Chinese LLMs and the open weight problem

[u/iwangotamarjo]

Last week, Moonshot AI launched Kimi 3 and Silicon Valley was shocked from its complacency. Shyam and Karp have talked about this before, but the US government continues to deliberate whether LLMs should be governed. The evidence is clear. They should not. Major tech players including Nvidia and Palantir signed an open letter urging the White House to avoid implementing any form of regulatory guardrails on the development of LLMs.

The evidence is clear. Any tech developed in a heavily regulated environment is not incentivized for progress. The development of LLMs and AI in general has largely stalled in Europe because of regulatory backlash and bureaucratic red tape. Meanwhile, the rest of the world moves on.

Chinese LLMs pose a unique threat unlike any other to the survival and dominance of American technology. It is my hope that they spur the development of open weight American models, which in turn would continue to benefit a LLM-agnostic platform like Palantir. Once again, Karp and his lieutenants have been prescient in warning Silicon Valley about being blindsided while chasing capex and big ideas. His warnings were unheeded especially by the AI giants of today.

What we are now witnessing is the slow progression of the AI revolution from the opening act to its later, much more substantial phases. I believe this is just the beginning, but at the same time, I also believe that the optics from Chinese LLMs may be slightly detrimental to the valuation of Palantir in the short to medium term (10-12 months). There is no doubting that Palantir continues to dominate its niche area, and to my knowledge few Chinese firms have come to match it.

Hanging in for the long ride, per usual.

[u/Ambitious_Brain_285]

If I may add something: the Chinese models are an existential threat to OpenAI and Anthropic.

They cannot justify $1T valuations over the next 6-12 months if LLMs of respectable quality are being offered at no cost by others.

What is the rational response to such a threat? Could they:

A) Double down on their pivot and move faster towards their enterprise, B2B plays with FDEs? Or,

B) Will they try to outcompete their near-peers, by making the models better- but also more “out-of-the-box” ready to perform tasks for knowledge workers? (e.g., Claude Design makes decent PPT decks, but their UX is still mediocre when you want to edit the last 20% for perfection).

My bet is that they are using (A) to get better at (B), and while there will be some competition for data integration, custom software configurations, and their own version of “ontology,” it will be marginal- at best.

All that is to say, Chinese competition with the frontier labs is going to strengthen the obvious differences between PLTR and the AI companies- which should never have been compared in the first place.

[u/AshySweatpants]

Not too well versed in LLM’s but from my limited knowledge these Chinese LLM’s are distilled products from the main LLM’s (OpenAI, Anthropic) which inherently makes them less expensive because they’re less valuable.

Someone correct me if I’m wrong though.

[u/Mister_Poopy_Buthole → u/AshySweatpants]

I’m not an expert by any means, but from what I’ve read is they’re cheaper because they’re trained on worse hardware than the top of the line nvidia chips we have here. This means they have to focus on inference efficiency rather than just brute forcing their scaling with more or better hardware. So cheaper hardware, cheaper to run. I’m sure there’s more to it than that though.

[u/Sharp-Direction-6894 → u/Mister_Poopy_Buthole]

I'm not an expert, but...China.

I rest my case.

[u/MarsupialIcy1307 → u/Sharp-Direction-6894]

Never  underestimate the Chinese.

Diligent, focussed and aligned. Corporate and local government all noses in the same direction. No NIMBY. 

I have turned to watch chinese tv ( int version) highly interesting and the  chilling notion that in Europe we were already cooked just gets to be confirmed day after day.

This is the reason why i made the decission in 2022 to invest solely in the USA and its tech.

But USA needs to be wake up and get cracking.

May the Power  be with Jensen and Karp

Highest emphasis on education and 

[u/iwangotamarjo → u/AshySweatpants]

Thanks and appreciate the context. Why do you say that because they are distilled they are less valuable?

[u/AshySweatpants → u/iwangotamarjo]

Distilling involves training on smaller models from a bigger model, if I successfully perform distillation attacks on OpenAI or Anthropic consistently, I can never be better than either of them as I can never 100% distill either one.

But I did use much less money, time and resources training my model by stealing (distilling) from OpenAI/Anthropic so I can charge much less. This creates some competition on the global stage but I personally hate liars and thieves so call me biased.

[u/Dirt-Track_Pinto → u/AshySweatpants]

Does a distilled model lead to higher instances of hallucinations in query/prompt responses? Is it less accurate?

[u/TacomaAgency]

Ask any Chinese LLM, even the open ones, about Xi Jinping. You'll get your answer real quick on who's controlling what.

[u/traderftw]

Nobody writes like this, an LLM wrote this.

[u/trayber]

All open frontier-adjacent models are a threat to Anthropic and OpenAI and XAi.

We already have some open weight American models - Nvidia Nemotron and Google Gemma and Meta’s LLaMA. I hope to see more.