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China’s open-weights AI strategy is winning

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Re: China’s open-weights AI strategy is winning

#171
post #165

The article's premise is that USA based LLM providers are losing the AI (cold war) battle because it will not be as adopted as open-weight models, comparing it to closed vs open sourced software. I do not think this is the case because: * The comparison is weird because open-weight is not the same as open-source software to begin with; * People based in the USA are at an advantaged position since they have access to…

The Chinese models are usually not only open weight AND open-source but they also often publish their methodology in detailed scholarly publications that are themselves open-access. DeepSeek most famously

Re: China’s open-weights AI strategy is winning

#175

Earlier quoted context omitted.

Yeah. People should absolutely be _trying_ the Chinese models, and experimenting with running things locally, but the noise in development is genuinely all Claude and Codex. I put my foot in the mobile comparison the other day, and will again. If you were to go back and be a mobile dev in 2010 by all means specialize on one platform, but play with both as a professional interest to stay realistic. Here it's important…

If startups includes openclaw users then I could see this being true. Deepseek is barely behind frontier models while 10x cheaper and 99% discount for cache.

people still use clawdbot?

Re: China’s open-weights AI strategy is winning

#176
A major turnoff for me has been the American AI labs’ marketing

It’s either constant fear mongering (Anthropic), regulatory threats and corporate chicanery (OAI), low quality sloppification (xAI), or ‘ummm we have AI too guys’ (Gemini)

The worst culprit is Anthropic. Every two weeks he pops up on some random podcast with dire predictions of AI killing 50% of all jobs. It’s the constant “us our AI or else…” rhetoric that’s made the regular guy really hate AI

There is almost no positive sum outcome rhetoric from these labs

And I hate that

Re: China’s open-weights AI strategy is winning

#177

So how would I use these Chinese models by API? I assume I'll pay by API call.

In theory Cerebras have a developer subscription model you can use, but they seem to have stopped new signups. So per sibling, OpenRouter and per-call pricing is the answer for now.

Re: China’s open-weights AI strategy is winning

#178
post #6

I’m suspicious of some quotes here, “80% of startups using Chinese models,” doesn’t seem quite right to me. I just interviewed at several startups and they were all using the US models. Maybe they have some minor use of Chinese models but the bread-and-butter of most of these businesses model use is the Claude and Codex subscriptions.

Not everything runs on paid models. Claude and Codex are frontier models, but some people have much higher usage needs and finite budgets that force them to self-host. And if you're self-hosting, you're very likely running a Chinese model

Re: China’s open-weights AI strategy is winning

#179

Earlier quoted context omitted.

If if it were true, who cares? Most startups fail. Most are terrible ideas and/or terribly executed. I fail to see why it's a useful metric.

Is your point that startups fail so we should disregard the central thesis that locked down AI will eventually lost to open models?

I don't see that anywhere in the parent's comment. Where did you get all that?

Re: China’s open-weights AI strategy is winning

#180
post #6

I’m suspicious of some quotes here, “80% of startups using Chinese models,” doesn’t seem quite right to me. I just interviewed at several startups and they were all using the US models. Maybe they have some minor use of Chinese models but the bread-and-butter of most of these businesses model use is the Claude and Codex subscriptions.

Not everything runs on paid models. Claude and Codex are frontier models, but some people have much higher usage needs and finite budgets that force them to self-host. And if you're self-hosting, you're very likely running a Chinese model

Especially if you're pre-funding, which the sampled startups (those pitching A16Z) were.
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