特朗普向Anthropic提出不可能的要求

Gary Marcus:The Road to AI We Can Trust(RSS)·2026-06-18 02:05·69天前·Gary Marcus
AI 导读

特朗普要求Anthropic完成不可能的任务,暴露了生成式AI安全护栏的根本困境。早在2024年1月,Gary Marcus就指出任何护栏都难以在过于严格和过于宽松之间找到平衡。如今这一判断得到验证:基于next-token predictor的大语言模型本质上不适合安全控制。要么对LLM加以限制直至出现更好的技术,要么承受后果。问题并非Anthropic独有,而是整个生成式AI面临的挑战。

Gary Marcus:The Road to AI We Can Trust(RSS)
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特朗普向Anthropic提出不可能的要求

2026-06-18 02:05· 69天前· Gary Marcus
AI 导读

特朗普要求Anthropic完成不可能的任务,暴露了生成式AI安全护栏的根本困境。早在2024年1月,Gary Marcus就指出任何护栏都难以在过于严格和过于宽松之间找到平衡。如今这一判断得到验证:基于next-token predictor的大语言模型本质上不适合安全控制。要么对LLM加以限制直至出现更好的技术,要么承受后果。问题并非Anthropic独有,而是整个生成式AI面临的挑战。

Where do we go from here?

In January 2024, I warned that the politics and inadequacy of guardrails would become a central issue for our times.

WIRED@WIRED Trump administration officials tell WIRED that if Anthropic wants to rerelease Fable 5, it will need to ensure the model's guardrails can't be circumvented. Security experts say that can't be done. wired.com The White House Wants Anthropic to Block All Jailbreaks. That May Not Be Possible Image 4 5:05 PM · Jun 17, 2026 · 4.97K Views * * * 4 Replies · 3 Reposts · 15 Likes Where do we go from here? At least with respect to LLMs, the security experts are right. And the writing has been on the wall literally for years. As Katie Conrad and I wrote here in January 2024:

virtually any guardrail has to thread a needle between the Scylla of being too restrictive and Charybdis of being too permissive. None thus far have done this effectively.

That’s still true. Next-token predictors simply aren‘t built for safety.

Either we curtail LLMs until we find a better technology, or we live with consequences.

Importantly, this is not an Anthropic problem, it’s a Generative AI problem.

Discussion about this post

"Next-token predictors simply aren‘t built for safety."

And in particular, Next-Token Predictors don't have a moral compass. It's all just matrix multiplication. You can try to steer the tokens that are predicted, but given the right context, the model might say anything.

LLMs are a fatally flawed technology. They're going to say this tech is "too big to fail", as if it's a bank. We know how banks work. If a bank is failing, you pump in enough money and it works again.

We don't know how LLMs work. All we know is that the more money and compute we pump in, the more opaque their operation becomes. The failure is not one of logistics, it's one of logic, of epistemology. Language is something very different to thinking.

Ready for more?

来源:Gary Marcus:The Road to AI We Can Trust(RSS)· garymarcus.substack.com