stack 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.

Andrej Karpathy's Databricks talk on Software 2.0, the shift from human-written code to code produced by neural network training. It covers how developer work moves toward curating datasets, the advantages and challenges, and opportunities for new tooling.

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.

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

A five-minute demo of the Common Lisp debugger fixing a bug, recompiling a single function, and resuming execution from the failed stack frame. It shows how to avoid re-running long computations.

A short Dyalog demonstration building Conway's Game of Life in a single line of APL, step by step. It shows how array operations replace loops.

An episode of jan Misali's Conlang Critic series reviewing Toki Pona, a minimalist constructed language with about a hundred words. It is a short, humorous critique of the language's design.

Gary Bernhardt argues that software history moves in reactions to earlier tools, and that new tools are not simply better in every way. He distinguishes capability (what a tool allows) from suitability (what it fits), and warns against repeating past mistaken reactions.

A 12-minute film in which Erlang's creators demonstrate the language's fault tolerance and live-system features, including phoning each other to show it working. This version has fixed audio.

A short clip of Simon Peyton Jones talking about the future of programming languages, saying Haskell is useless in the sense that pure programs cannot have effects, while mainstream languages are useful but unsafe. He describes languages converging, with ideas such as STM and LINQ moving between them.

Leandro Facchinetti explains why he thinks Racket is a great language and why he stopped using it. He describes his backstory and experiences with the Racket community.

Jiahao Chen's JuliaCon 2017 talk argues that vector transposes should be taken seriously in type systems and linear algebra libraries. It explains why treating vectors as matrices causes trouble in languages.

Luis von Ahn, creator of CAPTCHA and reCAPTCHA, explains how small contributions from many people online can digitize books. He then introduces Duolingo as a way to translate the web while people learn languages.

Vox explains the Berlin and Kay research showing that languages around the world tend to invent color words in the same order. It walks through the hierarchy and the debate around it.

A 13-minute OSCON 2010 talk in which Rob Pike argues about what is wrong with mainstream languages like C++, Java and C#, and presents Go as a response. He discusses verbosity and what lightness means in a language.

Yuta, a Japanese YouTuber, explains whether Japanese speakers can read Chinese text. He shows how shared kanji let people guess meanings while the two languages remain completely different.

'Skwerl' is a short film by Brian and Karl made entirely in fake English, imitating how English sounds to people who don't speak it. It was made for Kino Sydney and shown on QI.

A short parody sketch of a job interview with a senior JavaScript developer, poking fun at the JS ecosystem and trendy stacks.

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.

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

Yegor Denisov-Blanch of Stanford presents a study of nearly 100,000 developers at hundreds of companies, measuring how AI affects productivity from commit data. It finds an average boost of about 20% with wide variance by codebase, task complexity and stack.