Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. Please support this podcast by checking out our sponsors:
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EPISODE LINKS:
Stephen’s Twitter: https://twitter.com/stephen_wolfram
Stephen’s Blog: https://writings.stephenwolfram.com
Wolfram Physics Project: https://www.wolframphysics.org
A New Kind of Science (book): https://amzn.to/30XoEun
Fundamental Theory of Physics (book): https://amzn.to/30XbAoT
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OUTLINE:
Here’s the timestamps for the episode. On some podcast players you should be able to click the timestamp to jump to that time.
(00:00) – Introduction
(07:50) – What is complexity
(20:51) – Randomness in the universe
(25:12) – The Wolfram Physics Project
(37:14) – Space and time are discrete
(49:19) – Quantum mechanics and hypergraphs
(58:33) – What is intelligence
(1:09:16) – Computational equivalence
(1:17:36) – What it is like to be a cellular automata
(1:32:00) – Making prediction vs explanations
(1:45:20) – Why does the universe exist
(1:51:01) – The universe and rulial space
(1:59:44) – Does an atom have consciousness
(2:10:10) – Why does our universe exist
(2:18:41) – What is outside the ruliad
(2:29:15) – Automated proof systems
(2:45:10) – Multicomputation for biology
(3:03:41) – Cardano NFT collaboration with Wolfram Alpha
(3:10:41) – Global theory of economics
Gustav Soderstrom: Spotify
Chris Urmson: Self-Driving Cars at Aurora, Google, CMU, and DARPA
Kai-Fu Lee: AI Superpowers – China and Silicon Valley
Sean Carroll: The Nature of the Universe, Life, and Intelligence
Jeff Hawkins: Thousand Brains Theory of Intelligence
Rosalind Picard: Affective Computing, Emotion, Privacy, and Health
Gavin Miller: Adobe Research
Rajat Monga: TensorFlow
Chris Lattner: Compilers, LLVM, Swift, TPU, and ML Accelerators
Oriol Vinyals: DeepMind AlphaStar, StarCraft, Language, and Sequences
Ian Goodfellow: Generative Adversarial Networks (GANs)
Elon Musk: Tesla Autopilot
Greg Brockman: OpenAI and AGI
Eric Weinstein: Revolutionary Ideas in Science, Math, and Society
Leslie Kaelbling: Reinforcement Learning, Planning, and Robotics
Kyle Vogt: Cruise Automation
Tomaso Poggio: Brains, Minds, and Machines
Tuomas Sandholm: Poker and Game Theory
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs
Pieter Abbeel: Deep Reinforcement Learning
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