Dario Amodei

These latter two threats are inherently contradictory.

One labels us a security risk.

The other labels Claude as essential to national security.

Regardless, these threats do not change our position.

I prefer Demis's timeline.

I wish we had five to 10 years, you know, so it's possible he's just right and I'm just wrong, but assume I'm right and it can be done in one to two years.

Why can't we slow down to Demis's timeline?

Well, you could just slow down.

Well, no, but the reason we can't do that is because we have...

geopolitical adversaries building the same technology at a similar pace, it's very hard to have an enforceable agreement where they slow down and we slow down.

And so if we can just

If we can just not sell the chips, then this isn't a question of competition between the US and China.

This is a question of competition between me and Demis, which I'm very confident that we can work out.

That'll concede.

So I can only describe it as it relates to kind of my own experience, but I've been in the AI field for about 10 years. And it was something I noticed very early on. So I first joined the AI world when I was working at Baidu with Andrew Ng in late 2014, which is almost exactly 10 years ago now. And the first thing we worked on was speech recognition systems.

So I can only describe it as it relates to kind of my own experience, but I've been in the AI field for about 10 years. And it was something I noticed very early on. So I first joined the AI world when I was working at Baidu with Andrew Ng in late 2014, which is almost exactly 10 years ago now. And the first thing we worked on was speech recognition systems.

So I can only describe it as it relates to kind of my own experience, but I've been in the AI field for about 10 years. And it was something I noticed very early on. So I first joined the AI world when I was working at Baidu with Andrew Ng in late 2014, which is almost exactly 10 years ago now. And the first thing we worked on was speech recognition systems.

And in those days, I think deep learning was a new thing. It had made lots of progress, but everyone was always saying, we don't have the algorithms we need to succeed. You know, we're not, we're only matching a tiny, tiny fraction. There's so much we need to kind of discover algorithmically. We haven't found the picture of how to match the human brain.

And in those days, I think deep learning was a new thing. It had made lots of progress, but everyone was always saying, we don't have the algorithms we need to succeed. You know, we're not, we're only matching a tiny, tiny fraction. There's so much we need to kind of discover algorithmically. We haven't found the picture of how to match the human brain.

And in those days, I think deep learning was a new thing. It had made lots of progress, but everyone was always saying, we don't have the algorithms we need to succeed. You know, we're not, we're only matching a tiny, tiny fraction. There's so much we need to kind of discover algorithmically. We haven't found the picture of how to match the human brain.