The First Time in AI History: A Model Goes Live for Three Days and Then the Government Forces It Offline—Who’s Binding Themselves Hand and Foot?

What would you do if one day your project gets hit with a “pause button”?

Don’t assume it has nothing to do with you—at least not yet.

On June 9, local time, Anthropic just released two flagship models, Claude Fable 5 and Mythos 5, claiming to comprehensively lead the industry and being seen as key products paving the way for an IPO.

As it turns out, within less than 72 hours, citing national security, the U.S. Department of Commerce placed both models under export controls, forcing access restrictions.

What’s even harsher: it’s not only banning all individuals and institutions outside the U.S. from accessing them—foreign nationals inside the U.S., even including Anthropic’s own foreign employees, are also put on the prohibited list.

This is the first time in AI history that a commercial large model, deployed to hundreds of millions of people, is forcibly recalled by the U.S. government.

However, this isn’t the most ironic part.

1. A company that keeps shouting “safety first” got bitten back by its own “safety” persona

You may not know this, but for a long time, Anthropic’s favorite move has been to paint the government a picture of extreme AI risks—repeatedly emphasizing that “top-tier AI capabilities are directly tied to national security,” and actively calling for strict regulation.

And the fire has finally reached them.

According to a report from The Wall Street Journal, the trigger was Amazon CEO Andy Jassy briefing top White House officials: Amazon researchers found that Fable 5 could be induced to provide sensitive information that could be used for cyberattacks.

White House AI and crypto affairs lead David Sacks then disclosed on X: after the U.S. government discovered a jailbreak vulnerability, it demanded that Anthropic fix it or face being taken offline. Anthropic CEO Dario Amodei refused to fix it, and said in an official statement that the vulnerability was “not serious,” adding that “other companies’ models also have” similar issues.

Sacks blasted: “Anthropic has always emphasized safety first, but this time they prioritized maintaining consumer-grade model services.”

Isn’t it ironic? A company that constantly calls on others to put “safety first” turns around and says “the vulnerability isn’t serious” when it’s their own turn.

It makes me think of a frequently cited quote by Li Xiaolai—although the context is different, the principle is the same: some people urge you to follow the rules because they hope you won’t get in their way.

2. But the more critical question is: should regulation stop at the gate, or be “raised” after the fact?

This incident has split Silicon Valley into two paths.

The White House route (David Sacks): A pre-emptive ban. If risks are found, fix them or get out. If you don’t cooperate, I won’t let you in.

The Silicon Valley route (a16z Marc Andreessen): Post-event accountability. a16z co-founder Marc Andreessen publicly opposes AI regulation centered on the “precautionary principle.” He argues that letting people who don’t understand the technology set complex rules—using layered approvals and compliance costs to crush innovation—will ultimately only help big companies entrench their position and block newcomers.

But he also stresses that he doesn’t oppose all regulation. He supports rules that build market trust and ensure public safety—such as preventing AI voice forgery to carry out financial fraud, preventing deepfakes from interfering with elections, and ensuring consumers and businesses can use new technologies safely.

He offered an analogy an engineer would instantly understand: reasonable regulation is like highway guardrails or car brakes—it doesn’t slow the car down; it makes people dare to “drive fast.” In a car without brakes, nobody dares to step on the accelerator.

Which approach is more conducive to innovation?

3. I’ll state the conclusion directly: both paths are imperfect, but pre-emptive bans hide a “harvesting trap”

First, what’s wrong with the White House route: “opaque and unpredictable enforcement standards” are, in themselves, the biggest killers of innovation. Anthropic itself has warned that if this standard—“find a small vulnerability and recall the entire model”—applies across the industry, then all leading model suppliers won’t be able to release new models.

More realistically, companies with deep resources are more likely to pass reviews, while smaller companies can’t even reach the threshold. In the end, the mechanism will evolve into a “gatekeeper” system that protects vested interests.

Many people say Europe is behind in innovation, and one reason is overregulation. Andreessen put it bluntly: the culture of overregulation has made Europe relatively lag behind in recent years, and regulation shouldn’t become a moat that allows vested interests to raise entry barriers.

So is post-event accountability workable? Also not. Look at the recent subpoenas issued by multiple state attorneys general against OpenAI: the advertising business, user engagement, management of consumer and health data, services for minors and elderly groups, deep learning models… all are under investigation. If you wait to assign accountability only after “something happens,” user harm has already occurred, and the losses are irreversible.

To be frank, I like post-event accountability—because it leaves room for innovators to “try, make mistakes, and be tested.” But you can’t set the bottom line at the edge of a cliff without guardrails.

So my view is: what innovation needs isn’t “no regulation,” but a system of “low barriers and high accountability”—you can enter without getting blocked at the door, but if something goes wrong, you pay a huge price.

4. What does this have to do with you?

If you’re a Web3 founder or investor, you can already feel it—

After this wave of regulatory turmoil broke out, the crypto market reacted quickly. Bittensor (TAO) surged 23.9%, Venice Token rose 18%, and ICP climbed 9.8%. Traders almost reflexively shifted funds into the AI infrastructure sector.

The logic is simple: centralized AI could be shut down at any time → so why not go buy some “decentralized, censorship-resistant” AI infrastructure?

My assessment is that a pre-emptive ban means “possible shutdown at any time,” and in Web3 projects, any that involve centralized API calls or depend on a single AI provider have similar risks. If you built a DApp on the OpenAI API, and one day the government requires OpenAI to pause all foreign users from using certain features, you won’t even be able to keep your business running.

As for how regulation will evolve, the debate between these two approaches will continue for a long time. Don’t assume you’re safe just because you’re standing in the light—when the shadow falls on someone else, it’s only one step away from you.

“Innovation isn’t about nobody regulating it—it’s about the people regulating it truly understanding what you’re doing.”

No matter which path the U.S. government ultimately chooses, we need to recognize this: every “temporary restriction” is a blunt instrument that carves into startups and long-tail projects alike.

And the simplest thing you and I can do is to make our business structure as decentralized as possible, provide redundancy across multiple providers, and reduce the risk of being “neck-blocked” by a single regulatory node. It’s not that because you’re legal, others #我的Gate交易时刻 will let you operate safely.