Lex Fridman PodcastGilbert Strang: Linear Algebra, Teaching, and MIT OpenCourseWare | Lex Fridman Podcast #52
Episode Details
EPISODE INFO
- Released
- November 25, 2019
- Duration
- 49m
- Channel
- Lex Fridman Podcast
- Watch on YouTube
- ▶ Open ↗
EPISODE DESCRIPTION
Gilbert Strang is a professor of mathematics at MIT and perhaps one of the most famous and impactful teachers of math in the world. His MIT OpenCourseWare lectures on linear algebra have been viewed millions of times. Thank you for listening ❤ Check out our sponsors: https://lexfridman.com/sponsors/ep52-sb See below for timestamps, and to give feedback, submit questions, contact Lex, etc. *CONTACT LEX:* *Feedback* - give feedback to Lex: https://lexfridman.com/survey *AMA* - submit questions, videos or call-in: https://lexfridman.com/ama *Hiring* - join our team: https://lexfridman.com/hiring *Other* - other ways to get in touch: https://lexfridman.com/contact *OUTLINE:* 0:00 - Introduction 3:45 - Math rockstar 5:10 - MIT OpenCourseWare 7:29 - Four Fundamental Subspaces of Linear Algebra 13:11 - Linear Algebra vs Calculus 15:03 - Singular value decomposition 19:47 - Why people like math 23:38 - Teaching by example 25:04 - Andrew Yang 26:46 - Society for Industrial and Applied Mathematics 29:21 - Deep learning 37:28 - Theory vs application 38:54 - Open problems in mathematics 39:00 - Linear algebra as a subfield of mathematics 41:52 - Favorite matrix 46:19 - Advice for students on their journey through math 47:37 - Looking back *PODCAST LINKS:*
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SPEAKERS
Lex Fridman
hostGilbert Strang
guest
EPISODE SUMMARY
In this episode of Lex Fridman Podcast, featuring Lex Fridman and Gilbert Strang, Gilbert Strang: Linear Algebra, Teaching, and MIT OpenCourseWare | Lex Fridman Podcast #52 explores gilbert Strang on Linear Algebra’s Power, Beauty, and Global Classroom Gilbert Strang and Lex Fridman discuss why linear algebra has become central to modern science, engineering, and artificial intelligence, and how Strang’s MIT OpenCourseWare lectures unexpectedly reached millions worldwide. Strang explains core linear algebra ideas—like vector spaces, the four fundamental subspaces, and singular value decomposition—and how they underpin data science and deep learning. They explore why piecewise-linear neural networks are so expressive, how data-driven methods “learn rules” compared to classical physics, and where the limits may lie. The conversation also touches on math education, the calculus vs. linear algebra imbalance, the joy of teaching, and the comfort and beauty many people find in mathematical truth.
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