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I don't see it happening. Increased military spending, sure, but individual member states will not give up their authority on war and geopolitical matters. Will France or Germany abolish their ministries and delegate it all to von der Leyen? So the structural problem remains.

"European leaders" operate under a permanent disadvantage because they have to agree among themselves to do anything. This leaves them unable to take the initiative geopolitically, and prone to taking whatever's the path of least resistance lying before them. The US and Russia have concluded that Europe will roll over and accept whatever they are presented with, after some angsty wailing, and unfortunately they are probably right. Not inviting Europe to talks is just a dominance move showing that they know the Europeans can't do anything about it.

Unfortunately for Europe, this is just the logical end point of their institutional arrangements. In a domain like geopolitics, where there are intelligent players looking for advantage, it is suicidal to turn off your ability to make decisions.

Dylan's just being deliberately obtuse. Deepseek developed a way to increase training efficiency and backed it up by quoting the training cost in terms of the market price of the GPU time. They didn't include the cost of the rest of their datacenter, researcher salaries, etc., because why would you include those numbers when evaluating model training efficiency???

The training efficiency improvement passes the sniff test based on the theory in their paper, and people have done back of the envelope calculations that also agree with the outcome. There's little reason to doubt it. In fact people have made the opposite criticism, that none of Deepseek's optimizations are individually groundbreaking and all they did is "merely engineering" in terms of putting a dozen or so known optimization ideas together.

Aside from national pride or security, one issue is that there's a Taiwan law requiring TSMC to keep latest gen fabs in Taiwan. So if TSMC takes over Intel fabs, Intel's US operations will never be able to reach latest gen (not that Intel is currently in good shape to achieve this, of course).

Slightly off topic, but the writing on this article is horrible. Optimizing for Google engagement, it seems. Ironically, an AI would probably have produced something vastly more readable.

Aww come on. There's plenty to be mad at Zuckerberg about, but releasing Llama under a semi-permissive license was a massive gift to the world. It gave independent researchers access to a working LLM for the first time. For example, Deepseek got their start messing around with Llama derivatives back in the day (though, to be clear, their MIT-licensed V3 and R1 models are not Llama derivatives).

As for open training data, its a good ideal but I don't think it's a realistic possibility for any organization that wants to build a workable LLM. These things use trillions of documents in training, and no matter how hard you try to clean the data, there's definitely going to be something lawyers can find to sue you over. No organization is going to open themselves up to the liability. And if you gimp your data set, you get a dumb AI that nobody wants to use.

The underlying research story is interesting, but the way it's written up actively makes it worse.

The researchers based s1 on Qwen2.5, an open-source model from Alibaba Cloud.

Watch me create a racing car for less than $50. Step 1: start with a Mercedes F1 racer...

It's definitely a trend. More and more top Chinese students are also opting to stay in China for university, rather than going to the US or Europe to study. It's in part due to a good thing, i.e. the improving quality of China's universities and top companies. But I think it's a troubling development for China overall. One of China's strengths over the past few decades has been their people's eagerness to engage with the outside world, and turning inward will not be beneficial for them in the long run.

But Mistral could do all that, with a far lower chance of pissing away the money...

Why not just put the money into Mistral? Mistral seems to be pretty cash-strapped and they're just about the only EU entity doing anything interesting with LLMs, and they've released open models before. Commissioning a bunch of models from them would be a better use of money than spreading it among a bunch of randos.

Chinese or not, it's MIT licensed. A world where any company can spend ~$10k to locally deploy a frontier reasoning model is very different from one where you can only get AI via API access to a handful of US tech giants.

Rare earths to begin with. There will be more demands.