computer hardware

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.

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.

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.

Bill Dally of NVIDIA gives a University of Washington lecture on trends in deep learning hardware. It covers numeric formats, specialized instructions, energy per operation and co-design of hardware and software.

The first lecture of MIT 6.042J Mathematics for Computer Science, taught by Tom Leighton, introducing mathematical proofs. It covers propositions, implication and basic proof methods.

John Gustafson presents posits, a proposed drop-in replacement for IEEE 754 floats that is simpler in hardware and more flexible in precision. The seminar includes a live demo and machine learning results.

The first lecture of Stanford's CS231n course on convolutional neural networks for visual recognition. It surveys the history and key challenges of computer vision, from the Cambrian explosion and Hubel and Wiesel to ImageNet.

A 1997 Computer History Museum lecture in which Larry Tesler and Chris Espinosa recount how the Apple human interface was born, from the Lisa through the Macintosh. It covers design decisions such as discoverability and the standard editing keys.

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.

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.

Hennessy and Patterson's 2018 Turing Award lecture at ISCA, A New Golden Age for Computer Architecture. It covers domain-specific hardware, security, open instruction sets and agile chip development.

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.

A UC Berkeley CS 161 lecture by Nicholas Weaver on cryptocurrency and blockchains, covering how they work and the case against them. It is aimed at a computer security course audience.

Tom Wildenhain's guest lecture for CMU's Esoteric Programming Languages course shows that PowerPoint transitions and slides are Turing complete without macros, building up to a mind-bending fractal ending.

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.

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.

Brian Kernighan gives a talk at the University of Nottingham on how to succeed in language design without really trying. He draws on his experience with awk and other languages.

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.

A 2012 lecture by Richard Stallman at Reykjavik University arguing that copyright, built for the printing press, fits poorly with computer networks. He criticizes draconian enforcement and corporate lobbying.

A SIGGRAPH 2019 course on geometric algebra. Charles Gunn gives an intro, then Steven De Keninck gives a programmer-focused course with live examples in ganja.js.

Sacha Arnoud, Waymo's Director of Engineering, gives a lecture in MIT's 2018 deep learning for self-driving cars course on the rise of machine learning in autonomous vehicles. It covers how Waymo uses deep learning and how it handles tricky driving situations.

David Shaw of D. E. Shaw Research presents Anton, a special-purpose machine that speeds up biomolecular simulations about a hundred-fold. The lecture covers molecular dynamics and how simulation helps understand how drugs bind.

The second talk in the Mill CPU series by Mill Computing, covering the Belt, the Mill's operand-passing model that replaces general registers. It explains the cost of register renaming in conventional wide CPUs and how the Belt reaches high instruction-level parallelism.

Scott Aaronson's Harvard CMSA talk traces what mathematical truths are knowable, from Godel and Turing to the Busy Beaver function. He covers recent work on Busy Beaver values.

Peter Norvig's UBC distinguished lecture on how massive amounts of simple data, such as for language modeling, can yield understanding that hand-built models could not.

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.

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.

Douglas Crockford's first Yahoo lecture puts JavaScript in historical context. He traces the language's structure and quirks back through the early decades of computer science and programming language history.

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.

Simon Peyton Jones gives Churchill College's annual computer science lecture on Haskell's birth and evolution. He covers the most influential ideas, from laziness to monads and type system evolution, plus current developments and guesses about the future.

Randy Pausch, a Carnegie Mellon computer scientist and virtual reality pioneer who was dying of cancer, gives his 'Last Lecture' about achieving childhood dreams and living well. The recording is a full-length talk of about 104 minutes.

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.

Vladimir Voevodsky's IAS lecture starts from Godel's second incompleteness theorem to explore whether first-order arithmetic could be inconsistent. It motivates his vision of univalent foundations and computer-checked proofs.

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.

A December 2005 guest lecture by Mark Zuckerberg in Harvard's CS50, discussing Facebook's early days, its technical choices and computer science. It captures him as a 21-year-old founder before Facebook's rise.

Lecture 1B of MIT's 6.001 Structure and Interpretation of Computer Programs (1986) with Gerald Sussman, covering procedures, processes and the substitution model. It includes the line about the power of naming things.

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.

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.