I think a big part of that is the Chinese publishing the solution for everywhere hurdle in the road they've encountered in the form of a paper.

Deepseek essentially releases instruction manuals in paper form.

> have not been a winner-take-all runaway acceleration game where catchup is impossible

From the Mistral site:

> ML4 was trained from scratch on 3,800 NVIDIA Grace Blackwell GPUs in Mistral’s own datacenters in Europe.

It is pretty capital intensive!

For sure people who don't grasp the difference between models, might be stuck in 'good enough' models.

But Opus 5.5/GPT is such a game changer in comparison to sooo many others, its still a moat for now.

It's shaping up to be much more like a game of 'chicken' where each company tries to raise more cash without going bust... Ultimately the game of musical chairs is going to have to stop. In the US it looks like they are trying to get a government sanctioned truce in the form of regulation. That's what 'Pacing the frontier' means...

Even "runaway acceleration" isn't instantaneous. People imagine the singularity as something that happens almost instantaneously. But obviously it happens over time, and that time might be decades. It might still end up looking like a vertical line on a long-term graph.

If the singularity is defined as an AI sufficiently intelligent to improve itself independently, that AI is still limited by the resources required to do this improvement.

Am I reading this correctly?

This appears to be roughly as good as Sol 6.1 (which is quite good), considerably faster in terms of wall clock for complete tasks, and considerably cheaper (where Sol 6.1 is already good value - just really slow).

That seems too good to be true...

But I really hope it is true...

Hear! Hear! I really want European models / AI labs to succeed.

I trust them and their populations to provide a more societal-friendly version of AI, putting pressure on the US tech oligarchy, while also providing democracy-friendly open models that I don't trust to happen with the Chinese labs.

this will be quite obsolete by the time the weights are released. still though, it's always good to see open weight releases

It will become winner take all when AI companies manage to really get value from user logs.

Right now they don't even get good feedback from local sessions - I can see it make the same mistake two days running, and then months later when a new model comes out, presumably trained on my data, it still makes the same mistake.

I strongly disagree with this "early days" framing.

AI is an idea 60 years old. We are on the 3rd or 4th generation of AI development. Three years into the current iteration of products.

This is not early days by any measure. LLMs are a result of a very, very mature research field.

We haven't reached RSI yet. Once any entity reaches RSI, the runway scenario will happen.

What do you mean "good enough"? Did you mean "large enough"? ;)

Disclaimer: I'm not sure how much of an IYKYK factor applies to this joke.

Yes, so far the competitive dynamics feel more like cloud computing than web search.

Especially with Mistral taking a fraction of the investment of the big guys. They can maintain the position pretty comfortably just by staying within a standard deviation of the leaders.

Hard to do that with a commodity that's easily replicated.

> Its quite interesting to see that at least the early days of AI so far have not been a winner-take-all runaway acceleration game where catchup is impossible.

Mistral is also an European company. As we live in a time where the US regime is engaged in pyrrhic geopolitical tactics, it's good to know that it can't threaten to cut access to models during s period where everyone is rushing to incorporate them more and more in our life.

I think it's a mistaken belief that AI as we found it is the exponential runaway train.

So it makes sense, since all you need is compute, that there's a ceiling and specialization is going to be more valuable then some super AGI.

Especially since the worst people seem to be the ones who think they'll all run away with the bag.

I mean, Mistral is about 9-12 months behind here when you look at its overall benchmarks versus the models released around a year ago.

I don't think it is, and I think that is what will pop the bubble. All these companies have winner take all valuations, and that won't happen.

... unless they can legislate it, which is why they are flattering heads of state and scare mongering about dangerous AI.

On a purely technical level, maybe? But in terms of actual revenue, is there really any chance of anyone catching the big labs?

Obviously, this is only a valid question if you don't believe that open weights are about to eat their lunch and their revenue is about to collapse, or they're running a super unprofitable ponzi scheme propped up by investor money that's about to collapse like a house of cards. I don't find those positions credible at all though.

If you do, then this question isn't really for you, as I'm more interested in thoughts from those who think that OpenAI and Anthropic in particular are about to be the largest companies on earth in a couple years. Could anyone catch them at that point?

[dead]

How do you figure? I haven't met a single person who doesn't use Claude or Codex for programming in any serious way.

It's a retrain of asian model.

Seems silly not to have predicted that 10 years ago. I feel like it's long been obvious that smarter models being available will mean way easier cheap synthetic data and access to tools that will speed up competitors as well as consumers.