MIT CSAIL

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MIT's Computer Science & Artificial Intelligence Laboratory (CSAIL). Media Inquiries: [email protected] Check out the latest CSAIL content ⬇️

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MIT CSAIL

Shorts

MIT CSAIL was founded #otd in 1963 as "Project MAC."

MIT researchers taught a robot dog to perceive a 3D world using Neural Volumetric Memory (NVM). This technique lets the bot climb stairs, step over gaps &amp; run autonomously w/a single neural network. Paper: Video: w/UC San Diego

Barrier-grid animations are a clever way to create a moving picture that doesn’t actually move — w/o electronics. MIT's "FabObscura" software helps you produce bolder designs for these displays, which can be attached to objects in homes, stores, &amp; more:

Videos

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Andrej Karpathy, Eureka Labs founder &amp; former Director of AI at Tesla, breaks down how LLMs like ChatGPT "download the Internet." Watch the full beginner-friendly breakdown here:

MIT PhD student Alex Zhang (alex zhang) explains how AI models are "mismanaged geniuses" that could take on a much wider range of tasks. Full video:

Do-it-all robots aren't ready for our homes. Scientists at MIT &amp; beyond think compliance might change that:

Free MIT course that covers tools &amp; technologies that are assumed, but rarely taught, in most CS programs &amp; software engineering jobs, like Bash, git, &amp; AI tools:

14 sorting algorithms in just 60 seconds. v/tetsuo //: 👾

A free MIT course breaking down fundamental math concepts in computer science: Here, MIT prof. Erik Demaine breaks down state machines (Lecture 4). v/MIT OpenCourseWare

60 years ago this month, the Fast Fourier Transform was created, a powerful tool for image compression &amp; data analysis. Watch a classic MIT breakdown of FFT, perhaps the most-taught algorithm at the Institute: v/MIT OpenCourseWare

An MIT introduction to computer science &amp; Python programming:

#otd in 1980 a Japanese computer scientist published a paper proposing the “Neocognitron,” the neural net that directly inspired CNNs: Kunihiko Fukushima’s paper explained back in 1986:

A free MIT course about deep learning, 2026 edition: Here, MIT CSAIL researcher Alexander Amini discusses the differences between supervised, unsupervised, &amp; reinforcement learning approaches (Lecture 5).

A free MIT course about building scalable &amp; high-performance software systems: (v/MIT OpenCourseWare) Here, MIT prof. &amp; CSAIL principal investigator Charles Leiserson discusses why performance matters in computing (Lecture 1).

A free 30-minute guide to mastering Claude Code:

Free MIT course breaks down deep learning: Here, MIT ass't prof. Sara Beery discusses how it's driven breakthroughs in areas like image generation, coding, &amp; playing games (Lecture 1).

The MIT paper that showed space can be more powerful than time in computers. Full video:

A free MIT course breaking down mathematics for computer science &amp; engineering: (v/MIT OpenCourseWare) Here, MIT prof. Tom Leighton, who is also the CEO &amp; co-founder of Akamai, discusses what a proof is (Lesson 1).

Is there a "secret sauce" driving the development of AI models? FutureTech researchers at MIT CSAIL found that at the frontier, sheer scale drives LLM performance, but proprietary techniques &amp; algorithmic advances matter more away from it:

The story of Mirai, MIT's AI model that can detect breast cancer years before humans do:

A decade of imaging. Compressed into three months. Here’s how MIT CSAIL &amp; Harvard taught an electron microscope to see like you do:

A breakdown of the simplest neural network from the late MIT Prof. Patrick Winston during his 6.034 (Artificial Intelligence) course. Clip v/tetsuo //: 👾

The early days of Amazon — a company now valued at ~$2.4 trillion. v/Jon Erlichman

MIT researchers taught a robot dog to perceive a 3D world using Neural Volumetric Memory (NVM). This technique lets the bot climb stairs, step over gaps & run autonomously w/a single neural network. Paper: Video: w/UC San Diego

Barrier-grid animations are a clever way to create a moving picture that doesn’t actually move — w/o electronics. MIT's "FabObscura" software helps you produce bolder designs for these displays, which can be attached to objects in homes, stores, & more:

Andrej Karpathy, Eureka Labs founder & former Director of AI at Tesla, breaks down how LLMs like ChatGPT "download the Internet." Watch the full beginner-friendly breakdown here:

Do-it-all robots aren't ready for our homes. Scientists at MIT & beyond think compliance might change that:

Free MIT course that covers tools & technologies that are assumed, but rarely taught, in most CS programs & software engineering jobs, like Bash, git, & AI tools:

60 years ago this month, the Fast Fourier Transform was created, a powerful tool for image compression & data analysis. Watch a classic MIT breakdown of FFT, perhaps the most-taught algorithm at the Institute: v/MIT OpenCourseWare

An MIT introduction to computer science & Python programming:

A free MIT course about deep learning, 2026 edition: Here, MIT CSAIL researcher Alexander Amini discusses the differences between supervised, unsupervised, & reinforcement learning approaches (Lecture 5).

A free MIT course about building scalable & high-performance software systems: (v/MIT OpenCourseWare) Here, MIT prof. & CSAIL principal investigator Charles Leiserson discusses why performance matters in computing (Lecture 1).

Free MIT course breaks down deep learning: Here, MIT ass't prof. Sara Beery discusses how it's driven breakthroughs in areas like image generation, coding, & playing games (Lecture 1).

A free MIT course breaking down mathematics for computer science & engineering: (v/MIT OpenCourseWare) Here, MIT prof. Tom Leighton, who is also the CEO & co-founder of Akamai, discusses what a proof is (Lesson 1).

Is there a "secret sauce" driving the development of AI models? FutureTech researchers at MIT CSAIL found that at the frontier, sheer scale drives LLM performance, but proprietary techniques & algorithmic advances matter more away from it:

A decade of imaging. Compressed into three months. Here’s how MIT CSAIL & Harvard taught an electron microscope to see like you do: