scale model

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.

Freeman Dyson recounts how Enrico Fermi rejected his team's meson scattering model, noting that it had too many free parameters. It is the source of the quote about fitting an elephant.

A Ray Summit 2022 keynote fireside chat between OpenAI's Greg Brockman and Anyscale's Robert Nishihara. They discuss how OpenAI's training infrastructure evolved and its use of Ray.

Stripe's John Collison interviews Anthropic CEO Dario Amodei about growth to around $5 billion ARR, model economics, agentic AI and vitalism.

An Autoline After Hours episode where Sandy Munro discusses his complete teardown of the BMW i3, along with automotive journalists. It covers the car's carbon fiber construction and manufacturing technology.

A 2007 Computer History Museum conversation in which Nvidia CEO Jen-Hsun Huang interviews TSMC founder Morris Chang. Chang recounts his career and the creation of the dedicated silicon foundry model.

A 2015 interview in which physicist Freeman Dyson, then 91, argues that global warming concerns are exaggerated, that CO2 is beneficial and that climate models oversimplify complex systems. It is posted on a channel that opposes climate consensus.

A 1996 BBC interview in which Noam Chomsky explains his propaganda model of the media to Andrew Marr, including how filters shape what journalists report and the role of self-censorship.

Engineer Sandy Munro joins an Autoline panel for a 100-minute deep dive on Tesla's design and manufacturing, including the Model 3 and its motors.

Marques Brownlee interviews Elon Musk about Tesla, the Model 3, the Roadster and the future of tech. It was recorded in 2018.

Yannic Kilcher interviews Emad Mostaque, founder of Stability AI, about the company's funding, its mission, and the release of Stable Diffusion. Topics include access to compute, handling harmful outputs, and avoiding the corrupting influence of profit.

Computerphile interviews AI safety researcher Rob Miles about ChatGPT: how it was trained with human feedback, why it tends to produce confident nonsense, and where it may or may not be dangerous.

A short excerpt of Elon Musk, interviewed by Kevin Rose, explaining first-principles reasoning with the example of the car versus improving horse carriages. He warns it takes much more mental energy than reasoning by analogy.

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.

Lex Fridman's long interview with OpenAI CEO Sam Altman about GPT-4, ChatGPT, and the future of AI. Topics include models as reasoning engines, AI risk, and consciousness.

A 1983 BBC interview in which Richard Feynman is asked how magnets work and explains why 'why' questions are hard to answer in everyday terms. He reflects on what counts as an explanation and the limits of analogy.

Nardwuar interviews Pharrell and Shay of N.E.R.D. in Vancouver, using his trademark deep research and gifts. The extended version runs about ten minutes.

Sandy Munro and Cory discuss how Tesla Model 3 and Model Y bodies in white have evolved over five years, including giga castings and lean design.

A podcast episode in which GPT-4 red teamer Nathan Labenz describes using the model before release, finding it human-level but not human-like, and discussing its weaknesses and worrying capabilities. It closes with speculation about GPT-5.

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.

Sandy Munro sits down with engineers from 3IS to compare the electrical architectures of the Tesla Model Y, Ford Mach-E and VW ID.4. They discuss ECU counts, bus architectures and what the differences mean for cost and integration.

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.

Part two of a StrictlyVC interview with OpenAI CEO Sam Altman, focused on AI. He discusses regulation, commodification of AI, Google's reluctance to release its own models, and best- and worst-case futures.