Show notes
Episode 3: Extropic is building a new kind of computer – not classical bits, nor quantum qubits, but a secret, more complex third thing. They call it a Thermodynamic Computer, and it might be many orders of magnitude more powerful than even the most powerful supercomputers today. Check out their “litepaper” to learn more: https://www.extropic.ai/future.======(00:00) - Intro(00:41) - Guillaume's Background(02:40) - Trevor's Background(04:02) - What is Extropic Building? High-Level Explanation(07:07) - Frustrations with Quantum Computing and Noise(10:08) - Scaling Digital Computers and Thermal Noise Challenges(13:20) - How Digital Computers Run Sampling Algorithms Inefficiently(17:27) - Limitations of Gaussian Distributions in ML(20:12) - Why GPUs are Good at Deep Learning but Not Sampling(23:05) - Extropic's Approach: Harnessing Noise with Thermodynamic Computers(28:37) - Bounding the Noise: Not Too Noisy, Not Too Pristine(31:10) - How Thermodynamic Computers Work: Inputs, Parameters, Outputs(37:14) - No Quantum Coherence in Thermodynamic Computers(41:37) - Gaining Confidence in the Idea Over Time(44:49) - Using Superconductors and Scaling to Silicon(47:53) - Thermodynamic Computing vs Neuromorphic Computing(50:51) - Disrupting Computing and AI from First Principles(52:52) - Early Applications in Low Data, Probabilistic Domains(54:49) - Vast Potential for New Devices and Algorithms in AI's Early Days(57:22) - Building the Next S-Curve to Extend Moore's Law for AI(59:34) - The Meaning and Purpose Behind Extropic's Mission(01:04:54) - Call for Talented Builders to Join Extropic(01:09:34) - Putting Ideas Out There and Creating Value for the Universe(01:11:35) - Conclusion and Wrap-Up======Links:Christian Keil – https://twitter.com/pronounced_kyleGuillaume Verd - https://twitter.com/GillVerdBeff Jezos - https://twitter.com/BasedBeffJezosTrevor McCourt - https://twitter.com/trevormccrt1First Principles:Gaussian Distribution: https://en.wikipedia.org/wiki/Normal_distributionEnergy-Based Models: https://en.wikipedia.org/wiki/Energy-based_modelShannon’s Theorem: https://en.wikipedia.org/wiki/Noisy-channel_coding_theorem======Production and marketing by The Deep View (https://thedeepview.co). For inquiries about sponsoring the podcast, email [email protected]======Checkout the video version here → http://tinyurl.com/4fh497n9🔔 Follow to stay updated with new uploads