I think it might have accelerated things but on a much more basic level, there seems to be no real moat in synthesizing the world’s knowledge into LLMs.

My spend on DeepSeek is not much and I regularly top up my balance every month as my support for all the good work DeepSeek is doing for the open science.

Architectural/algorithmic tweaks do advance the efficiency frontier nicely. But raw intelligence mostly comes from data (not just its sheer quantity, but also how it's curated & cleansed) and the scaling law. The know-how about data curation doesn't seem to get published much, even among the open-weight labs, though.

I'm not sure I like this framing - so much of AI research has been academic, in the open, building on others people's work. Much less comp sci generally, math & philosophy, etc. The idea that rich companies can just build stuff in secret because they have resources is a fantasy.

So boring to see conversations moved over to Chinese models when that’s not even what we’re talking about here. This is about Mistral.

How it should be. Knowledge should not be copyrighted. The world will be a better place with such information democratized

Also, the field moves fast, but slower than people do. Researchers and engineers switch companies every year or two, and the know-how walks out the door with them.

There would be a lot of competition even without DeepSeek. Workers can freely exfiltrate trade secrets without noncompetes in California.

>instruction manuals in paper form

So the most common way to publish manuals?