MIT's Computer Science & Artificial Intelligence Laboratory (CSAIL). Media Inquiries: [email protected] Check out the latest CSAIL content ⬇️
Cambridge, MA
Joined October 2009
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Scientists have lacked the data to bring physical AI underwater. MIT CSAIL researchers are helping robots change that using sonar & ML approaches: tinyurl.com/3rpnhdkz
ETH Zurich recently taught a robotic hand to walk: bit.ly/4zePk4P
Its clever design & fluid motion reminded us of another walking hand: Thing from The Addams Family.
MIT CSAIL retweeted
Want genAI to make you a functional, real-world object? Good luck — their 3D models are often physically flawed & hard to edit.
New "InstructMesh" tool makes it easy to generate, tweak, & 3D print things that actually work, such as decor & medical devices: bit.ly/4z5L5bu
Back when calculators were a little more controversial, v/@JonErlichman.
AI is quickly improving at tough theory questions in math, physics, & economics.
In a new MIT study, frontier OpenAI models’ success rate rose from 3% to 35% in 16 months, while a successful attempt cost about $15. The new bottleneck may be verification: bit.ly/3UoRJee
MIT CSAIL retweeted
As humanoid robots become part of our everyday lives, they need to do more than just perform impressive motions. They should be safe, fun to interact with, and respond naturally to unexpected contact, without sacrificing performance.
Our latest work, Compliant GMT (C-GMT), brings whole-body compliant responses to general motion tracking.
🌐 More details: venki1899.github.io/c-gmt/
Work done at MIT Improbable AI Lab with @michl_wang, Jin, @pulkitology.
The late MIT prof. Patrick Winston explains how to speak & get your ideas valued & accepted.
The famous lecture in full: tinyurl.com/2p592kya
v/@MITOCW
Want genAI to make you a functional, real-world object? Good luck — their 3D models are often physically flawed & hard to edit.
New "InstructMesh" tool makes it easy to generate, tweak, & 3D print things that actually work, such as decor & medical devices: bit.ly/4z5L5bu
To give context on age:
Grace Hopper began computing at 38, completed the first compiler at 46, helped shape COBOL at 53, kept developing COBOL for the Navy in her 70s, retired from the Navy at 80, & then became a consultant for the Digital Equipment Corporation.
v/@cooperx86
MIT CSAIL retweeted
"DREAM" is an AI model from MIT & Meta that can both understand images & generate them from text — then judge its own rough drafts to finish the best one.
The result: stronger vision, better image quality, & ~10% faster generation w/external re-rankers: bit.ly/4hBJing
Wise words from Geoffrey Hinton: A PhD in computer science is worth it.
v/@samuelxzhang
Computer scientist Margaret Hamilton passed away at 90 on Sep. 30th. Considered an icon at MIT, she designed the flight software for the Apollo missions to the moon.
More on her groundbreaking work: bit.ly/4zegcS8
Video v/MAKERS
MIT CSAIL retweeted
Left: MIT computer scientist Katie Bouman w/stacks of hard drives of black hole image data.
Right: MIT computer scientist Margaret Hamilton w/the code she wrote that helped put a man on the moon.
(image credit @floragraham)
#EHTblackhole #BlackHoleDay #BlackHole
MIT CSAIL retweeted
We’ve lost an icon. Margaret Hamilton, a computer science pioneer best known for her work at MIT leading development of the flight software for the Apollo missions to the moon, has died at 90. Read about her legacy via MIT News: news.mit.edu/2026/margaret-h…
ALT Margaret Hamilton is reclined inside a NASA spacecraft module, surrounded by control panels and switches.
What happens when you put an AI coding assistant on an island?
MIT researchers put 13 agents in this digital space w/no task or reward. Over 30 hours, they invented challenges, experiments, sports, & art — & the skills they found helped them accomplish more later: bit.ly/4rQ2xOZ
MIT CSAIL retweeted
There’s lots of buzz around agentic harnesses for robots, particularly for long horizon tasks that require complex reasoning and memory. But what will it really take to turn a reasoning agent into a reactive, reliable and low-latency robot policy?
In our new paper, workspace models, we design a new memory architecture that acts as a latent harness for stronger reasoning models. Here’s why we think this might be the way forward:
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