Every Definition of Intelligence Is Wrong. Here's Why — Michael Bennett
Dr. Michael Timothy Bennett is a computer scientist who's deeply interested in understanding artificial intelligence, consciousness, and what it means to be alive. He's known for his provocative paper "What the F*** is Artificial Intelligence" which challenges conventional thinking about AI and intelligence. **SPONSOR MESSAGES*** Prolific: Quality data. From real people. For faster breakthroughs. https://prolific.com/mlst?utm_campaign=98404559-MLST&utm_source=youtube&utm_medium=podcast&utm_content=mb *** Michael takes us on a journey through some of the biggest questions in AI and consciousness. He starts by exploring what intelligence actually is - settling on the idea that it's about "adaptation with limited resources" (a definition from researcher Pei Wang that he particularly likes). The discussion ranges from technical AI concepts to philosophical questions about consciousness, with Michael offering fresh perspectives that challenge Silicon Valley's "just scale it up" approach to AI. He argues that true intelligence isn't just about having more parameters or data - it's about being able to adapt efficiently, like biological systems do. TOC: 1. Introduction & Paper Overview [00:00:00] 2. Definitions of Intelligence [00:02:54] 3. Formal Models (AIXI, Active Inference) [00:07:06] 4. Causality, Abstraction & Embodiment [00:10:45] 5. Computational Dualism & Mortal Computation [00:25:51] 6. Modern AI, AGI Progress & Benchmarks [00:31:30] 7. Hybrid AI Approaches [00:35:00] 8. Consciousness & The Hard Problem [00:39:35] 9. The Diverse Intelligences Summer Institute (DISI) [00:53:20] 10. Living Systems & Self-Organization [00:54:17] 11. Closing Thoughts [01:04:24] Michaels socials: https://michaeltimothybennett.com/ https://x.com/MiTiBennett Transcript: https://app.rescript.info/public/share/4jSKbcM77Sf6Zn-Ms4hda7C4krRrMcQt0qwYqiqPTPI References: Bennett, M.T. "What the F*** is Artificial Intelligence" https://arxiv.org/abs/2503.23923 Bennett, M.T. "Are Biological Systems More Intelligent Than Artificial Intelligence?" https://arxiv.org/abs/2405.02325 Bennett, M.T. PhD Thesis "How To Build Conscious Machines" https://osf.io/preprints/thesiscommons/wehmg_v1 Legg, S. & Hutter, M. (2007). "Universal Intelligence: A Definition of Machine Intelligence" Wang, P. "Defining Artificial Intelligence" - on non-axiomatic reasoning systems (NARS) Chollet, F. (2019). "On the Measure of Intelligence" - introduces the ARC benchmark and developer-aware generalization Hutter, M. (2005). "Universal Artificial Intelligence: Sequential Decisions Based on Algorithmic Probability" Chalmers, D. "The Hard Problem of Consciousness" Descartes, R. - Cartesian dualism and the pineal gland theory (historical context) Friston, K. - Free Energy Principle and Active Inference framework Levin, M. - Work on collective intelligence, cancer as information isolation, and "mind blindness" Hinton, G. (2022). "The Forward-Forward Algorithm" - introduces mortal computation concept Alexander Ororbia & Friston - Formal treatment of mortal computation Sutton, R. "The Bitter Lesson" - on search and learning in AI Pearl, J. "The Book of Why" - causal inference and reasoning Alternative AGI Approaches Wang, P. - NARS (Non-Axiomatic Reasoning System) Goertzel, B. - Hyperon system and modular AGI architectures Benchmarks & Evaluation Hendrycks, D. - Humanities Last Exam benchmark (mentioned re: saturation) Filmed at: Diverse Intelligences Summer Institute (DISI) https://disi.org/
