Lex Fridman

Rajat Monga: TensorFlow | Lex Fridman Podcast #22

Chris Lattner: Compilers, LLVM, Swift, TPU, and ML Accelerators | Lex Fridman Podcast #21

Oriol Vinyals: DeepMind AlphaStar, StarCraft, and Language | Lex Fridman Podcast #20

MIT 6.S093: Introduction to Human-Centered Artificial Intelligence (AI)

Ian Goodfellow: Generative Adversarial Networks (GANs) | Lex Fridman Podcast #19

Elon Musk: Tesla Autopilot | Lex Fridman Podcast #18

Lex Fridman interviews Elon Musk about Tesla's Autopilot and the future of self-driving technology. Musk discusses the evolution of Autopilot, the importance of data and hardware, and the challenges of achieving full autonomy. He emphasizes the potential for current Tesla cars to become appreciating assets as software ...

Greg Brockman: OpenAI and AGI | Lex Fridman Podcast #17

Eric Weinstein: Revolutionary Ideas in Science, Math, and Society | Lex Fridman Podcast #16

Leslie Kaelbling: Reinforcement Learning, Planning, and Robotics | Lex Fridman Podcast #15

Karl Iagnemma & Oscar Beijbom (Aptiv Autonomous Mobility) - MIT Self-Driving Cars

Oliver Cameron (CEO, Voyage) - MIT Self-Driving Cars

Drago Anguelov (Waymo) - MIT Self-Driving Cars

Kyle Vogt: Cruise Automation | Lex Fridman Podcast #14

Self-Driving Cars: State of the Art (2019)

MIT 6.S091: Introduction to Deep Reinforcement Learning (Deep RL)

Tomaso Poggio: Brains, Minds, and Machines | Lex Fridman Podcast #13

Deep Learning State of the Art (2019)

Deep Learning Basics: Introduction and Overview

In this lecture, Lex Fridman introduces deep learning for self-driving cars, emphasizing its role in automating pattern extraction from data with minimal human intervention. He discusses the importance of optimization of neural networks and the accessibility provided by libraries like TensorFlow. Fridman highlights the...

Tuomas Sandholm: Poker and Game Theory | Lex Fridman Podcast #12

Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11