John Siracusa

speaker
26,399 appearances 43 recordings 1 series first heard Aug 2024 last heard 10 Sep

John Siracusa’s voice in public audio — every appearance, attributed to the second.

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recordings per month · last 12 months
5 · Jun OctJan 26AprJulnow

Recordings per month over the last 12 months — 27 in all, peaking in Jun 2026 with 5.

Appearances

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Like why, you know, again with the image stuff, it's like, oh, we want to do this to be nice and so people know when things are AI generated and blah blah blah. podcast-host
And yeah, it's not a security thing. podcast-host
We're not fooling anybody, because obviously anyone can just remove the watermark, but it's like we're trying to do this to be nice. podcast-host
There is one other angle that I hear everybody talking about with this, and I have no idea. podcast-host
if this is in in anthropics mind at all. podcast-host
I don't know if it, you know, it's just a happy accident because the EU regulation, I think, doesn't say anything about this. podcast-host
But the angle is, um podcast-host
First, the premise that when AI models are training on stuff, that they don't do well if they are trained on like their own output, like uh or the output of other models, right? podcast-host
So they want to train on stuff that was not AI generated. podcast-host
If you train an AI on AI generated output, it just kind of goes into a degenerative loop and uh things get worse and worse. podcast-host
So I've heard. podcast-host
I don't know the foundation of that, but that's what I've heard. podcast-host
And so podcast-host
The idea here is podcast-host
Why would Claude, why would Anthropic do this besides obviously complying with the EU regulation? podcast-host
Like Claude is doing it, um Anthropic's doing it worldwide, which is just a simplification, I think, which is what Apple should do in response to EU regulations. podcast-host
But anyway, they're saying, Oh, they're doing it. podcast-host
So they won't accidentally train their next model on stuff that was generated by any of their current models because they're when their models go out there, they'll be like, oh, yum, yum, training data, munch, munch, munch, steal everybody's data. podcast-host
Um oh wait. podcast-host
Our watermark, our watermark detector has detected that this data was generated by us. podcast-host
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