Dr. Maxwell Ramstead hosts Guillaume Verdon -- physicist, founder of Extropic, and the mind behind the Beff Jezos persona and the Effective Accelerationism movement -- for a conversation that bridges thermodynamics, computing hardware, and civilizational philosophy. Verdon traces his path from childhood fascination with theories of everything through theoretical physics at the Perimeter Institute, quantum computing at Google, and the founding of Extropic. The core technical insight: instead of fighting thermal noise at enormous energetic cost (as quantum computers do), thermodynamic computing harnesses it. Extropic's chips use the natural stochastic physics of electrons to accelerate Markov chain Monte Carlo sampling -- the same class of algorithms that underpin diffusion models, energy-based models, and much of modern probabilistic ML. The numbers are striking. Current wafer-scale AI systems consume 20+ kilowatts. A thermodynamic wafer with 1.5 billion p-bits and 20 billion parameters would run on 20 watts -- roughly what the human brain uses. Verdon argues this is not a coincidence: the brain is literally a thermodynamic computer operating near the Landauer limit, and Extropic is building silicon that works on the same principles. The second half turns to philosophy. Verdon derives Effective Accelerationism directly from stochastic thermodynamics: thermodynamic selection pressure favors systems that capture and dissipate more free energy, so growth is not just desirable but physically inevitable. He and Ramstead explore hyperstition through the lens of active inference, the geopolitical stakes of the US-China technology race, and why Verdon views deceleration as a form of psychological warfare against Western competitiveness. Recorded with Maxwell Ramstead hosting in place of Tim Scarfe. ***SPONSOR MESSAGE*** Google Gemini 2.5 Flash is a state-of-the-art language model in the Gemini app. Sign up at https://gemini.google.com *** --- TIMESTAMPS: 00:00:00 Intro Montage & Sponsor 00:02:21 From Theories of Everything to Thermodynamic Computing 00:08:41 The Failure of Reductionism & Physics-Inspired AI 00:17:15 From Quantum to Thermodynamic Computing 00:23:56 How Thermodynamic Computers Actually Work 00:31:15 Moore's Wall & The Brain as Proof of Concept 00:40:00 The Computing Stack of the Future 00:48:23 Why Current AI Will Cook Us to Death 00:50:38 Effective Accelerationism: The Philosophy of Beff Jezos 01:00:00 Hyperstition, Geopolitics & Avoiding Catastrophe 01:16:00 Closing: The Future of Extropic & Getting Involved --- REFERENCES: paper: [00:04:40] It From Bit https://cqi.inf.usi.ch/qic/wheeler.pdf [00:06:15] Renormalization Group Theory https://www.damtp.cam.ac.uk/user/dbs26/AQFT/Wilsonchap.pdf [00:23:00] Metropolis-Hastings Algorithm https://arxiv.org/abs/1504.01896 [00:40:00] Deep Information Bottleneck and Renormalization https://arxiv.org/abs/1907.07331 [00:40:00] Energy-Based Models (EBMs) https://www.researchgate.net/publication/200744586_A_tutorial_on_energy-based_learning [01:03:00] Free Energy Principle and Active Inference https://www.nature.com/articles/nrn2787 concept: [00:05:30] Holographic Principle (AdS/CFT Correspondence) https://en.wikipedia.org/wiki/Holographic_principle [00:20:00] Markov Chain Monte Carlo (MCMC) https://en.wikipedia.org/wiki/Markov_chain_Monte_Carlo [00:21:10] Maxwell's Demon and Information Theory https://plato.stanford.edu/entries/information-entropy/ [00:29:45] Landauer's Principle https://en.wikipedia.org/wiki/Landauer%27s_principle [01:11:40] Fisher's Fundamental Theorem of Natural Selection https://en.wikipedia.org/wiki/Fisher%27s_fundamental_theorem_of_natural_selection --- LINKS: Full Transcript: https://app.rescript.info/share/21936dd6830231c0194e8b2908f4d963 Download PDF transcript: https://app.rescript.info/api/public/sessions/a34e6a9a2ed827b9/pdf