An easier way to get bugs out of programming languages
Developed at MIT, D2X is a new tool that makes it easy to debug any domain-specific programming language.
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Creating a versatile vaccine to take on Covid-19 in its many guises
Aided by machine learning, scientists are working to develop a vaccine that would be effective against all SARS-CoV-2 strains.
Putting clear bounds on uncertainty
Computer scientists want to know the exact limits in our ability to clean up, and reconstruct, partly blurred images.
This is your brain. This is your brain on code
MIT researchers are discovering which parts of the brain are engaged when a person evaluates a computer program.
Subtle biases in AI can influence emergency decisions
But the harm from a discriminatory AI system can be minimized if the advice it delivers is properly framed, an MIT team has shown.
The task of magnetic classification suddenly looks easier
MIT undergraduate researchers Helena Merker, Harry Heiberger, and Linh Nguyen, and PhD student Tongtong Liu, exploit machine-learning techniques to determine the magnetic structure of materials.
A new twist on old-school animation
MIT researchers create KineCAM, an instant camera that yields images that appear to move.
Seeing the whole from some of the parts
A new technique in computer vision may enhance our three-dimensional understanding of two-dimensional images.
Q&A: Chris Rackauckas on the equations at the heart of practically everything
Have a question about numerical differential equations? Odds are this CSAIL research affiliate has already addressed it.
Robots dress humans without the full picture
MIT researchers design a robot that has a trick or two up its sleeve.
Seeing an elusive magnetic effect through the lens of machine learning
An MIT team incorporates AI to facilitate the detection of an intriguing materials phenomenon that can lead to electronics without energy dissipation.
A new programming language for high-performance computers
With a tensor language prototype, “speed and correctness do not have to compete ... they can go together, hand-in-hand.”
The downside of machine learning in health care
Assistant Professor Marzyeh Ghassemi explores how hidden biases in medical data could compromise artificial intelligence approaches.
Invisible machine-readable labels that identify and track objects
An MIT team develops 3D-printed tags to classify and store data on physical objects.
The promise and pitfalls of artificial intelligence explored at TEDxMIT event
MIT scientists discuss the future of AI with applications across many sectors, as a tool that can be both beneficial and harmful.