competitors.

2. Some people have become very tied to the memory ChatGPT has of them.

3. Inertia is powerful. They just have to stay close enough to competitors to retain people, even if they aren’t “winning” at a given point in time.

4. The harness for their models is also incredibly important. A big reason I continue to use Claude Code is that the tooling is so much better than Codex. Similarly, nothing comes close to ChatGPT when it comes to search (maybe other deep research offerings might, but they’re much slower).

These are all pretty powerful ways that ChatGPT gets new users and retains them beyond just having the best models.

Re: OpenAI declares 'code red' as Google catches up in AI race

#485

Earlier quoted context omitted.

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.

Completely failed for me running the code it changed in a docker container i keep running. Claude did it flawlessly. It absolutely rocks at code reviews but ir‘s terrible in comparison generating code

It really depends on what kind of code. I've found it incredible for frontend dev, and for scripts. It falls apart in more complex projects and monorepos

Re: OpenAI declares 'code red' as Google catches up in AI race

#486

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…

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.

This is the way. (Sadly)

Re: OpenAI declares 'code red' as Google catches up in AI race

#487
post #359

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 expe…

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 Ope…

Because it would take many years, and Google is using its own TPUs anyway.

Re: OpenAI declares 'code red' as Google catches up in AI race

#488
post #258

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 TPU architecture is the most impressive thing I care about. They developed them and have been using them internally for years. This shows they grok what they're actually doing.

There are serious philosophical problems with betting big on an interesting outcome like ChatGPT, even though it seems obvious (Google also did this of course), but creating the best architecture to do that job seems like a first-principles intelligent move, because there was no reason to keep using graphics cards except that they "did the job."

Re: OpenAI declares 'code red' as Google catches up in AI race

#489

(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…

GPT4.5 was allegedly such a pre-train. It just didn’t perform good enough to announce and product it as such.

it wasn't economical to deploy but i expect it wasn't wasted, expect the openai team to pick that back up at some point

Re: OpenAI declares 'code red' as Google catches up in AI race

#490

Earlier quoted context omitted.

This would trigger something that people in power would rather not trigger.

the only thing power is concerned about is China dominating American in AI, because of the military and economic edge it would give them. Future wars will be AI fighting against AI.

Even Chinese leadership is somewhat skeptical about AI maximalism [0] with worries about "AI Washing" by enthusiastic cadre trying to climb rungs [1], and evoking Solow's Paradox [2].

There is still significant value in AI/ML Applications from a NatSec perspective, but no one is actually seriously thinking about AGI in the near future. In a lot of cases, AI from a NatSec perspective is around labor augmentation (how do I reduce toil in analysis), pattern recognition (how do I better differentiate bird from FPV drone), or Tiny/Edge ML (how do I distill models such that I can embed them into commodity hardware to scale out production).

It's the same reason why during the Chips War zeitgeist, while the media was harping about sub-7nm, much of the funding was actually targeted towards legacy nodes (14/28nm), chip packaging (largely offshored to China in the 2010s because it was viewed as low margins/low value work), and compound semiconductors (heavily utilized in avionics).

[0] - https://www.zaobao.com.sg/news/china/story20250829-7432514

[1] - https://finance.sina.com.cn/roll/2025-09-30/doc-infsfmit7787...

[2] - https://m.huxiu.com/article/4780003.html

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