Chapter
Intuitive Physics and Reinforcement Learning
06:31 - 16:59 (10:27)
This podcast discusses the challenges and importance of using reinforcement learning to solve problems that require understanding of intuitive physics. Reinforcement learning involves providing the machine with a single scalar for every trial.
Clips
The two most popular paradigms of machine learning today are supervised learning and reinforcement learning.
06:31 - 08:52 (02:20)
Summary
The two most popular paradigms of machine learning today are supervised learning and reinforcement learning. While supervised learning requires a large sample size for learning, reinforcement learning needs simulation to handle large-scale learning.
ChapterIntuitive Physics and Reinforcement Learning
Episode#258 – Yann LeCun: Dark Matter of Intelligence and Self-Supervised Learning
PodcastLex Fridman Podcast
The first few months of a baby's life are spent learning about the world through observation, without any specific tasks or reinforcement, which forms the basis of common sense.
08:52 - 09:47 (00:55)
Summary
The first few months of a baby's life are spent learning about the world through observation, without any specific tasks or reinforcement, which forms the basis of common sense. Reproducing this kind of learning in machines is possible through self-supervised learning which involves observing the world and building world models.
ChapterIntuitive Physics and Reinforcement Learning
Episode#258 – Yann LeCun: Dark Matter of Intelligence and Self-Supervised Learning
PodcastLex Fridman Podcast
This podcast episode explores the limitations of AI and how it compares to human intuition when it comes to intuitive physics and learning from experience.
09:47 - 12:32 (02:44)
Summary
This podcast episode explores the limitations of AI and how it compares to human intuition when it comes to intuitive physics and learning from experience.
ChapterIntuitive Physics and Reinforcement Learning
Episode#258 – Yann LeCun: Dark Matter of Intelligence and Self-Supervised Learning
PodcastLex Fridman Podcast
The human brain has intuitive physics that helps us fill in missing information, including predicting the future and inferring the past.
12:33 - 16:59 (04:26)
Summary
The human brain has intuitive physics that helps us fill in missing information, including predicting the future and inferring the past. Machines can do the same by predicting and learning from what actually happens over time.