Dr. Jürgen Schmidhuber, a renowned scientist and AI researcher widely regarded as one of the pioneers in the field, originated key ideas behind today's transformers, LSTMs, and recursive self-improvement through his lab's work. He argues that true AGI remains bottlenecked by physical hardware, that today's AI data center investments are headed for a correction as open-source keeps pace with closed labs, and that the path to general intelligence runs through artificial curiosity and self-generated experimentation rather than internet data. He closes by reconsidering mainstream AI safety arguments and offers a sweeping vision of self-replicating robot societies eventually colonizing the solar system.

(0:00) Intro

(1:24) How Close Is Superhuman AI?

(2:27) Why ChatGPT Didn't Surprise Him

(3:21) The Path to Recursive Self-Improvement

(9:01) Will AI Takeoff Feel Sudden?

(11:02) Intelligence Means Efficiency

(12:32) Advice for Labs: Beyond Human-Biased Data

(17:10) Artificial Curiosity and the Theory of Fun

(21:33) When Do We Get the AI Scientist?

(24:07) AI Chemistry, MOFs, and Carbon Capture

(25:04) Robotics Reality Check

(28:23) The Data Center Bet: Overbuilt?

(31:48) Open Source vs. Closed Labs

(34:25) Does Being First to RSI Create a Moat?

(38:06) AI Safety and Alignment Skepticism

(43:44) Quickfire

With your host:

@jacobeffron

- Managing Director at Redpoint