language learning

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.

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

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.

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.

Veritasium debunks the idea of learning styles, such as being a visual learner, with an interview with Daniel Willingham and a memory experiment. It argues that a multimodal approach helps everyone.

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.

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.

The Map Men explain why British place names are so hard to pronounce, tracing it to layers of Viking, Anglo-Saxon, Celtic and Norman influence, with a pronunciation guide.

Linguist Simon Roper reconstructs how a London accent would have sounded from the 14th to the 21st centuries, reading passages in period pronunciation. It draws on the Cambridge History of the English Language.

Tom Scott explains why subtitles often differ from dubbed dialogue, covering how translation, timing and reading speed shape each. It features translators and voice talent working in several languages.

Veritasium examines which experts have real expertise, drawing on chess research and work by Klein and Kahneman. It explains that expertise comes from pattern recognition built through deliberate practice in valid, feedback-rich environments.

Dialect coach Erik Singer tours a range of accents across North America with linguists in Part 2 of WIRED's accent series. It covers regional distinctions such as Southern Mississippi, Miami and Utah English.

Linguist Geoff Lindsey explores vocal fry: what it is, who uses it, how it relates to glottal stops and accents, and why some people dislike it.

Dialect coach Erik Singer and several linguists tour distinct accents across English-speaking North America. It is the first part of a WIRED series on US accents.

CGP Grey explains why airport codes are inconsistent and sometimes confusing, from their origins in old weather station codes to the quirks that cause mistakes. He builds the story around a single typo that sent a flight to the wrong continent.

CGP Grey investigates why the name Tiffany spiked in popularity and then faded, with help from onomastics experts. It is a short, playful look at how names spread.

Tom Scott explains Gricean maxims, the unwritten guidelines that shape how we understand each other. He uses examples such as why 'asbestos-free cereal' sounds suspicious.

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 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.

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.

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.

An animated introduction to geometric algebra, presented as a language that can describe most of physics. It was made with manim and covers multivectors and how they generalize familiar tools like cross products and quaternions.

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.

A Veritasium video on how a feud between Russian mathematicians led to Markov chains and the modern prediction algorithms built on them. It covers the history and the math behind them.

Steve Mould shows Spintronics, a set of mechanical components such as resistors, capacitors and transistors linked by chains, that give an intuitive feel for how electrical circuits work.

Geekerwan's Chinese-language review of Intel's Lunar Lake lightweight laptop chip, covering performance, perf-per-watt curves and battery life benchmarks. It tests whether x86 can compete on efficiency.