I spoke with him on Zoom after the launch, digging into Recursive’s unique technical approach and why he doesn’t think of this new project as a neolab, the informal term for a new generation of AI startups that prioritize research over building products.

We hear a lot about recursion these days! It feels like a very common goal across different labs. What do you see as your unique approach?

Our unique approach is to use open-endedness to get to recursive self-improvement, which no one has yet achieved. It’s an elusive goal for a lot of people. A lot of people already assume it happens when you just do auto-research. You know, you can take AI and ask it to make some other thing better, which could be a machine learning system, or just a letter that you write, or, you know, whatever it might be, right? But that’s not recursive self-improvement. That’s just improvement.

Our main focus is to build truly recursive, self-improving superintelligence at scale, which means that the entire process of ideation, implementation, and validation of research ideas would be automatic.