Recursive Self-Improvement and the Road to Superintelligence

So I want to mention what has been coming up more and more actually over the last, not just this week, but a couple of weeks, but in a cadence this week that has been extraordinary to me, which is super intelligence.

And many of you who listen to this podcast regularly know that my book on super intelligence came out relatively recently of another mind, which you can get at Barnes and Nobles or at, uh, Amazon.

But it's about superintelligence and navigating a new social contract with superintelligent AI.

And so I co-authored that with Amy Zimmerman.

And it happens to actually now be fitting right into the conversation that is all over the place about superintelligence.

In the last, really in the last couple of weeks, there have been articles, interviews with folks.

There have actually been a couple of interviews with people from Anthropic, some current and former security folks, safety folks, and scientists, engineers, talking about superintelligence and what it could mean.

And I watched.

One of those a couple of days ago, two days ago, which was done by a guy named Jeffrey Ladish, L-A-D-I-S-H, which I recommend people watch and you can get it on YouTube.

And the debate really has moved on from will superintelligence ever be possible to when? And people are talking about as early as 2027.

I'm not sure I'm there yet.

Although, as we were saying, there's kind of a proto-superintelligence already to 2030.

And what's it going to look like? And so these are all things that people are talking about.

And one of the debates which has come up in the past week with some of the new capabilities of the newest models that we talked about some during our last episode.

is AI actually improving itself? And that when AI can really improve itself in a robust way, a 360-degree way, manner, that we're going to potentially have a new jump in intelligence and possibly the jump that we are expecting into superintelligence.

And there is something called recursive self-improvement, which is a kind of self-improvement that AI could itself engage in And when it has improved itself, it goes back.

That's the recursive part.

And it improves itself again.

So it's sort of a loop, if you will.

And that's the recursive part.

Recursive self-improvement, this feedback loop.

And AI would then be able to, as we know, it can already write code, but it would write the code.

It would test the code, which it can already do.

It would develop new capabilities potentially.

It could even potentially develop new architectures and port over the code into new architectures, discover new efficiencies, propose and implement successor systems, all kinds of things.