All that compute is not needed. We have an existence proof from biology in the form of natural intelligence that much greater efficiency is possible. However, achieving dramatic improvements in compute efficiency will depend on unpredictable scientific breakthroughs. Personally I suspect that an entirely new hardware architecture will be needed, although I don't have any hard evidence to back that up.

I dunno, DeepSeek v4 Pro is rather on par as far as I can tell, maybe not with 5.5 Pro in all areas quite yet, but close.

I think China is thinking more about the application layer on top of models as going to matter more than the models themselves, so they don't need to gatekeep the models as much.

China is competing in value AI because they cannot work at the frontier, but how is this bad at all? It’s like how the USA has the best drones but they are a few million dollars apiece while China has DJI.

If China could work at the frontier, I don’t know, I kind of think they would still be dumping a lot of resources into exploring the value side since they have that culture already in place.

Forgive me if this is a naive assumption, but wouldn’t large language models be fundamentally different for a language that is largely symbols? Again, my understanding of Mandarin is limited if it exists at all.

> China is pursuing these because they cannot compete on the frontier.

? Claude, ChatGPT, etc are heinously expensive for tiny benefits lmao. Local + efficient is clearly the future

Well China is consistently 6 months behind the frontier labs(possibly because they can they harvest data from released frontier models). If the scaling continues, US will win, but if not then China will win as the models will converge.