Computing in Earth science: a non-linear path
UROP student Sonia Reilly studies the math of machine learning to improve predictions of natural disasters.
Objects can now change colors like a chameleon
Computer Science and Artificial Intelligence Laboratory team creates new reprogrammable ink that lets objects change colors using light.
MIT’s fleet of autonomous boats can now shapeshift
New capabilities allow “roboats” to change configurations to form pop-up bridges, stages, and other structures.
MIT engineers build advanced microprocessor out of carbon nanotubes
New approach harnesses the same fabrication processes used for silicon chips, offers key advance toward next-generation computers.
IBM gives artificial intelligence computing at MIT a lift
Nearly $12 million machine will let MIT researchers run more ambitious AI models.
Artificial intelligence could help data centers run far more efficiently
MIT system “learns” how to optimally allocate workloads across thousands of servers to cut costs, save energy.
A battery-free sensor for underwater exploration
Submerged system uses the vibration of “piezoelectric” materials to generate power and send and receive data.
Boosting computing power for the future of particle physics
Prototype machine-learning technology co-developed by MIT scientists speeds processing by up to 175 times over traditional methods.
Using Wall Street secrets to reduce the cost of cloud infrastructure
“Risk-aware” traffic engineering could help service providers such as Microsoft, Amazon, and Google better utilize network infrastructure.
Study measures how fast humans react to road hazards
In “semiautonomous” cars, older drivers may need more time to take the wheel when responding to the unexpected.
Computer-aided knitting
New research from the Computer Science and Artificial Intelligence Laboratory uses machine learning to customize clothing designs.
Automating artificial intelligence for medical decision-making
Model replaces the laborious process of annotating massive patient datasets by hand.
Model predicts cognitive decline due to Alzheimer’s, up to two years out
Researchers hope the system can zero in on the right patients to enroll in clinical trials, to speed discovery of drug treatments.