mental models

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.

An excerpt from the 1983 BBC series Fun to Imagine in which Richard Feynman describes how he and a mathematician friend counted in their heads in different ways, one verbally and one visually. It shows that people can reach the same goal through quite different mental methods.

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.

Curt Jaimungal interviews biologist Michael Levin of Tufts about consciousness, bioelectricity, emergence, and cancer research. The conversation challenges reductionist views of life.

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.

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.

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 short clip of Steve Jobs describing the computer as a bicycle for the mind. He compares human efficiency of travel to what computers do for mental work.

A short clip of Richard Feynman answering an interviewer's question about why magnets repel, explaining that a 'why' question depends on a shared framework of understanding. It illustrates how hard it is to explain fundamentals to a layperson.

A short clip of Richard Feynman answering an interviewer's question about how magnets work, in which he explains why a why-question has no simple answer without a shared frame of reference.

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.

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 clip from a BBC interview in which Richard Feynman is asked why magnets repel and attract. He explains that "why" questions depend on what a person already accepts as fundamental.

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.

A one-minute clip from the All Things D conference in which Steve Jobs says Apple is fundamentally a software company, with iPod, Mac and iPhone all being software. He says the hardware is where the money is but the value is in the software.

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.