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A Technology Connections video on how ground-source (geothermal) heat pumps work and why they hold efficiency in winter. It also covers related heat pump information, and the description notes air-source heat pumps have since improved.

Technology Connections explains what forced-air furnaces are, how they work and why they need electricity. He covers combustion, airflow and the parts of a modern furnace.

Asianometry explains the EUV light source inside ASML's lithography machines, where lasers hit falling tin droplets twice to produce 13.5 nm light. It walks through the engineering of the droplet generator, the pre-pulse and main laser, and the plasma that results.

Kaze Emanuar explains how he rewrote and optimized the Super Mario 64 source code so it runs far faster on real N64 hardware. He covers performance bottlenecks and fixes in detail for his ROM hacks.

Yosh trains a reinforcement learning agent to drive Trackmania until he can no longer beat it. The video explains how the training works and the design choices involved.

Vsauce explores whether people in past decades really looked older than people of the same age today, or whether photographic and cultural factors make them seem so. It draws on old photos, yearbooks and perception research.

Tantacrul explains how he and engraver Simon Smith designed the free music notation font for MuseScore 3.6. It draws on the history of the SCORE notation application by Leland Smith.

Technology Connections explains why brown is not a spectral color but a context-dependent perception, essentially dark orange seen against brighter surroundings.

Robert Miles covers a paper where researchers ran real versions of his earlier mesa-optimizer thought experiments. They show inner misalignment, where an AI learns the wrong goal in training and misbehaves when deployed.

Matt Parker of Stand-up Maths examines scatter plots that were claimed to show fraudulent vote-switching in Michigan's 2020 election. He recreates the analysis and shows that the pattern arises from comparing percentages across different bases, not from fraud.

Captain Disillusion's comedic, fast-paced explainer on how color works in cameras, displays and video. It covers the biology of color perception and what it means for screens.

A Technology Connections video essay on how analog and digital clocks shape different mental models of time, with the minute hand acting as a progress indicator.

8-Bit Show And Tell walks through the BASIC source code of the original Commodore 64 Sid Meier's Pirates!. It covers bugs, quirks and traces of abandoned features and scenarios left in the code.

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

Huygens Optics explains the Fourier transform and shows how a lens performs one optically. A DLP projector is used as a Fourier filter to do simple pattern recognition on lithographic character patterns.

Veritasium explains why analog computing may suit AI workloads, covering old analog computers, The Analog Thing and Mythic's analog chips that use flash memory for neural network inference. It argues digital hardware is hitting limits.

Benn Jordan explains how Flock Safety's license plate cameras log and share vehicle locations, and explores how adversarial AI can defeat them. It covers weak security and the surveillance risks of private police-camera networks.

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.

Adam Neely explains what perfect (absolute) pitch is, how it differs from relative and quasi-absolute pitch, and why he would not want it. He covers its drawbacks, including drift with age.

A Computerphile video in which Dr Mike Pound and PhD student Lewis Stuart explain 3D Gaussian splatting, a quick technique that turns photos of a scene into a 3D model without much compute. It includes a demo and compares the approach to NeRFs.

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.

A Veritasium video on AlphaFold, DeepMind's protein structure prediction system, and the protein design work it enabled. It features interviews with John Jumper and with David Baker's protein design group and explains why predicting protein folding matters.

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.

Engineering Explained examines new research suggesting corn ethanol in US gasoline may emit as much or more carbon than gasoline. It covers the Renewable Fuel Standard and why ethanol was assumed to be a green fuel.

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.

Vsauce explores how human reasoning works, drawing on the social theory of reason and the extended mind thesis, made in partnership with Bill Gates around climate change.

PBS Space Time examines Roger Penrose's idea that consciousness arises from quantum processes in the brain, and reviews new evidence about microtubules. It ends with an estimate of what replicating consciousness would demand.

Sabine Hossenfelder explains superdeterminism as an interpretation of quantum mechanics, addressing common objections and misconceptions, including the worry that it kills free will or science. She ties it to Bell's theorem and hidden variables.

Tom 7 (suckerpinch) delivers a long, comedic digression on gradient descent and floating-point imprecision. He shows how rounding behavior can supply the nonlinearity needed to build a neural network.

Tom Scott, with linguists Gretchen McCulloch and Molly Ruhl, examines whether the language you speak changes how you think. The short answer is mostly no, with caveats about the weak version of the Sapir-Whorf hypothesis.

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.

Harvard professor Arthur Brooks explains why boredom is useful rather than something to avoid. He describes how a wandering mind engages the brain's default mode network, which supports creativity and curiosity, and suggests it may protect against depression.

Steve Mould explains motion amplification and video magnification, techniques that find tiny changes in video invisible to the eye and exaggerate them. He covers the MIT research and industrial uses such as diagnosing vibrating machinery.

FortNine looks at why Tesla Autopilot has rear-ended motorcyclists, speculating that the vision system misreads motorcycle taillights as a distant car. It argues that radar and other sensors would help.

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.

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 Climate Town video on how the auto industry reshaped American cities and culture through advertising, lobbying and campaigns like the 1939 World's Fair. It is snarky in tone but backed by a published source document.

Wendover Productions explains how UK rail privatization worked and why it failed. It covers the fragmented operator and infrastructure structure and why market forces apply poorly to rail.

Yuta explains what Japan's 99% conviction rate actually means, noting that prosecutors drop cases unless confidence is very high. He argues that the number is widely misunderstood and cites his sources.

This Place argues that the uncanny valley is a flawed concept, since 'human likeness' is too broad and the supporting evidence is cherry-picked. It proposes that the creepiness really comes from how animated characters and robots move.