Cristos Goodrow: YouTube Algorithm

Cristos Goodrow is VP of Engineering at Google and head of Search and Discovery at YouTube (aka YouTube Algorithm). This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spoti

David Chalmers: The Hard Problem of Consciousness

David Chalmers is a philosopher and cognitive scientist specializing in philosophy of mind, philosophy of language, and consciousness. He is perhaps best known for formulating the hard problem of consciousness which could be stated as “why does the feeling which accompanies awareness of sensory information exist at all?” This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @l

Jim Keller: Moore’s Law, Microprocessors, Abstractions, and First Principles

Jim Keller is a legendary microprocessor engineer, having worked at AMD, Apple, Tesla, and now Intel. He’s known for his work on the AMD K7, K8, K12 and Zen microarchitectures, Apple A4, A5 processors, and co-author of the specifications for the x86-64 instruction set and HyperTransport interconnect. This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter,

Vladimir Vapnik: Predicates, Invariants, and the Essence of Intelligence

Vladimir Vapnik is the co-inventor of support vector machines, support vector clustering, VC theory, and many foundational ideas in statistical learning. He was born in the Soviet Union, worked at the Institute of Control Sciences in Moscow, then in the US, worked at AT&T, NEC Labs, Facebook AI Research, and now is a professor at Columbia University. His work has been cited over 200,000 times. This conversation is part of the Artificial Intelligence podcast. If you would like to get more informa

#72 – Scott Aaronson: Quantum Computing

Scott Aaronson is a professor at UT Austin, director of its Quantum Information Center, and previously a professor at MIT. His research interests center around the capabilities and limits of quantum computers and computational complexity theory more generally. This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube w

#73 – Andrew Ng: Deep Learning, Education, and Real-World AI

Andrew Ng is one of the most impactful educators, researchers, innovators, and leaders in artificial intelligence and technology space in general. He co-founded Coursera and Google Brain, launched deeplearning.ai, Landing.ai, and the AI fund, and was the Chief Scientist at Baidu. As a Stanford professor, and with Coursera and deeplearning.ai, he has helped educate and inspire millions of students including me. EPISODE LINKS: Andrew Twitter: https://twitter.com/AndrewYNg Andrew Facebook: https://

#74 – Michael I. Jordan: Machine Learning, Recommender Systems, and the Future of AI

Michael I. Jordan is a professor at Berkeley, and one of the most influential people in the history of machine learning, statistics, and artificial intelligence. He has been cited over 170,000 times and has mentored many of the world-class researchers defining the field of AI today, including Andrew Ng, Zoubin Ghahramani, Ben Taskar, and Yoshua Bengio. EPISODE LINKS: (Blog post) Artificial Intelligence—The Revolution Hasn’t Happened Yet This conversation is part of the Artificial Intelligence po

#75 – Marcus Hutter: Universal Artificial Intelligence, AIXI, and AGI

Marcus Hutter is a senior research scientist at DeepMind and professor at Australian National University. Throughout his career of research, including with Jürgen Schmidhuber and Shane Legg, he has proposed a lot of interesting ideas in and around the field of artificial general intelligence, including the development of the AIXI model which is a mathematical approach to AGI that incorporates ideas of Kolmogorov complexity, Solomonoff induction, and reinforcement learning. EPISODE LINKS: Hutter

#76 – John Hopfield: Physics View of the Mind and Neurobiology

John Hopfield is professor at Princeton, whose life’s work weaved beautifully through biology, chemistry, neuroscience, and physics. Most crucially, he saw the messy world of biology through the piercing eyes of a physicist. He is perhaps best known for his work on associate neural networks, now known as Hopfield networks that were one of the early ideas that catalyzed the development of the modern field of deep learning. EPISODE LINKS: Now What? article: http://bit.ly/3843LeU John wikipedia: ht

#77 – Alex Garland: Ex Machina, Devs, Annihilation, and the Poetry of Science

Alex Garland is a writer and director of many imaginative and philosophical films from the dreamlike exploration of human self-destruction in the movie Annihilation to the deep questions of consciousness and intelligence raised in the movie Ex Machina, which to me is one of the greatest movies on artificial intelligence ever made. I’m releasing this podcast to coincide with the release of his new series called Devs that will premiere this Thursday, March 5, on Hulu. EPISODE LINKS: Devs: https://


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