Artificial intelligence system rapidly predicts how two proteins will attach
The machine-learning model could help scientists speed the development of new medicines.
Preparing global online learners for the clean energy transition
MIT Energy Initiative edX course asks students to rethink how we operate power systems.
Invisible machine-readable labels that identify and track objects
An MIT team develops 3D-printed tags to classify and store data on physical objects.
Tiny materials lead to a big advance in quantum computing
Using ultrathin materials to reduce the size of superconducting qubits may pave the way for personal-sized quantum devices.
Demystifying machine-learning systems
A new method automatically describes, in natural language, what the individual components of a neural network do.
Deploying machine learning to improve mental health
MIT scientist Rosalind Picard collaborates with clinicians to develop tools for mental health care delivery.
Cynthia Breazeal named dean for digital learning at MIT
Overseeing business and research units across MIT Open Learning, Breazeal will focus on the future of digital technologies and their applications in education.
A new language for quantum computing
Twist is an MIT-developed programming language that can describe and verify which pieces of data are entangled to prevent bugs in a quantum program.
Seeing into the future: Personalized cancer screening with artificial intelligence
Scientists demonstrate that AI-risk models, paired with AI-designed screening policies, can offer significant and equitable improvements to cancer screening.
Brave Behind Bars: Prison education program focuses on computing skills for women
MIT computer scientists and mathematicians offer an introductory computing and career-readiness program for incarcerated women in New England.
When should someone trust an AI assistant’s predictions?
Researchers have created a method to help workers collaborate with artificial intelligence systems.
Reasserting US leadership in microelectronics
MIT researchers lay out a strategy for how universities can help the US regain its place as a semiconductor superpower.
How well do explanation methods for machine-learning models work?
Researchers develop a way to test whether popular methods for understanding machine-learning models are working correctly.
Q&A: Dolapo Adedokun on computer technology, Ireland, and all that jazz
MIT EECS student and Mitchell Scholar hopes to play music in Dublin while working on his MS in intelligent systems.
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.