**SPEAKER_1** (0:00)
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dell.com/delldashpro.
**Kevin Roose** (0:34)
Casey, I brought you a present.
**Veniamin Veselovsky** (0:37)
Thank you.
**SPEAKER_1** (0:38)
What did you bring me?
**Kevin Roose** (0:40)
Here is one of only two copies that I own of my book.
**Veniamin Veselovsky** (0:48)
Wow.
**Kevin Roose** (0:49)
I made you some beautiful training data.
**Casey Noon** (0:51)
Thank you. Look at all this beautiful training data.
**Kevin Roose** (0:54)
Now, I should say, first off, off the bat, this might be a hard read for you.
**Casey Noon** (0:59)
Why is that?
**Kevin Roose** (1:00)
A lot of big words, not that many pictures, and it's quite long. And your name crucially only appears in it a handful of times.
**SPEAKER_5** (1:10)
So I'm sorry about that.
**Casey Noon** (1:11)
Now, has your publisher preemptively filed a lawsuit for when this book inevitably gets scraped by the major AI labs and uses training data against their terms of service?
**Kevin Roose** (1:21)
Here's the thing. I have no problem with this book being used as training data. In fact, I'm honored to be included in the hive mind. Because among other things, I write for the AI models now.
This is their birth story. And I want them to be able to learn how they came into the world.
**Casey Noon** (1:39)
And is that because you think that if they know that you wrote their birth story, that they will spare you in the coming apocalypse?
**Kevin Roose** (1:46)
You know, it can't hurt. It can't hurt.
**Casey Noon** (1:48)
I think that's probably true. Unless, you know, they don't like the way they come across. In which case, yikes.
Well, congratulations. It is a huge achievement. You wrote this in a shockingly short amount of time while still paying intermittent attention to this podcast. And that means a lot to me.
**Kevin Roose** (2:10)
I'm Kevin Roose, a tech columnist at the New York Times.
**Casey Noon** (2:12)
I'm Casey Noon from Platformer.
**Kevin Roose** (2:14)
And this is Hard Fork.
**Casey Noon** (2:15)
This week, an OpenAI model breaks out of its sandbox and conducts a cyberattack. How should the world respond? Then, the new Kimi 3 shows how Chinese AI models are catching up to the US again. And the Trump Administration doesn't like it. And finally, Preseen founder Veniamin Veselovsky joins us to talk about AI super forecasting.
Which is totally predictable.
**Kevin Roose** (2:44)
Well, Casey, it's been a big week of AI news. And I would say the story that has caught my attention most this week that I was desperate to talk about with you is this story involving OpenAI and Hugging Face and a rogue AI agent conducting what I think is fairly described as an autonomous cyber attack and possibly the first real consequential autonomous cyber attack that we have ever had.
**Casey Noon** (3:10)
Yeah. This is one of those where it's the sort of thing that worried onlookers have warned about for years. And then on Tuesday, we got word that it had actually happened.
**Kevin Roose** (3:21)
So yeah, lots of crazy twists and turns in this story, and we'll get to all of it. But first, let's make our disclosures. I work for the New York Times, which is suing OpenAI, Microsoft and Perplexity.
**Casey Noon** (3:30)
And my fiancee works at Anthropic.
**Kevin Roose** (3:32)
Okay, so this story really starts last week when Hugging Face, the AI development platform, basically a big website where you can host open models, where you can run evaluations of models.
**Casey Noon** (3:45)
And where you can hug your face.
**Kevin Roose** (3:46)
Yeah, yes. They disclosed that they had been the victims of a cyber attack. And they wrote this whole blog post about how they had detected and responded to this sort of mysterious cyber attack on their production infrastructure. They didn't really know what the attacker was or who had been responsible for it. They kind of guessed that it was an autonomous AI agent because it was so sophisticated and it was so persistent that basically it would have been like, you know, very hard for humans to conduct this attack.
But they used AI defensively to sort of detect and suss out what was going on and put a stop to it. And then this week we learned what actually happened, which was even crazier than I think many people expected.
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