MIT CSAIL
@MIT_CSAIL
MIT's Computer Science & Artificial Intelligence Laboratory (CSAIL). Media Inquiries: [email protected] Check out the latest CSAIL content ⬇️
Can AI actually code for us? 🧵 MIT research reveals there’s a "long way to go" due to bottlenecks like assessment, codebase scale, & incorrect retrievals. The work reflects a vision to let humans focus on high-level design while routine work is automated:…
"Programming is not about typing, it's about thinking." — Rich Hickey v/@CodeWisdom
MIT CSAIL's "PhysicsGen" system helps robots handle items efficiently by customizing & multiplying the data they train on. It turns a few VR demonstrations into thousands of simulations, potentially helping build huge datasets for dexterous robots: bit.ly/4nJl6ln
A report card grading the safety of leading AI model-makers, v/@FLI_org: bit.ly/3IyJcz9 Anthropic topped the list w/a C+, while DeepSeek scored lowest w/an F.
We are so excited to share that 6.1200J Mathematics for Computer Science is now ready and waiting for you! Watch the videos on YouTube: bit.ly/4lHxiSl Taught by Prof. Erik Demaine, Dr. Zachary Abel, and Dr. Byrnmor Chapman, this course covers elementary discrete…
How X looked when it launched, 19 years ago this month. It was originally branded as "twttr" after co-founder Noah Glass came across the word in a dictionary: bit.ly/4eUseY1
A new handheld interface from MIT gives anyone the ability to train a robot for tasks in fields like manufacturing. The versatile tool can teach a robot new skills using one of three approaches: natural teaching, kinesthetic training, & teleoperation: bit.ly/4nTAw6F
56 years ago today, humans walked on the moon for the first time. Original @TIME report of the monumental event, from 1969: bit.ly/3UbKiTP
The Fibonacci sequence in Pascal's Triangle, v/@TheMathFlow.
Hello world! This is @nishanthkumar23 and I'll be taking over @MIT_CSAIL 's X/Twitter & Instagram for 24 hours! I'm a 4th year PhD @MITEECS working on AI/ML for Robotics and Computer Agents. Drop any and all questions about research, AI, MIT, or dogs (esp. robot dogs!) below 👇
A new approach from CSAIL & Google marks a shift toward teaching models to orchestrate their own parallel decoding strategy. The team's "Parallel Structure Annotation" (PASTA) enables LLMs to generate text in parallel, accelerating their response times: bit.ly/4eDsVVo
