The Gradient Podcast - Gil Strang: Linear Algebra and Deep Learning
In episode 86 of The Gradient Podcast, Daniel Bashir ( / spaniel_bashir ) speaks to Professor Gil Strang. Professor Strang is one of the world’s foremost mathematics educators and a mathematician with contributions to finite element theory, the calculus of variations, wavelet analysis, and linear algebra. He has spent six decades teaching mathematics at MIT, where he was the MathWorks Professor of Mathematics. He was among the first MIT faculty members to publish a course on MIT’s OpenCourseware and has since championed both linear algebra education and open courseware. Have suggestions for future podcast guests (or other feedback)? Let us know here or reach us at [email protected] Subscribe to The Gradient Podcast: Apple Podcasts (https://podcasts.apple.com/us/podcast...) | Spotify (https://open.spotify.com/show/6onNcSq...) | Pocket Casts (https://pca.st/itunes/1569777340) | RSS (https://api.substack.com/feed/podcast... The Gradient on Twitter ( / gradientpub ) Outline: (00:00) Intro (02:00) Professor Strang’s background and journey into teaching linear algebra (04:55) Undergrad interests (07:10) Writing textbooks (10:20) Prof. Strang’s interests in deep learning (11:00) How Professor Strang thought about teaching early on (16:20) MIT OpenCourseWare and education accessibility (19:50) Prof Strang’s applied/example-based approach to teaching linear algebra and closing the theory-practice gap (22:00) Examples! (27:20) Orthogonality (29:15) Singular values (34:40) Professor Strang’s favorite topics in linear algebra (37:55) Pedagogical approaches to deep learning, mathematical ingredients of deep learning’s complexity (42:04) Generalization and double descent in deep learning, powers and limitations (46:20) Did deep learning have to evolve as it did? (48:30) Teaching deep learning to younger students (50:50) How Prof. Strang’s approach to teaching linear algebra has evolved over time (53:00) The Four Fundamental Subspaces (56:15) Reflections on a career in teaching (59:49) Outro Links: Professor Strang’s homepage (https://math.mit.edu/~gs/) Get full access to The Gradient at thegradientpub.substack.com/subscribe (https://thegradientpub.substack.com/s...) Episode link: https://play.headliner.app/episode/16... (video made with https://www.headliner.app)

Why This Is the Most Exciting Time to Be Human | Ken Ono, Axiom Math

The Gradient Podcast - David Pfau: Manifold Factorization and AI for Science

Po-Shen Loh: Mathematics, Math Olympiad, Combinatorics & Contact Tracing | Lex Fridman Podcast #183

Keynote: After the AI Hype – What’s Real, and What’s Next - Richard Campbell - 2026

We Can't Predict The Future of AI, Only Time Can
![Your Phone Is Destroying Your Sense of Meaning | Arthur Brooks [ARC 2026]](https://i.ytimg.com/vi/PfTcgYwW14E/hqdefault.jpg?sqp=-oaymwEjCNACELwBSFryq4qpAxUIARUAAAAAGAElAADIQj0AgKJDeAE=&rs=AOn4CLBzBqlOzXKaS_MJrH8pIKehA8ZKPQ)
Your Phone Is Destroying Your Sense of Meaning | Arthur Brooks [ARC 2026]

2026 Fields Medal: Hong Wang

How To Think SO Clearly People Assume You're Brilliant

Philosopher David Chalmers asks: When we talk to AI, what are we talking to?

The Strange Math That Predicts (Almost) Anything

2026 Fields Medal: Yu Deng

Gilbert Strang: Linear Algebra vs Calculus

The Most Powerful Manifestation Technique ... It Works So Fast It's Scary.

Is This Wish Meant to Be Fulfilled? 🧚🤲 Detailed Pick a Card Tarot Reading ✫・

One of the most important algebras -- The Witt Algebra

The French Do Not Care About Work

How To Learn So Fast It’s Almost Unfair

Terry Tao's GPT chatlog re: Jacobian conjecture

The myth that stupidity means low intelligence | Jonny Thomson: Full Interview

