Dario Amodei

Like, you know, in the most extreme world, we make this autonomous AI that, you know, the robots enslave us or whatever, right? I mean, that's half joking, but you know, that is the most extreme thing that could happen. Then it doesn't matter which company was ahead. If instead you create a race to the top where people are competing to engage in good practices, right?

then at the end of the day, it doesn't matter who ends up winning. It doesn't even matter who started the race to the top. The point isn't to be virtuous. The point is to get the system into a better equilibrium than it was before. And individual companies can play some role in doing this. Individual companies can help to start it, can help to accelerate it.

And frankly, I think individuals at other companies have done this as well, right? The individuals that when we put out an RSP, react by pushing harder to get something similar done at other companies. Sometimes other companies do something that's like, we're like, oh, it's a good practice. We think that's good. We should adopt it too. The only difference is, you know, I think we are

We try to be more forward-leaning. We try and adopt more of these practices first and adopt them more quickly when others invent them. But I think this dynamic is what we should be pointing at. And I think it abstracts away the question of which company is winning, who trusts who. I think all these questions of drama are important. are profoundly uninteresting.

And the thing that matters is the ecosystem that we all operate in and how to make that ecosystem better because that constrains all the players.

Look, I'm sure we've made plenty of mistakes along the way. The perfect organization doesn't exist. It has to deal with the imperfection of a thousand employees. It has to deal with the imperfection of our leaders, including me. It has to deal with the imperfection of the people we've put to oversee the imperfection of the leaders, like the board and the long-term benefit trust.

It's all a set of imperfect people trying to aim imperfectly at some ideal that will never perfectly be achieved. Um, that's what you sign up for. That's what it will always be. But, uh, uh, imperfect doesn't mean you just give up. There's better and there's worse. And hopefully, hopefully we can begin to build.

We can do well enough that we can begin to build some practices that the whole industry engages in. And then, you know, my guess is that multiple of these companies will be successful. Anthropic will be successful. These other companies, like ones I've been at the past will also be successful because And some will be more successful than others.

That's less important than, again, that we align the incentives of the industry. And that happens partly through the race to the top, partly through things like RSP, partly through, again, selected surgical regulation.

This is one of these statements that's like more true every, every, every month. Every month I see this statement is more true than I did the month before. So if I were to do a thought experiment, let's say you have a team of 100 people that are super smart, motivated and aligned with the mission, and that's your company.

Or you can have a team of a thousand people where 200 people are super smart, super aligned with the mission. And then like 800 people are, let's just say you pick 800 like random big tech employees. Which would you rather have? The talent mass is greater in the group of 1,000 people. You have even a larger number of incredibly talented, incredibly aligned, incredibly smart people.

But the issue is just that if... Every time someone super talented looks around, they see someone else super talented and super dedicated. That sets the tone for everything, right? That sets the tone for everyone is super inspired to work at the same place. Everyone trusts everyone else. If you have a thousand or 10,000 people and things have really regressed, right?

You are not able to do selection and you're choosing random people. What happens is then you need to put a lot of processes and a lot of guardrails in place, right? just because people don't fully trust each other. You have to adjudicate political battles. Like there are so many things that slow down the org's ability to operate. And so we're nearly a thousand people.

And, you know, we've, we've, we've tried to make it so that as large a fraction of those thousand people as possible are like, super talented, super skilled. It's one of the reasons we've slowed down hiring a lot in the last few months. We grew from 300 to 800, I believe, I think in the first seven, eight months of the year. And now we've slowed down.

We're at like, you know, the last three months we went from 800 to 900, 950, something like that. Don't quote me on the exact numbers, but I think there's an inflection point around a thousand and we want to be much more careful how we grow. Early on, and now as well, we've hired a lot of physicists. Theoretical physicists can learn things really fast.

Even more recently, as we've continued to hire that, we've really had a high bar on both the research side and the software engineering side, have hired a lot of senior people, including folks who used to be at other companies in this space. And we've just continued to be very selective.

It's very easy to go from a hundred to a thousand and a thousand to 10,000 without paying attention to making sure everyone has a unified purpose. It's so powerful. If your company consists of a lot of different fiefdoms that all want to do their own thing, they're all optimizing for their own thing. It's very hard to get anything done.

But if everyone sees the broader purpose of the company, if there's trust and there's dedication to doing the right thing, that is a superpower. That in itself, I think, can overcome almost every other disadvantage.

Yeah. I think the number one quality, especially on the research side, but really both, is open-mindedness. Sounds easy to be open-minded, right? You're just like, oh, I'm open to anything. But if I think about my own early history in the scaling hypothesis... Um, I was seeing the same data others were seeing.

I don't think I was like a better programmer or better at coming up with research ideas than any of the hundreds of people that I worked with. Um, in some ways, in some ways I was worse. Um, uh, you know, like I've, I've never liked, you know, precise programming of like, you know, finding the bug, writing the GPU kernels.