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People underestimate the lead OAI has with their post-5.2 models. The author does not strike me as someone who closely follows the progress frontier labs make i
by sinenomine 7mo ago
People underestimate the lead OAI has with their post-5.2 models. The author does not strike me as someone who closely follows the progress frontier labs make in US and around the world.
- hyperbovine 7mo agoAgreed, compare the frontier models from Google and OAI. It’s like night and day. Anyone who says “the tech has caught up” has not spent even one day using Gemini 3.1 to try and accomplish something complicated.
- PunchTornado 7mo agoI think the vast majority of coding us done through claude and gemini
- energy123 7mo agoIt's a joint ignorance of how these frontier models get baked and what consumers want. Many pundits think it's just a matter of scraping the internet and having a few ML scientists run ablation experiments to tune hyperparameters. That hasn't been true for over a year. The current requirements are more org-scale, more payoff from scale, more moat. The main legitimate competitive threat is adversarial distillation. Many pundits also think that consumers don't want to pay a premium for small differences on the margin. That is very wrong-headed. I pay $200/month to a frontier lab because, even though it's only a few % higher in benchmark scores, it is 5x more useful on the margin.
- nick32661123 7mo agoYou pay to OpenAI or which one do you use? Do you switch regularly?
- energy123 7mo agoI pay OpenAI but I would also be a happy Anthropic customer. My view is that OpenAI, Anthropic and Google have a good moat. It's now an oligopolistic market with extreme barriers to entry due to needed scale. The moat will keep growing as the payoffs from scale keep growing. They have internal scale and scope economies as the breadth of synthetic data expands. The small differences between the labs now are the initial conditions that will magnify the differences later. It wouldn't be surprising to also see consolidation of the industry in the next 2 years which makes it even more difficult to compete, as 2 or 3 winners gobble up everyone and solidify their leads. When people worry about frontier lab's moat, they point to open weights models, which is really a commentary that these models have zero cost to replicate (like all software). But I think the era of open weights competition cannot be sustained, it's a temporary phenomenon tied to the middle-ground scale we're in where labs can still do that affordably. The absolute end of this will be the end-game of nation state backed competition.
- svnt 7mo agoIt is the benchmark error rate, not the benchmark success %, that we actually trip up on. Going from 85% to 90% is possibly 1/3 fewer errors or even higher, depending on the distribution of work you’re doing.
- lelanthran 7mo ago> The current requirements are more org-scale, more payoff from scale, more moat. What moat? None of the AI providers have a moat at the moment, and the trend doesn't indicate that any of them will in the near future.
- energy123 7mo agoI made 2 posts in this thread regarding why I think they have a moat. Was there anything ambiguous or that you disagreed with?
- lelanthran 7mo ago> I made 2 posts in this thread regarding why I think they have a moat. Was there anything ambiguous or that you disagreed with? I'm afraid I don't see those posts; I see 2x posts from you asserting they have a moat, but not why you think they have a moat. I distinguish between "They have a moat." and "This is why $FOO, $BAR and $BAZ forms a moat." Maybe you think brand recognition is a moat, but that didn't work out for incumbents before (too many examples to list).
- energy123 7mo agoIt was kind of buried in my second post: > They have internal scale and scope economies as the breadth of synthetic data expands. These frontier labs will have a hundred or a thousand teams of people+AI working in parallel generating synthetic data to solve different niches. A few teams solve computer use. A few teams solve math. A few teams solve various games. So the org is basically a big machine that mints data, and model research is only a small part of it. Scale then is the moat. The second leg of the moat thesis is that open weights competition will die off soon because the cost to keep up with the scale will be too excessive. The third leg of the moat thesis is that customers are happy to pay big margins for differences that appear small if the benchmark is the measuring stick. If the paradigm was still scrape internet -> train model, I'd agree that there is no moat.
- 7mo ago
- PunchTornado 7mo agoFunny. What lead? Gemini and Claude are much better.
- nextlevelwizard 7mo agoYeah. I also do not see the lead. Claude Opus writes better code and for conversation all models even Le Chat is just better than ChatGPT currently.
- wiseowise 7mo ago> for conversation all models even Le Chat is just better than ChatGPT currently Not sure what you’re smoking, but I want some.
- nextlevelwizard 7mo agoI am smoking this thing called: putting same prompt in four different apps and seeing which ones give me answers and which ones hallucinate and patronize me, but considering your comment I can see how you would prefer ChatGPT
- wiseowise 7mo agoHave you tried actually holding a conversation with it? I'm really puzzled in which world Gemini/Claude is better than ChatGPT for day-to-day tasks/conversations. Claude can't even search products on Amazon, Jesus.