Chapter
The Intersection of Physics and Machine Learning
22:34 - 31:16 (08:41)
Physicist, Max Tegmark, discusses the similarities and potential intersection between the mathematical structures of quantum physics and machine learning algorithms, predicting the possibility of evolving systems and discovering new implications for consciousness.
Clips
The way the brain compartmentalizes information is different from what one might imagine from mere psychological introspection, and introspection itself may be flawed due to a lack of understanding of the brain's inner workings.
22:34 - 24:07 (01:32)
Summary
The way the brain compartmentalizes information is different from what one might imagine from mere psychological introspection, and introspection itself may be flawed due to a lack of understanding of the brain's inner workings. Viewing the brain as an information processing system reveals emergent phenomena related to how it processes information.
ChapterThe Intersection of Physics and Machine Learning
EpisodeLeonard Susskind: Quantum Mechanics, String Theory, and Black Holes
PodcastLex Fridman Podcast
AI systems created through machine learning may lead to the discovery of mechanisms that can help us understand the nature of consciousness, despite the initial complexity of such systems.
24:08 - 25:55 (01:46)
Summary
AI systems created through machine learning may lead to the discovery of mechanisms that can help us understand the nature of consciousness, despite the initial complexity of such systems.
ChapterThe Intersection of Physics and Machine Learning
EpisodeLeonard Susskind: Quantum Mechanics, String Theory, and Black Holes
PodcastLex Fridman Podcast
The fields of physics and machine learning intersect in the structure of the math, with young physicists bringing value to the field of machine learning.
25:55 - 31:16 (05:20)
Summary
The fields of physics and machine learning intersect in the structure of the math, with young physicists bringing value to the field of machine learning.