language learning

Chris Lonsdale presents a TEDx talk on how adults can learn a language in about six months, centering on immersion, comprehensible input and a practical learning methodology.

A 15-minute clip of linguist Stephen Krashen discussing language acquisition, drawn from the 1980s. It presents his input hypothesis and the distinction between acquisition and learning.

A lecture from the 1980s by linguist Stephen Krashen on how people acquire language. He explains his comprehensible input hypothesis for second-language acquisition.

The first lecture of Stanford's Natural Language Processing with Deep Learning course, taught by Chris Manning and Richard Socher. It introduces NLP and word vectors, including SVD, skip-gram, CBOW, negative sampling and word2vec.

Bassist Victor Wooten argues that music should be learned the way children learn their first language: by immersion and play, without early correction or rigid academic instruction. He draws on how babies pick up speech from the people around them.

Robert Sapolsky's Stanford lecture on language, comparing human and animal communication, ape language projects like Koko and Kanzi, and how language is acquired. It is part of his human behavioral biology course.

A George Carlin stand-up bit from Doin' It Again about soft language and euphemism, showing how softened words hide uncomfortable facts. It touches on topics like shell shock and aging.

A Polish linguist tests whether speakers of Bulgarian, Polish and Croatian can understand Interslavic, a constructed language built from Slavic languages. It shows how well they follow it without prior study.

A sketch from the Norwegian NRK show Uti Var Hage poking fun at the Danish language and how hard it is to understand.

Finnish comedian Ismo does a stand-up routine on Conan about the many meanings of the English word 'ass'. He riffs on the confusing quirks of English as a second language.

Machine Learning Street Talk interviews Paul Lessard about Categorical Deep Learning, which uses category theory and monads to make neural network architectures more interpretable and composable. They also discuss neural networks' limits in reasoning and unbounded computation.

A kinetic typography animation set to Stephen Fry's spoken essay on language. Fry argues against grammar pedantry and for the way language evolves, including the verbing of nouns.

Finnish YouTuber Saara improvises gibberish that mimics how various languages sound to people who do not speak them. The sentences are mostly made up, and the clip went viral.

Noam Chomsky talks with the University of Washington's Upon Reflection about how languages change over time, why a national language is a modern idea, and how language is a system of communication rooted in human nature.

Lex Fridman interviews MIT psycholinguist Edward Gibson on human language, syntax, grammar and how large language models relate to them. The conversation runs nearly three hours.

A clip from George Carlin's 1990 special 'Doin' It Again' in which he describes how American English has been sterilized with euphemisms, using examples such as shell shock becoming PTSD.

A Fry and Laurie sketch about language, full of absurd phrases and wordplay, which also plays on the distinction between langue and parole.

Noam Chomsky gives a Talks at Google lecture covering his work on politics and language. It touches on his linguistic theory, including universal grammar, alongside his political criticism.

Guy Steele's 1998 OOPSLA keynote on designing a programming language that its users can grow. He builds the talk using only one-syllable words and terms he has defined, to demonstrate the idea.

The first lecture of Andrew Ng's Stanford CS229 Machine Learning course, giving an overview of the course. It introduces supervised and unsupervised learning, learning theory and reinforcement learning.

Jonathan Blow's first talk on designing a new programming language for games, which became Jai. He explains the problems with C++ and why Go, Rust and D do not fit game development.

Andrew Ng presents unsupervised feature learning and deep learning, showing how algorithms can learn representations from unlabeled data instead of hand-designed features. He gives examples in vision and audio, including visualizations of features learned by successive layers.

Evan Czaplicki, creator of Elm, examines how programming languages are funded. He looks at where compiler engineers' salaries come from, why Go has about 5 engineers while Dart has about 30, and how this limits language design.

Guy Steele's classic 1998 OOPSLA keynote on how a programming language must grow with its user community. He delivers it in a playful style, starting with only monosyllabic words and defining new terms as he goes.

Valve's John McDonald presents at GDC 2018 on how Valve uses deep learning (VACnet) to detect cheaters in Counter-Strike: Global Offensive. He covers training on human-reviewed replays and how model output is confirmed by manual review.

A SXSW talk by W Watson that uses Lacanian psychoanalysis, with nods to Zizek, to critique popular programming languages. It argues that people choose and defend languages for emotional and ideological reasons rather than rational ones.

Shriram Krishnamurthi's PWLConf 2019 talk on the formal notion of expressive power of programming languages, based on Felleisen's paper. It explains how to tell when a feature adds power by whether emulating it requires global rewriting.

The first episode of Google's Machine Learning Recipes series. It introduces machine learning and builds a first supervised-learning classifier in about six lines of Python using scikit-learn.

A GDC 2018 talk by Valve's John McDonald on VACNet, a deep learning system that analyzes CS:GO gameplay to detect cheaters. It covers how the model is trained on human-reviewed Overwatch cases and how its output feeds human moderation.

Stephen Wolfram gives a 13-minute tour of the Wolfram Language, a symbolic, functional programming language with a built-in knowledgebase. He demos querying large datasets, interactivity and deployment.

Max Tegmark's MIT CBMM talk on why deep learning works so well. He argues that the laws of physics and the symmetries in physical data make it compressible into small neural networks, tying physics to network structure.

Mark Rober and Jabril build an app that uses machine learning to decode baseball sign sequences. The video also explains neural networks in a simple, accessible way.

Brian Kernighan gives a talk at the University of Nottingham on how to succeed in language design without really trying. He draws on his experience with awk and other languages.

Michael Arntzenius's Strange Loop talk on Datafun, a functional query language that brings database-style querying into a general-purpose language. It discusses bridging database theory and programming languages.

A 10-minute clip from a Jonathan Blow Twitch stream in which he argues that game engines do not really need separate scripting languages. He questions the value of embedded interpreters when the main language can do the job.

Jonathan Blow demos his prototype programming language, covering the base language and compile-time execution, including running a game while compiling. The video is about 70 minutes of demo followed by Q&A.

Dwarkesh Patel interviews Andy Matuschak on how he learns, why memorization matters for understanding, and why most learning tools fail. The conversation also covers handling confusion and the role of tutoring.

Paul Biggar's Google Tech Talk on compiling and optimizing scripting languages, drawn from his work on the phc ahead-of-time PHP compiler. He covers runtime typing, aliasing and code generation challenges, and argues AOT can compete with JIT.

Rob Pike's October 2009 Google Tech Talk introducing Go, a new experimental systems language designed for fast builds, concurrency and garbage collection. It covers the goals, syntax and type system.

An animated ranking of the most popular programming languages from 1965 to 2019, built from popularity indexes, GitHub access data and historical surveys.