In the AI talent war, it is clear that the demand for expertise in training (esp post-training) models is high, and will be even higher as diffusion of these capabilities happens across many downstream industries.
The proposal of OSS labs to capture this opportunity is strong! Very thoughtful post!
While I tend to agree with your point on models + other components being the main driver of value at the moment, it seems like the highest level of the stack is closer to commoditization. If we look at coding harnesses, it seems like frontier models can perform just fine in third party harnesses like OpenCode, the Pi coding agent, an all the other open source coding harnesses.
So from a user perspective isn’t it conceivable that the “ownership” of the rest of the stack doesn’t matter as much?
Of course the way these models become useful in third party harnesses involves a huge investment in RL infra…
> Nvidia has the one great reason to be open [...], but there’s no one else obvious on this list. Until there are more specific economic reasons to build open models, the companies building these at the frontier will have fewer resources to spend on the models and face a consolidation to the best few.
I disagree with this statement. I think Chinese companies in particular have plenty of reasons to be open, which they've shown over the last year and a half.
There's no way for China to realistically achieve world dominance in AI. They can make great models, sure, but there's no way for a Chinese company to compete with OpenAI or Anthropic in western markets. AI is all about data, and no serious enterprise will ever agree to send their most important data to China, or even to a Chinese company with datacenters in the west. They have more of a chance in consumer, TikTok managed to get extremely popular despite being Chinese after all, but I think people's privacy requirements for "swipes on funny cat videos" are very different than their requirements for their medical information and relationship advice, despite the fact that the former are often sufficient to reconstruct the latter.
If China cannot win, the next best thing they can do is to make sure the west doesn't win either. The way to do that is to publish great open models for free, taking a loss which the Chinese state coffers can bear, but making sure that privately-run, profit-oriented American companies, who have to recoup their costs of training, have no chance of competing.
A large gap between SOTa and open models is bad for China, because they can't (and don't want to) use the SOTA models. Conversely, any research which brings open models closer to the frontier is propping China up.
I also think that open models are particularly great for China because of their GPU restrictions, as they essentially allow them to externalize some of their research cost onto external researchers, whose results they can later incorporate.
The above is not meant as a critique of open models. As a European aligned with western values, yet working for an institution that's a lot more GPU-poor than many places in China, I have learned plenty from papers and blog posts published by AI2 and Huggingface, and I hugely appreciate what those organizations are doing. I think open models are great and broadly beneficial to everybody, they're just more beneficial to China than to everybody else (and that's fine).
In the AI talent war, it is clear that the demand for expertise in training (esp post-training) models is high, and will be even higher as diffusion of these capabilities happens across many downstream industries.
The proposal of OSS labs to capture this opportunity is strong! Very thoughtful post!
While I tend to agree with your point on models + other components being the main driver of value at the moment, it seems like the highest level of the stack is closer to commoditization. If we look at coding harnesses, it seems like frontier models can perform just fine in third party harnesses like OpenCode, the Pi coding agent, an all the other open source coding harnesses.
So from a user perspective isn’t it conceivable that the “ownership” of the rest of the stack doesn’t matter as much?
Of course the way these models become useful in third party harnesses involves a huge investment in RL infra…
> Nvidia has the one great reason to be open [...], but there’s no one else obvious on this list. Until there are more specific economic reasons to build open models, the companies building these at the frontier will have fewer resources to spend on the models and face a consolidation to the best few.
I disagree with this statement. I think Chinese companies in particular have plenty of reasons to be open, which they've shown over the last year and a half.
There's no way for China to realistically achieve world dominance in AI. They can make great models, sure, but there's no way for a Chinese company to compete with OpenAI or Anthropic in western markets. AI is all about data, and no serious enterprise will ever agree to send their most important data to China, or even to a Chinese company with datacenters in the west. They have more of a chance in consumer, TikTok managed to get extremely popular despite being Chinese after all, but I think people's privacy requirements for "swipes on funny cat videos" are very different than their requirements for their medical information and relationship advice, despite the fact that the former are often sufficient to reconstruct the latter.
If China cannot win, the next best thing they can do is to make sure the west doesn't win either. The way to do that is to publish great open models for free, taking a loss which the Chinese state coffers can bear, but making sure that privately-run, profit-oriented American companies, who have to recoup their costs of training, have no chance of competing.
A large gap between SOTa and open models is bad for China, because they can't (and don't want to) use the SOTA models. Conversely, any research which brings open models closer to the frontier is propping China up.
I also think that open models are particularly great for China because of their GPU restrictions, as they essentially allow them to externalize some of their research cost onto external researchers, whose results they can later incorporate.
The above is not meant as a critique of open models. As a European aligned with western values, yet working for an institution that's a lot more GPU-poor than many places in China, I have learned plenty from papers and blog posts published by AI2 and Huggingface, and I hugely appreciate what those organizations are doing. I think open models are great and broadly beneficial to everybody, they're just more beneficial to China than to everybody else (and that's fine).