Dwarkesh Patel
Hosts the Dwarkesh Podcast, a long-form interview show on AI progress, timelines, and the people building frontier models, along with economists and historians.
“People inside the AI labs claim to have evidence that makes them more worried and they are not allowed to talk about it. … I think it's a terrible state of affairs. If they really believe this, if they think that we're in a situation where we're less than a year away from automating AI research and radically speeding it up, they should make this evidence public.”
Interesting Times · Geopolitics & World Affairs · October 2026
Asked about models the labs haven't released, Patel describes a recent conversation with someone at Anthropic who expected AI to match humans at AI research within nine months, but couldn't say why. He worries the labs will stop releasing their most capable models as they automate their own research.
Transcript
As in the ones internal to the company. Well,
…it would cost too much to release them or they're not safe yet. But the public doesn't see them. You're an insider. Whether or not you see them, you hear about them, you know something about them. How should we think about unreleased models and how does that change our picture of what's going on?
…example, just the other day, maybe two days ago, I was talking to somebody at Anthropic and they were like, look, I expect AIs to be humans at AI research within nine months. And I'm like, why do you believe that? Well, they're like, it's not just vibes, but I have information on the inside. I'm like, what is it? Is it a new model? Is it some evaluation you ran? It's like, I can't talk about it. I think it's a terrible state of affairs. If they really believe this, if they think that we're in a situation where we're less than a year away from automating AI research and radically speeding it up, they should make this evidence public. I especially worry about the following scenario where as AIs get better and better at making AI progress faster and automating it, they will be inclined not to keep releasing models that are even close to their smartest models externally. Because then if they release this externally, it would help others make smart models. And it just not, it's just kind of a schlep to release models externally…
the gap between what they know and what we know is just would get bigger and bigger under that scenario. So we'd end up more in the dark, more surprised when things happen. It would be harder for regulators, policymakers, members of Congress, everyone.
Yes. I also think an important part of why it's important that companies externally deploy every model that they're releasing internally or using internally for RD is we just don't know if these models are actually aligned. And the only way to find out, you know, they realize when they're in a test…
So this notion of a pause in AI systems, that the companies, at least for some period of time, should stop releasing new models altogether. What do you think of that idea? It makes things better or makes things worse.
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