China May Restrict Access to Its Most Powerful AI Models

tech

China May Restrict Access to Its Most Powerful AI Models

Chinese AI companies have made inroads globally by giving their models away for free. Now Beijing is weighing whether to stop them. Chinese authorities have held talks with Alibaba, ByteDance, and Z.ai about whether to restrict foreign access to their most advanced models, including ones not yet released, Reuters reported today, citing three people familiar with the discussions.

TL;DR

Chinese authorities are discussing whether to restrict foreign access to advanced AI models from companies like Alibaba, ByteDance, and Z.ai.
This potential restriction would be a significant change from the current "open-weight" model release strategy, which has helped Chinese AI gain global traction.
The discussions are reportedly driven by national security concerns, similar to U.S. restrictions on AI models.
Chinese AI models currently lag U.S. models by about seven months on average, with openness being a key competitive advantage.
Concerns exist about "distillation," where Chinese firms allegedly use outputs from U.S. models to improve their own, potentially violating terms and posing security risks.

Continue reading the original article

Yann LeCun reposted

Adam Thierer

We stand at a critical crossroads in the debate over AI governance in the United States, and it feels like we are inching closer to a very serious battle over whether or not open source models will even be allowed in an environment where a new de facto licensing regime has been taking shape.

Lacking formal congressional statutory frameworks or clear administration rules (like the diffusion rule revision), we appear to be left with a sporadic, arbitrary, non-transparent process for model review. The fiction of “voluntary” agreements hangs over this debate, and some large model developers are already showing an incredible willingness to bend over backwards to accommodate national security-related officials / orders that the rest of us are not privy to. It's a very opaque process. And those model developers are expected to play ball with those officials, or else their models get pulled from the market or held up for long periods. Or they will lose any government procurement contracts they have. There is nothing “voluntary” about it when that Sword of Damocles hangs in the room.

As this mess worsens, at some point the question of how to handle open source models will come into sharper focus because it will have to. I've even heard some rumors lately that something may be coming from the admin on this front to address this.

Needless to say, if this informal new AI model review regime expands and takes on more pre-vetting characteristics / requirements, it is hard to see how open source players could comply with such quasi-licensing of AI models. Specifically, if this ambiguous new regime is accompanied by a general presumption of ‘restrict-until-permitted,’ then that would spell doom for open source. That is a very dark path for our country.

Worse yet, of course, would be a move by national security officials to more directly restrict open source models and capabilities. If that happens, then we would be right back in the thick of a Clipper Chip-like battle along the lines of what we saw in the late 1990s. That is a much darker path for America.

Meanwhile, open source developers have no “golden shares” or other goodies to offer the government to make their problems go away.

Let’s be clear: If our government takes the dark path, it will become the single most important battle over computational freedom of modern times. It is time for people to make a stand in defense of open source before it is too late.

clem 🤗 reposted

Podcast Alpha

Chinese models are now 41% of Hugging Face downloads.

They passed the US.

Clem Delangue @ClemDelangue, CEO of the main open model platform, cites Hugging Face's own Spring 2026 report: Chinese open weights lead monthly and overall downloads. His harder claim is that open source is the accelerant behind AI leadership, so if China keeps leading open source, it could lead AI overall within a year or two.

Peter Diamandis @PeterDiamandis has walked through the same China-catching-up dynamic on his show, pointing at GLM matching Western frontier benchmarks.

For US frontier labs, this is a moat-erosion signal. For any US enterprise standardizing on Chinese open weights, it is a sovereignty question that has not been priced.

The full argument on why open source decides the AI race: https://t.co/9hvHpgtIp9

Source: Equity by TechCrunch - https://t.co/sMp6CzV9QV

Yann LeCun reposted

Daniel Jeffries

Replying to @Dr_Gingerballs

This is such a splitting hairs issue.

Like what would you want?

All the data? Not possible. Massive IP violation.

Training harness? Okay great, you can't run it at scale.

It's useful to have open models you can inspect and fine tune. Period. Yeah they are not "fully open"

Aravind Srinivas reposted

roon

the era of the chinese labs being far behind is over, Kimi is at least on par with the modern public frontier models. people have to think differently now without any competitive margin built in

Aravind Srinivas reposted

Chamath Palihapitiya

From Anthropic’s Fable model on the economic, moral, ethical and legal opinion of distillation of Anthropic’s Fable model:

Whether it’s a moral problem is genuinely contested. The labs trained their models on the open internet — copyrighted books, articles, code — largely without permission, and their fair-use defense is essentially “learning from data is transformative.” Distillation is the same argument turned against them: a model learning from another model’s outputs. It’s hard to construct a moral principle that permits the first and forbids the second, which is why critics call the labs’ objections hypocritical rather than principled.

Distillation is contentious because it lets a smaller model absorb much of a frontier model’s capability by training on its outputs — effectively free-riding on billions of dollars of compute, data curation, and RLHF work.

The DeepSeek episode made this concrete: if you can extract 80% of the value of a $1B training run for $5M by querying the API, the economics of frontier labs get shaky.

That’s the core anxiety — it’s a moat problem before it’s anything else.

Legally, it’s mostly a contract issue, not a copyright one. Model outputs likely aren’t copyrightable (no human author), so the labs’ real weapon is terms of service — every major API prohibits using outputs to train competing models. But ToS violations are breach of contract, hard to detect, hard to prove, and nearly unenforceable against a foreign entity. There’s no statute against distillation itself. So the practical answer: it’s an economic problem dressed in legal clothing, with a moral argument that cuts both ways depending on whose training data you start counting from.

David Sacks

This is concerning. For the first time, a Chinese model Kimi K3 has taken #1 on the Frontend Code Arena and is scoring at or near the frontier on other benchmarks.

Meanwhile America is tying itself in knots: politicians and bureaucrats are banning new data centers, piling on state regulations, and pushing for new federal agencies to pre-approve frontier models.

This is how you lose the AI race. The rest of the world won’t play by our rules if we bog ourselves down. Permissionless innovation is how America won the internet and became the technological envy of the world. We can do it again with AI -- while addressing risks in a targeted way -- or we’ll watch our lead evaporate.

clem 🤗 reposted

David Sacks

This is concerning. For the first time, a Chinese model Kimi K3 has taken #1 on the Frontend Code Arena and is scoring at or near the frontier on other benchmarks.

Meanwhile America is tying itself in knots: politicians and bureaucrats are banning new data centers, piling on state regulations, and pushing for new federal agencies to pre-approve frontier models.

David Sacks

I’m not sure whether Dean Ball is confessing to a regulatory capture strategy or simply predicting this will happen (he now says the latter). Either way, the weaponization of regulatory uncertainty as a competitive tool should be completely unacceptable.

He argues there’s no need to ban Chinese open-source models — just direct agencies to issue soft-law warnings that create enough FUD so regulated enterprises back off. “It needn’t be that well justified.”

Wrong. Regulatory decisions should always be well justified and grounded in facts, logic, and evidence, not the deliberate exploitation of fear and uncertainty. Implementing a surreptitious policy through manufactured doubt — rather than strong and explicit justification — corrodes the rule of law and invites future abuse against anyone.

We are at a critical inflection point in AI policy. The leading closed labs, already a duopoly in terms of AI model revenue, want the government to eliminate their open source competition. They have laid their cards on the table. It is time for the rest of Silicon Valley — the vast majority that still values open competition — to do the same.

David Sacks

Kimi K3 just fixed 15 critical security bugs that Codex and Fable refused because of “cyber guardrails.” There’s no reason to limit American models on tasks that Chinese models handle without issue. We’re only making ourselves less competitive.

clem 🤗 reposted

Anthony Pompliano 🌪

Banning Chinese models is the most un-American thing we could do.

Stop complaining and start competing.

People won't use Chinese models if American companies build something better.

clem 🤗 reposted

Jeff Whitehead

Hugging Face says it resorted to a Chinese AI model to battle a fully autonomous cyberattack because U.S. model guardrails stymied its defense

https://t.co/U9VO77ZSLl

clem 🤗

Banning open-source AI would hurt defenders 10x more than attackers, which would make the world 10x more dangerous and this is a good example why! https://t.co/Fv1z0zvJoZ