fusion

Zach Hartwig of MIT introduces the key concepts of magnetic fusion energy and the state of fusion research. He then presents MIT's proposed pathway of using high-field superconducting magnets to build smaller, cheaper tokamaks on a climate-relevant timescale.

An MIT colloquium by Dennis Whyte on power exhaust and first-wall cooling in fusion reactors, including recent innovations and the SPARC and ARC designs.

A roughly three-hour technical livestream Q&A on Helion Energy's fusion approach and the National Ignition Facility. It covers neutron production, shielding, energy recovery, diagnostics and why tokamaks might fare better.

Royal Institution lecture by Dr Kate Lancaster on the most powerful lasers in the world and the extreme conditions they create. It includes live demonstrations and covers applications from industry to fusion.

A professor from Illinois compares the cost of building, fueling and operating a nuclear plant against a natural gas plant, using visual charts. It shows how construction time and interest rates dominate, when the investment pays off and when costs cross over.

MIT 22.01 lecture by Michael Short explaining the Chernobyl accident technically, including RBMK reactor positive feedback, xenon poisoning and the cascade of human errors during the test.

Professor Ruzic explains modular micro-reactors: self-contained nuclear units with passive safety whose fuel lasts about 20 years. He covers their use for process and district heat and where they can compete with diesel generation.

A lecture for high school seniors and college freshmen making the case for nuclear power and answering common objections. It is an overview of the channel's more detailed videos on each topic.

Part 1 of Jean-Marc Jancovici's 2019 course at Ecole des Mines de Paris, on energy and its central role in the economy and climate. It is in French with English subtitles available and runs about two and a half hours.

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.

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.

Sebastien Bubeck presents the Sparks of AGI paper at MIT, showing early experiments with GPT-4 across many domains and asking whether artificial intelligence has arrived. It includes the TikZ unicorn example.

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.

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.

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.

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

Harvard Belfer Center lecture by Matthew Bunn explaining how nuclear bombs work, including fission and fusion weapons and which parts of bomb-making are hard. It is part 1 of 2 in the Nuclear 101 series.

Dan Britt lectures on the history of climate, covering orbital cycles, ice ages and conditions millions of years ago. It frames current climate debate with deep-time context.