[crowcroft]

Meta's end goal is to have better AI than everyone else, in the medium term that means they want to have the best foundational models. How does this help.

1. They become an attractive place for AI researchers to work, and can bring in better staff. 2. They make it less appealing for startups to enter the space and build large foundation models (Meta would prefer 1,000 startups pop up and play around with other people's models, than 1000 startups popping up and trying to build better foundational models). 3. They put cost pressure on AI as a service providers. When LLAMA exists it's harder for companies to make a profit just selling access to models. Along with 2 this further limits the possibility of startups entering the foundational model space, because the path to monetization/breakeven is more difficult.

Essentially this puts Meta, Google, and OpenAI/Microsoft (Anthropic/Amazon as a number four maybe) as the only real players in the cutting edge foundational model space. Worst case scenario they maintain their place in the current tech hegemony as newcomers are blocked from competing.

[siquick]

> Essentially this puts Meta, Google, and OpenAI/Microsoft (Anthropic/Amazon as a number four maybe) as the only real players in the cutting edge foundational model space.

Mistral is right up there.

[yodsanklai]

Mistral has ~20 employees. I'm sure they have good researchers, but don't they lack the computing and engineering resources the big actors have?

[crowcroft]

I'm curious to see how they go, I might have a limited understanding. From what I can tell they do a good job in terms of value and efficiency with 'lighter' models, but I don't put them in the same category as the others in the sense that they aren't producing the massive absolute best in class LLMs.

Hopefully they can prove me wrong though!