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