learning from data

Dwarkesh Patel interviews Andy Matuschak on how he learns, why memorization matters for understanding, and why most learning tools fail. The conversation also covers handling confusion and the role of tutoring.

Pixar staff tell the story of how Toy Story 2 was almost deleted from the studio's computers and was saved by a home computer backup.

Fox Business interview in which Oracle co-founder Larry Ellison claims Oracle will beat Amazon at cloud databases. He argues the world's valuable data lives in Oracle and says Amazon struggled to move off it.

Brian Kernighan explains how grep came to be, written overnight by Ken Thompson, and how it got its name from the ed command g/re/p. He also covers the lineage from QED to ed that led to it.

Dwarkesh Patel interviews OpenAI chief scientist Ilya Sutskever on time to AGI, what comes after generative models, data limits, alignment, and competing with Google. The title centers on whether next-token prediction could surpass human intelligence.

Asian Boss interviews Professor Kim Woo-joo of Korea University Guro Hospital about COVID-19 in early 2020. He covers masks, testing, aerosol spread, and South Korea's response.

A clip from the documentary Page One in which New York Times reporter David Carr interviews and confronts the founders of Vice magazine over their media deal. It captures tension between old and new media in 2010.

Mike Acton, in a HandmadeCon 2015 interview with Casey Muratori, discusses game engine development, hiring and learning on your own.

Dwarkesh Patel interviews Google's Jeff Dean and Noam Shazeer about 25 years at the company, from PageRank and MapReduce to the Transformer, mixture of experts and Gemini. They also discuss where AI is heading.

Dwarkesh Patel interviews Richard Sutton, reinforcement learning pioneer, Turing Award winner and author of The Bitter Lesson. Sutton argues LLMs are a dead end because they cannot learn on the job, and that continual learning from experience will require a new architecture.

A five-minute clip in which Erich Fromm asks whether the purpose of work is just making money. He argues that white-collar workers end up selling their personality, relating to others the way goods relate to each other on a market, and he points to creative pleasure, participation and usefulness to society as what work could offer instead.

A one-minute clip of Steve Jobs in 2010 saying companies should ask users before tracking them, and that people's personal data is like their diary.

A Computer History Museum oral history with Avie Tevanian covering his math talent, work on the Mach microkernel at CMU, joining NeXT, leading NEXTSTEP development and the 1996 Apple acquisition.

A Channel 9 Going Deep interview in which Brian Beckman talks with Rich Hickey, creator of Clojure, about the language's design. It covers Clojure's persistent data structures, reference types and its approach to concurrency on the JVM.

A 2023 University of Toronto conversation between Geoffrey Hinton and Fei-Fei Li on responsible AI development. They look back at the history of deep learning and ImageNet and discuss the ethics and risks of AI.

A Channel 4 News interview with technologist Jaron Lanier, who argues that social media damages people's lives. He discusses how Facebook, YouTube and Google use algorithms and data collection to shape what users see.

A five-minute clip from Donald Knuth's Web of Stories interviews in which he gives advice to young people, including being wary when too many people adopt an idea.

A Bankless podcast interview with Paul Christiano of the Alignment Research Center on the AI alignment problem and possible solutions. It also covers his views on how an AI takeover might unfold.

John Gruber interviews Craig Federighi and Greg Joswiak after WWDC 2020 about the Mac transition to Apple silicon, macOS Big Sur and iOS 14.

A short excerpt from a 1973 Yorkshire TV film in which Richard Feynman explains that knowing the name of something is not the same as knowing it.

Dwarkesh Patel interviews Andrej Karpathy on why reinforcement learning is flawed, why AGI may blend into steady GDP growth, why self-driving took so long, and the future of education. The conversation runs about two and a half hours.

Matt Damon appears on Hot Ones, eating progressively spicier wings while discussing his film career and promoting Stillwater. He also explains how the decline of the DVD market changed which movies get made.

A long Machine Learning Street Talk interview with Kenneth Stanley, creator of NEAT and novelty search, about his book on why greatness cannot be planned. They discuss open-endedness, the tyranny of objectives, serendipity and the evolution of ideas.

Ezra Klein interviews Democratic pollster David Shor, who walks through survey data and charts explaining the 2024 election results. They discuss voter shifts, the education divide and what Democrats got wrong.

A short street interview from Invisible People with Keith, a homeless man in Los Angeles who lost his housing-industry job in the crash and moved from painkillers to heroin because it was cheaper. He talks candidly about the grip of addiction.

A Soho Forum debate in which patent lawyer Stephan Kinsella argues for abolishing copyright and patents against law professor Richard Epstein. Both come from libertarian perspectives.

A 42-minute CBS interview with Geoffrey Hinton at the Vector Institute in 2023, covering the history of neural networks and the present and future of AI. He discusses AGI timelines and whether language models truly understand.

Tim Dodd of Everyday Astronaut gets a close-up walkthrough of SpaceX's Raptor 2 engine from Elon Musk at Starbase. They cover how Raptor 2 was simplified and upgraded relative to Raptor 1, including cooling and thrust vectoring details.

A 12-minute clip from Joe Rogan's podcast in which former NASA astronaut Garrett Reisman describes working for Elon Musk at SpaceX. He discusses Musk's engineering breadth, his Mars-focused decision making and the stress of the job.

A short clip of Steve Jobs explaining how sales and marketing people take over mature companies from product people, leading to product decline.

A Google Developers Q&A in which Blink engineering leads and the PM answer the community's top questions about the new Blink rendering engine forked from WebKit.

A TED2014 interview in which Charlie Rose talks with Google CEO Larry Page about the company's long-term vision, including balloons for internet access and the DeepMind acquisition. Page also discusses data sharing and privacy.

A one-minute clip from the 1995 Steve Jobs interview in which he describes what he saw at Xerox PARC and what he missed. He says he grasped the graphical interface but not the networking and object-oriented parts.

The full-length Numberphile interview with mathematician and hedge fund founder Jim Simons. He discusses his path from mathematics and codebreaking to founding Renaissance Technologies, his use of algorithms in markets, and his philanthropy.

A long interview by Blender Guru with Ton Roosendaal, creator of Blender. They cover Blender's origins, the move to open source, why Ton is not driven by money, Autodesk, and what sets Blender apart from other open source projects.

A short clip from a Richard Feynman interview in which he explains fire, describing how burning wood releases sunlight stored by the tree, which built itself mostly from air. It showcases his curiosity and plain-spoken explanations.

Lex Fridman interviews legendary chip architect Jim Keller about Moore's Law, microprocessor design, and first-principles thinking. Keller draws on his work at AMD, Apple, Tesla and Intel, discussing instruction sets, transistor budgets, and self-driving.

A short excerpt from a 1994 interview of Steve Jobs in which he says everything around us was made up by people no smarter than you, and that you can change and shape the world.

A standing whiteboard conversation at Lang.NEXT 2012 among Carl Hewitt, Erik Meijer and Clemens Szyperski about the actor model. Hewitt, who originated the model, explains its foundations.

Numberphile talks with mathematician Ron Graham about the magnitude of Graham's number, building up from arrow notation to show how impossibly large it is. It is part of a series of videos on this number.