Lex Fridman

Jim Keller: Abstraction Layers from the Atom to the Data Center | AI Podcast Clips

Complete Statistical Theory of Learning (Vladimir Vapnik) | MIT Deep Learning Series

Vladimir Vapnik: Predicates, Invariants, and the Essence of Intelligence | Lex Fridman Podcast #71

Jim Keller: Most People Don't Think Simple Enough | AI Podcast Clips

Moore's Law is Not Dead (Jim Keller) | AI Podcast Clips

Jim Keller: Elon Musk and Tesla Autopilot | AI Podcast Clips

Jim Keller: Moore's Law, Microprocessors, and First Principles | Lex Fridman Podcast #70

In this episode of the Artificial Intelligence Podcast, Lex Fridman interviews Jim Keller, a legendary microprocessor engineer. They discuss the differences between the human brain and computers, diving into the basics of computer architecture, including transistors, microprocessors, and instruction sets. Keller explai...

David Chalmers: What is Consciousness? | AI Podcast Clips

David Chalmers: The Hard Problem of Consciousness | Lex Fridman Podcast #69

YouTube Algorithm Basics (Cristos Goodrow, VP Engineering at Google) | AI Podcast Clips

Cristos Goodrow: YouTube Algorithm | Lex Fridman Podcast #68

Efficient Computing for Deep Learning, Robotics, and AI (Vivienne Sze) | MIT Deep Learning Series

Paul Krugman: Economics of Innovation, Automation, Safety Nets & UBI | Lex Fridman Podcast #67

Privacy Preserving AI (Andrew Trask) | MIT Deep Learning Series

Daniel Kahneman: How Hard is Autonomous Driving? | AI Podcast Clips

Ayanna Howard: Human-Robot Interaction & Ethics of Safety-Critical Systems | Lex Fridman Podcast #66

Daniel Kahneman: Deep Learning (System 1 and System 2) | AI Podcast Clips

Grant Sanderson (3Blue1Brown): Is Math Discovered or Invented? | AI Podcast Clips

Daniel Kahneman: Thinking Fast and Slow, Deep Learning, and AI | Lex Fridman Podcast #65

Deep Learning State of the Art (2020)

This podcast takes listeners on an exciting journey through the major advancements in deep learning from 2017 to 2019, while also offering insights into what we can expect in 2020. The speaker highlights significant developments in deep learning frameworks like TensorFlow and PyTorch, breakthroughs in natural language ...