Sam Altman & Brad Lightcap: Which Companies Will Be Steamrolled by OpenAI? | E1140

There are two strategies to build on AI right now. There's one strategy which is assume the model is not going to get better, and then you kind of, like build all these little things on top of it. There's another strategy which is build assuming that OpenAI is going to stay on the same rate of trajectory, and the models are going to keep getting better at the same pace. It would seem to me that 95% of the world should be betting on the latter category. But a lot of the startups have been built in the former category. When we just do our fundamental job because we like have a mission, we're going to steamroll you.

Ready to go? Guys, I'm so excited for this. I've wanted to do this for a long time. Also, this is the first time that you've done an interview together.

I think it is, yeah.

I think that's right.

This is going to be the most unique interview then that you've done together. So this is very exciting. I want to start, I spoke to many mutual friends before and they said, "We've got to start with context." Sam, what gave you the conviction to- to do this seven years ago?

I think there were two things that seemed... Well, I've been interested in AI since I was a little kid. Um, but, and I studied it at college and nothing was working. But when we started, there were two things that seemed really important. One, deep learning seemed to actually legitimately be working. And two, it got better with scale. We didn't know how predictably it got better with scale at the time, but it was clear that like bigger was better. And that seemed like a remarkable set of things. And the confusing thing to us at the time was like, "Why does everybody else not see this and why is e- everybody else not jumping on it?" But they weren't. And so we wanted to do it.

Can I ask, when there were those moments of doubt from everyone else, which there were across those years, what gave you the conviction to stick at it when bluntly very few others had that same confidence?

It just seemed to us like it was going to work and we kept making progress. Like it- we- it was not- it was- I wouldn't call- I would not call it blind faith, although there is some amount of you just, you know, you got to believe you can do a hard thing. But it- it felt really important to us t- to do this, that if we could do it, it would be, you know, hugely meaningful, um, to the world in some way and that it might work. Like we had an attack vector we believed in, we had, ah, and then we had continued data that the approach was working. Of course the specifics took a long time to figure out. Uh, you know, we did not start off doing language models obviously. We kind of knew that if we could keep doing things that we previously thought were impossible, that was somehow a good sign for progress. And we had this like fundamental conviction on the approach and the attack vector at a very high level for a very long time. And the details took a long time to work out and many brilliant discoveries by our colleagues. There was never any doubt that AI would be a big deal if we could do it. So that's helpful. Like it's going to be really valuable. Um, the approach we got successively more confident in, although it- it did take some wandering in the jungle for a while, or the desert, whatever that phrase is.