Using machine learning to hunt down cybercriminals
Model from the Computer Science and Artificial Intelligence Laboratory identifies “serial hijackers” of internet IP addresses.
A new mathematical approach to understanding zeolites
Study of minerals widely used in industrial processes could lead to discovery of new materials for catalysis and filtering.
3 Questions: How artificial intelligence is supercharging materials science
Associate Professor Juejun Hu shines a light on the impact machine learning and AI are having on materials science and engineering.
System helps smart devices find their position
Connected devices can now share position information, even in noisy, GPS-denied areas.
Lincoln Laboratory's new artificial intelligence supercomputer is the most powerful at a university
TX-GAIA is tailor-made for crunching through deep neural network operations.
Machine learning you can dance to
MIT grad student startup Samply uses algorithms to help music producers find the perfect sound.
Notation system allows scientists to communicate polymers more easily
BigSMILES language allows computers and researchers to convey stochastic configurations more clearly.
What a little more computing power can do
Commercial cloud service providers give artificial intelligence computing at MIT a boost.
Detecting patients’ pain levels via their brain signals
System could help with diagnosing and treating noncommunicative patients.
Computing in Earth science: a non-linear path
UROP student Sonia Reilly studies the math of machine learning to improve predictions of natural disasters.
MIT report examines how to make technology work for society
Task force calls for bold public and private action to harness technology for shared prosperity.
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.
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.
Automating artificial intelligence for medical decision-making
Model replaces the laborious process of annotating massive patient datasets by hand.