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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.

Branch Education's animated deep dive into ASML's EUV photolithography machine and how it prints nanometer-scale transistors onto chips. It covers the system's components and the process of chip manufacturing.

Veritasium explains how ASML's EUV lithography machines make the most advanced computer chips, covering the engineering of the light source, mirrors and the supply chain around them. It is a long-form explainer on the world's most complex commercial machine.

Wes Bos breaks down the techniques behind the McMaster-Carr website's speed: server-rendered HTML, prefetching, CDN and service worker caching, preloading, critical CSS and fixed-size images. He also notes its old-school jQuery and YUI JavaScript.

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.

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

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.

A 36-minute animated deep dive from Branch Education into how DRAM works. It shows how memory connects to the CPU and how billions of bits are stored in nanoscale capacitor cells. It also covers why DRAM sits between SSDs and the processor.

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.

Aaron Francis walks through how PHP has changed from 2012 to 2023, covering traits, array destructuring, generators, typed properties and more. It is a quick chaptered tour of modern PHP features.

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 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.

Asianometry explains why Russia cannot replace TSMC after sanctions halted chip shipments. It looks at Russian chip designers such as Baikal, MCST and Yadro, and at Russia's lagging domestic manufacturing capacity.

Asianometry explains that the worst of the 2021-22 chip shortage sits in trailing-edge semiconductors, not the leading-edge chips usually covered. It covers why those older-node fabs are so hard to expand and fix.

Asianometry's short analysis of SMIC's N+2 node, China's 7nm leap forward. It considers how far behind the competition SMIC still is.

Branch Education walks through a semiconductor fab and the dozens of steps used to turn silicon wafers into microchips, with 3D animation. It covers lithography, deposition and etching at a high level.

Asianometry explains why India, a chip design powerhouse, cannot fabricate chips, tracing the 1980s government attempt to build a national semiconductor champion and how it collapsed. It includes the sabotage at the SCL fab.

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.

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's video whose title shows its own live view count, and the story of how he made that work. It explains why open APIs were once common and why they largely disappeared.

2swap explores lambda calculus using John Tromp's lambda diagrams, with animated beta-reductions, asking what PLUS times PLUS gives. It touches on Church encodings and the equivalence of Turing machines and lambda calculus.

Asianometry traces the 30-year rise and peak of Japan's semiconductor industry from the 1950s to the 1980s, covering how a postwar country gained competence in an emerging technology.

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.

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.

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.

Answer in Progress investigates why Japanese websites look different from those elsewhere, using an AI clustering approach to test the 2013 claim. It then looks at possible explanations.