Nathan Labenz: evaluation

Transcript context

…I am a little more sympathetic, I think, off the top to the argument that there was some massive reappropriation of human knowledge that is upstream of all AI. And you could say that's not distillation. Sure. You could say they the American companies spent a lot more than the Chinese companies are having to spend. I think that's also undeniably true. But if I'm just kinda what feels just and fair? I'm especially because we're blocking them from using Claude. Right? We're not it's not like we're saying, hey. You can buy all the Claude you want. Right? So we've said we've got clad. The the the makers of clad have advocated strongly for chip restrictions, and they also try to refuse to sell their model into China in the first place. And the whole premise of Claude or the whole existence of Claude is based on the idea that we hovered up hovered up all this human knowledge in every form we could find it from digital, and you gotta believe that includes the whole Chinese digitized heritage. Now we're, like, sucking in the books, which I don't care about the fact that some books get destroyed in this process, but this wasn't something that everybody's consented to. And so it does feel a little strange to me given all of those fact patterns that we would then draw the line and say, okay. Like, it's anthropics consent. That's the consent that really matters. Now I think they should be permitted to do business with who they wanna do business with. And if they wanna put in measures to try to prevent distillation, I think that's their prerogative. But I'm, like, not at all convinced that it should be the state's job to come in and engage in sort of statecraft to try to punish or prevent this distillation. To me, it's kinda I don't know. Information wants to be free. Knowledge tends to diffuse. It's not like Anthropic has a super or any AI company has, like, a super moral high ground in terms of I didn't get my check for my share of the training data, and they're getting paid for the distillation queries too, which whenever they don't wanna be paid, so it's probably beside the point. But I don't know. I'm not I don't know. I don't find my I find myself a bit on the side of the underdog Chinese here where it's like, man, you've got kind of a deck stand stacked against you and get some knowledge where you can get it. What's wrong with that perspective? I think we do want the the deck stacked against China. We don't want China to win the race to ASI. I I'm not a lawyer, so I won't opine on the exact legal path that you may take to to make your terms of service in full. So I I'll just observe that, and I say that as someone who used to work at Uber. It's extremely hard to bring justice through the judiciary against Chinese companies. Almost impossible. So not a lawyer. I don't understand the technicalities here, but I'll just observe and start with that. And it may take a very long time, and by then, a lot of damage is done. And then I'll also observe, like, yes, companies are training on all of these corpus that is available to everyone. That is an an even playing field. The problem is that once you've done that at at great expense, it does cost them billions of dollars. If you can if you can and you and you create that artifact out of this training dataset, which is called the model. Now other people can turn around, and and instead of doing this, which cost billions of dollars, they turn to this, which cost a lot less than that, and they copy you and they catch up with you. If you do that, you kill innovation. And that's that's it's nothing new. It's just called IP and patent law. It's exactly what humans do. Right? It's like you as a human. You're like a researcher. You you think for, like, decades. You do all of that work because you're lot of money in r and d. You come up with an idea which is much smaller in tokens and much more precious and much cheaper to steal as is than, like, all the corpus of stuff that you trained on, how do you protect that idea in order to recoup your investment, in order to produce it? It's called a patent. It's called IP. Right? It's nothing new. If you apply to the same standard you're applying now to, for example, the pharma industry, you will have very cheap drugs, which is awesome, and you would have no new drug ever. You would completely destroy innovation in the pharma industry. And I think this is why you're finding all of these people support open models because people like free stuff. And it's it's you can't really measure the the future innovation that you don't get as a result of that. All you see is you get free models. You know? And look. I'm one of them. You know? So I'm I'm I'm speaking against my interests here. Right? Like, my company is dependent economically on those, like, very, very, very cheap models. But I'm also in in a coordination problem right now because, like, I cannot not adopt these models while the models are out there because my competitors are going to do it. So I have to adopt them if they're out there. I wish they will forbidden across the board so that we would like like the four reasons I invoked earlier. Like, protect our our like, champions, not have the CCP, like, influence the country or run parts of the country and and have, a fair level field of of competition.…

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