fusion

Sabine Hossenfelder explains how close nuclear fusion really is to break-even, and why headlines about ITER and lab milestones are misleading. She distinguishes plasma gain (Q plasma) from whole-system gain (Q total) and shows the latter is still far below one.

Real Engineering's Brian McManus explains Helion's approach to nuclear fusion: colliding two plasma rings, compressing them magnetically, and capturing energy directly from the changing magnetic flux rather than boiling water. It covers why this pulsed design sidesteps problems of tokamaks and laser fusion.

A CAD-based animation from the Max Planck Institute for Plasma Physics showing how the Wendelstein 7-X stellarator is configured and what its fusion research aims to achieve. It runs about 11 minutes.

A guest video by Welch Labs on 3Blue1Brown explaining how text-to-image and video models work. It covers CLIP, shared embedding spaces, diffusion models (DDPM, DDIM), conditioning, guidance and negative prompts.

Kurzgesagt compares how many people nuclear accidents have killed against other energy sources. It walks through the worst nuclear accidents and puts their death tolls in context per unit of energy.

A 2011 remix of over six hours of talks by Kirk Sorensen and other thorium advocates, explaining thorium as a nuclear fuel and the liquid-fluoride thorium reactor (LFTR). It argues LFTRs could produce energy without long-lived transuranic waste.

RethinkX summarizes its report arguing that mainstream LCOE estimates are inflating a bubble in coal, gas, nuclear and hydro assets. It claims solar, wind and batteries will strand conventional energy investments.

Kyle Hill explains what nuclear waste actually is and how it is stored, arguing that the problem was effectively solved decades ago. It covers solid shielded waste and deep geological storage.

Veritasium visits Chernobyl, Fukushima and other places to find who on Earth is exposed to the most ionizing radiation. The answer turns out to be surprising and puts radiation risk in context.

Real Engineering looks at why nuclear power plants are expensive and how their economics compare with fossil and renewable alternatives. It is based on a video from the Illinois Energy Professors.

Randall Munroe of xkcd answers what would happen if you swam in a spent nuclear fuel pool, and how much radiation you would receive at the surface versus at depth.

Scott Manley explains the nuclear salt water rocket, Robert Zubrin's concept of a rocket fueled by a rapid nuclear reaction in uranium salt dissolved in water. He covers its extraordinary performance and the dangers of managing it.

Cleo Abram's explainer on whether nuclear waste is really the intractable problem it is portrayed as, looking at how spent fuel can be recycled and used. It features a collaboration with Johnny Harris.

Minutephysics compares how efficiently different processes convert mass to energy per E=mc^2, from fire and fission to fusion, antimatter and black holes, which can convert a large fraction of mass to energy.

3Blue1Brown's visual explanation of how transformers and GPT-style language models work, tracing data through tokens, embeddings and attention.

3Blue1Brown's visual walkthrough of the attention mechanism inside transformers, covering self-attention, multiple heads and cross-attention. It is chapter 6 of his deep learning series.

Yannic Kilcher walks through the Attention Is All You Need paper, which introduced the Transformer, a sequence model based solely on attention without recurrence or convolutions. He reviews the architecture and the paper's translation results.

Rob Miles explains on Computerphile how language models generate plausible text and how transformers improved on recurrent networks, with a look at what comes next.

A short cartoon explaining how language models like ChatGPT work, from autocomplete and conditional probabilities to neural networks, gradient descent and backpropagation. It shows how networks act as universal function approximators.

Kurzgesagt examines how AI-generated content is flooding the internet, from video and music to news and books. It looks at how this makes verifying what is real harder.

Alex O'Connor shows that ChatGPT cannot draw a wine glass filled to the brim, and ties the failure to David Hume's missing shade of blue. It asks what the failure says about how image models learn.

A Welch Labs explainer on neural scaling laws and the compute-efficient frontier, asking why model loss seems to hit a line it cannot cross. It draws an analogy to an ideal gas law for AI.

Rob Miles explains "glitch" tokens, odd strings in large language model vocabularies that make the model produce gibberish. He covers how they likely arise from tokenizer training data, such as Reddit usernames, that never appeared in the model's own training.

Musician Benn Jordan explains and demonstrates adversarial noise that poison-pills music files against AI training and scraping.

Chubbyemu presents a case study of a man who followed AI health advice, replaced salt with sodium bromide and developed bromism with severe neurological effects. It is told as a dramatized medical case by a doctor.

Musician Benn Jordan uses AI to detect AI-generated music and digs into music industry data, including streaming payouts and sample library copyright problems. He covers ways to tell whether a track is human-made.

Computerphile video in which Mike Pound explains a University of Maryland paper on watermarking LLM output. The method biases token choices so generated text can later be detected statistically.

Rob Miles discusses GPT-3 on Computerphile, covering how scaling parameters kept improving results over GPT-2 and how the model nearly learned arithmetic without anyone knowing exactly how.