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A short clip of Robert Sapolsky on how social hierarchy generates chronic stress, drawing on baboon research. It links rank-related stress to heart health and life expectancy.

A one-minute clip from Richard Feynman's 1979 Auckland lecture in which he answers whether you see an object or only its light. It is a short, playful take on perception and on the use of philosophy.

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.

The first lesson of Uncle Bob (Robert C. Martin)'s "Coding Better World Together" series. It makes the case for clean code and for treating software craftsmanship as an ethical and professional responsibility. It runs about 109 minutes.

Chris Granger, creator of Light Table and the Eve language, gives a Berkeley data science lecture on what computation and programming might look like in ten years. He covers the path that led to Eve and ends with demos.

Brian Will critiques object-oriented programming and rewrites a roughly 3800-line OO program in a procedural style, cutting code and complexity. It is part of a series of OOP critiques.

Physicist Al Bartlett's well-known lecture on the arithmetic of exponential growth, applied to population, energy consumption and resource depletion. He argues that steady percentage growth cannot be sustained on a finite planet and that most public discussion ignores this.

Physicist Albert Bartlett's full-length lecture on how steady exponential growth in population and energy use collides with finite resources. It uses examples like bacteria in a bottle and covers peak oil.

Robert Sapolsky's Stanford lecture on the limbic system as the emotional part of the nervous system, covering its role in decision making, links to the cortex and the functions of its subparts.

Andrej Karpathy's first Neural Networks: Zero to Hero lecture, which builds micrograd, a tiny autograd engine, from scratch in Python. It explains backpropagation and neural network training step by step, assuming only basic Python and some high-school calculus.

The opening lecture of Robert Sapolsky's Stanford course on Human Behavioral Biology, explaining the course premise and how to avoid categorical thinking. It starts a roughly 25-lecture series on how biology, genes, hormones and environment shape behavior.

Cognitive scientist George Lakoff lectures on how political debates are framed through language and metaphors tied to values, and on the moral worldviews behind progressive and conservative politics. It was given in 2005 at UC San Diego.

Stanford professor Robert Sapolsky lectures on depression as a real biological disease. He covers its biological and psychological causes, how it differs from ordinary sadness, and ideas such as learned helplessness. He ties these together into one account.

Andrej Karpathy's three-hour-plus general-audience deep dive into how ChatGPT-style LLMs are built, covering the full training stack from pretraining to post-training. It also gives mental models for their quirks, like hallucination, and how to use them well.

Douglas Hofstadter's Stanford Presidential Lecture argues that analogy is the core of cognition, illustrating how concepts, categorization and thought arise from analogy-making.

The first episode of John Vervaeke's lecture series on the modern meaning crisis, tracing its history through philosophy, cognitive science, religion and psychology. It introduces the series and its themes.

Robert Sapolsky's lecture on how the body's stress response, evolved for short-term physical emergencies, harms long-term health when triggered by psychological stressors. It was given as the inaugural Fenton-Rhodes Lecture.

Neuroscientist Anil Seth gives a Royal Institution lecture on the science of consciousness. He separates conscious level, content and self, and argues that experience arises from the brain's predictive inference.

Andrej Karpathy builds the GPT tokenizer from scratch, implementing byte pair encoding along with encode and decode. He shows how many odd LLM behaviors trace back to tokenization, and covers Unicode byte encodings along the way.

A Virginia Tech presentation by Sid Smith about collapse, fossil fuels and overshoot, arguing that industrial civilization faces a decline and how one might live with that. It was later expanded into a video series.

Leo Dirac explains how transformer models have replaced LSTMs in NLP. He gives background from bag of words through RNNs and LSTMs, then a technical deep dive into multi-headed self-attention and positional encoding, with sample code.

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.

Energy scholar Vaclav Smil argues that global energy transitions are slow and that renewable targets should not rest on wishful thinking. He appraises how energy dependencies are likely to change and asks for using much less.

A 73-minute Stanford talk by Robert Sapolsky drawn from his book Behave. It surveys the biological factors behind human behavior at its best and worst.

Geoffrey Hinton's 2025 Royal Institution Discourse on what AI has learned from biological intelligence and how it might surpass it. He explains neural networks and argues that human language use resembles what backpropagation-trained networks do.

The first lecture of Stanford's Natural Language Processing with Deep Learning course, taught by Chris Manning and Richard Socher. It introduces NLP and word vectors, including SVD, skip-gram, CBOW, negative sampling and word2vec.

Robert Sapolsky's Stanford lecture on language, comparing human and animal communication, ape language projects like Koko and Kanzi, and how language is acquired. It is part of his human behavioral biology course.

Sasha Rush surveys linear RNNs and state space models as replacements for attention in transformer-style models, in a talk for MLSys. It covers the foundational preliminaries and predates Mamba.

Dr. Russell Barkley lectures on the neuroanatomy of ADHD and how to treat it, linking executive function and working memory to the disorder. It is part 3 of a CADDAC series.

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 Royal Institution lecture in which Nicholas Humphrey presents his theory of phenomenal consciousness and its evolution. He draws on the book Sentience and discusses evidence for animal sentience.

The first lecture of David MacKay's Cambridge course on information theory, pattern recognition and neural networks. It introduces the core ideas of his book Information Theory, Inference, and Learning Algorithms.

A university lecture from CS480/680 by Pascal Poupart on attention mechanisms and transformer networks, worked through on a chalkboard.

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.

A clip of psychologist Jordan Peterson lecturing on intelligence and IQ, covering how it is defined and its correlation with academic and work success.

Andres Gomez Emilsson of the Qualia Research Institute presents a model of DMT experiences using hyperbolic geometry and dynamical systems theory. He describes how different intoxication levels correspond to changing curvature and information content of experience.

Noam Chomsky's 2011 University of Oslo lecture on Newton's contributions to the study of mind. He argues Newton abandoned mechanical explanation and lowered the bar for scientific intelligibility, with consequences for the limits of human understanding. Q&A starts at 45:33.

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.

Neuroscientist Karl Friston gives a 15-minute talk on the free energy principle, covering Markov blankets, Bayesian model evidence and global brain theories.

Douglas Hofstadter lectures at Uppsala University on how analogy and daring thinking drove Einstein's discovery of light quanta. He argues deep insight in physics comes from imaginative leaps rather than rigid logic.