Judea Pearl

Person

Israeli-American computer scientist (born 1936)

Mentioned in 8 videos

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Videos Mentioning Judea Pearl

The Limits of AI Understanding

The Limits of AI Understanding

Sam Harris

A prominent figure in artificial intelligence and a father of the field, known for his work on causality.

#06 – D.A. Wallach: music, medicine, longevity, and disruptive technologies

#06 – D.A. Wallach: music, medicine, longevity, and disruptive technologies

Peter Attia MD

Professor at UCLA and author of 'The Book of Why,' an expert in causal inference.

Yann LeCun: Deep Learning, ConvNets, and Self-Supervised Learning | Lex Fridman Podcast #36

Yann LeCun: Deep Learning, ConvNets, and Self-Supervised Learning | Lex Fridman Podcast #36

Lex Fridman

A prominent researcher in causal inference whose concerns about current neural networks' ability to learn causality are discussed.

George Hotz: Comma.ai, OpenPilot, and Autonomous Vehicles | Lex Fridman Podcast #31

George Hotz: Comma.ai, OpenPilot, and Autonomous Vehicles | Lex Fridman Podcast #31

Lex Fridman

A computer scientist and philosopher, described as being 'obsessed with counterfactuals,' a concept George Hotz applies to autonomous driving problems.

Dileep George: Brain-Inspired AI | Lex Fridman Podcast #115

Dileep George: Brain-Inspired AI | Lex Fridman Podcast #115

Lex Fridman

A computer scientist and philosopher, and Turing Award laureate, known for his work on causality and probabilistic reasoning.

Jitendra Malik: Computer Vision | Lex Fridman Podcast #110

Jitendra Malik: Computer Vision | Lex Fridman Podcast #110

Lex Fridman

Mentioned as someone who has extensively discussed the neglect of causality in AI, describing deep learning successes as merely 'curve fitting.'

Judea Pearl: Causal Reasoning, Counterfactuals, and the Path to AGI | Lex Fridman Podcast #56

Judea Pearl: Causal Reasoning, Counterfactuals, and the Path to AGI | Lex Fridman Podcast #56

Lex Fridman

Professor at UCLA, Turing Award winner, pioneer in AI, computer science, and statistics, known for developing probabilistic approaches like Bayesian networks and profound ideas in causality.

Stanford AA228V I Validation of Safety Critical Systems I Explainability

Stanford AA228V I Validation of Safety Critical Systems I Explainability

Stanford Online

Mentioned for his significant research on causal graphs, relevant to understanding causality beyond mere correlation.