personal computers

The opening lecture of Jordan Peterson's 2017 University of Toronto personality course. He defines personality from historical, constructivist, psychoanalytic, behavioral and neuropsychological angles.

A Jordan Peterson university lecture on the Big Five trait openness to experience, covering creativity and intelligence. It explains how IQ is measured, how well it predicts life success, and the Pareto distribution of creative output.

An eight-minute excerpt of a 1983 video featuring Seymour Papert, creator of Logo, on children learning programming and abstract ideas through embodied play. It shows kids acting out the Logo turtle.

Chris Shore of the Centre for Computing History explains how Colossus was built, how it worked, and how it affected the course of World War II. It is an hour-long museum lecture on the codebreaking computer.

A lecture by Richard Feynman on how computers work, using the analogy of a filing clerk that becomes progressively dumber and faster. It also covers heuristics and how computers handle data and solve problems in finite time.

Daniel Dennett's Royal Institution lecture on whether the brain is a computer and where its software comes from. He argues that minds are built by evolution and culture, with competence arising without comprehension.

A Bell Labs film in which Dr. J.N. Shive uses a mechanical wave machine to demonstrate reflection, standing waves, resonance and impedance matching. He includes some equations but relies mostly on real-world examples a layperson can follow.

Robert Wills of TNMoC explains the Apollo Guidance Computer hardware and software, then walks through the Apollo 11 landing procedure step by step, including the 1202 alarms.

Alan Kay's Stanford Startup School lecture covers his career at Xerox PARC and how to think about inventing the future. He goes through what came out of PARC and why companies fail to capitalize on such ideas.

Steve Blank's Computer History Museum lecture argues that Silicon Valley's roots lie in WWII radar and electronic warfare work, Stanford's Fred Terman and Cold War military funding rather than the semiconductor alone.

Part two of Alan Kay's Stanford Startup School lecture on inventing the future. He draws on his time at Xerox PARC and elsewhere to discuss how to think about new technology and what makes ideas useful.

Admiral Grace Hopper holds up a length of wire to show how far light travels in a nanosecond, about 11.8 inches. She explains how she made the idea concrete to people who could not picture a billionth of a second.

A 1990 lecture by James Gosling on NeWS, Sun's networked window system in which clients send PostScript programs to the server for execution. It covers the high-level imaging model and compares NeWS with similar systems.

A long recorded seminar in which Alan Kay discusses object-oriented programming, probably from the mid-1980s. He covers the original idea of objects, messaging and the work done at Xerox.

Part one of Capt. Grace Hopper's 1982 NSA lecture on the future of data, hardware, software and people. It includes her humor, her nanosecond demonstration and views on scaling and resisting old ways of doing things.

The full 1973 BBC Lighthill debate on artificial intelligence, featuring James Lighthill, Donald Michie, Richard Gregory and John McCarthy. It documents the argument that preceded the 1970s AI winter and includes early robot demos.

A lecture by Commodore Grace Hopper on the future of computing, posted by MIT Lincoln Laboratory. It includes her well-known nanosecond wire demonstration and humorous comparisons of device latencies.

The first lecture of MIT's 6.001 (SICP) with Abelson and Sussman, giving an overview of the course and an introduction to Lisp. It argues that computer science is about managing complexity and abstraction, not computers.

The first lecture of MIT's 1986 6.001 Structure and Interpretation of Computer Programs, given by Harold Abelson, introducing Lisp and the idea of computer science as the study of process.

Casey Muratori's first refterm lecture lays out philosophies of optimization, distinguishing optimization from non-pessimization, which means avoiding needless work. It uses his fast terminal renderer project to show how fast computers really are.

The first lecture of Jordan Peterson's 2017 Maps of Meaning course, setting out the Cold War context for his theory of belief and culture. He introduces the narrative structure of culture and archetypal characters for the individual, the known and the unknown.

The first lecture of Michael Sipser's MIT 18.404J Theory of Computation course, covering course mechanics, finite automata, regular languages and regular expressions. It proves closure of regular languages under union and begins concatenation.

A Stanford EE380 seminar by Michael P. Frank of Sandia National Laboratories on generalized reversible computing. It surveys unconventional computing approaches as transistor scaling nears its limits and energy efficiency stops improving.

An excerpt of Richard Feynman's 1985 lecture Q&A about whether machines can think. He discusses the difficulty of defining what computers can never do and compares machine intelligence to machines that don't copy animals.

An excerpt from Hal Abelson's opening SICP lecture introducing computer science and contrasting declarative and imperative knowledge. He argues that computer science is not really a science and is more like magic or engineering of ideas.

A 2013 lecture in which Vitalik Buterin explains what quantum computers are and what they can and cannot do. He then discusses what they could mean for Bitcoin's cryptography.

Thomas Sowell speaks at the Hoover Institution about economic and racial inequality and what he considers myths about poverty. He also recounts his early life and brief flirtation with Marxism.