machine language

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.

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.

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.

Ian Piumarta's 2007 Stanford EE380 lecture on building a dynamic programming environment from the ground up, from the Viewpoints Research Institute's work. It covers the design of a language and system with a recursive design, parsing through code generation, and the COLA architecture.

Rob Miles explains on Computerphile how language models generate plausible text and how transformers improved on recurrent networks, with a look at what comes next.

Chris Lattner and Brennan Saeta present Swift for TensorFlow at the TensorFlow Dev Summit 2019, covering language-integrated automatic differentiation and tooling for machine learning in Swift.

A Curry On talk by Lars Bak, known for V8 and Dart, on building a secure and robust IoT development platform. It discusses language and VM design choices for small devices.

Julia co-creator Jeff Bezanson candidly lists fundamental problems with the language at JuliaCon 2019, including modularity, types and compiler latency, and how they might be solved.

Lex Fridman's long interview with Chris Lattner, creator of LLVM and Swift, covering the future of computing and programming languages. It touches on compilers, hardware, and his work at Apple, Tesla, Google and SiFive.

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.

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.

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 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.

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.

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.

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.

An episode of Tim Hunkin's The Secret Life of Machines that explains how a washing machine works, using models, cut-aways and animations. It was first aired in 1988.

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 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 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.

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.

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.

John Oliver's Last Week Tonight segment on US voting machines, covering how they work, their security weaknesses, and how elections could be made more secure.

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

A short excerpt of Rob Pike's Lang.NEXT 2014 talk where he describes Go's target audience as young Google programmers who are not researchers. The language has to be easy for them to understand and adopt.

Richard Feldman explains how pure functional languages can match or beat imperative ones on performance. Compilers can turn immutable code into in-place mutation, avoiding naive copying. The talk draws on his work on the Roc language.

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.

A 2023 LLVM Developers' Meeting keynote by Abdul Dakkak, Chris Lattner and Jeff Niu introducing Mojo, a Python-family systems language built on MLIR and LLVM for heterogeneous computing.

Pokey Rule presents Cursorless, a spoken language designed for editing code by voice, built on tree-sitter parsing with smart structural and simple token-level primitives. The talk is from Strange Loop 2023.

Dan Bornstein's Google I/O 2008 talk on the internals of Dalvik, the virtual machine that runs Android code. It covers the motivation for its design, the dex format and its register-based interpreter, plus tips for writing code that suits the platform.

Machine Thinking argues the 1751 machine, a metal-cutting lathe associated with Vaucanson, triggered the biggest explosion of wealth in history by enabling precise manufacturing of other machines.

Andrew Kelley, creator of Zig, introduces the language at the Recurse Center's Localhost series in 2018. He covers its goals of robustness, optimality and clarity, C interop, cross-compilation and explicit allocators.