Chip design drastically reduces energy needed to compute with light
Simulations suggest photonic chip could run optical neural networks 10 million times more efficiently than its electrical counterparts.
Preliminary reports examine options for MIT Schwarzman College of Computing
Working groups identify key ideas for new college; period of community feedback continues.
Cracking open the black box of automated machine learning
Interactive tool lets users see and control how automated model searches work.
Q&A: Phillip Isola on the art and science of generative models
Image-translation pioneer discusses the past, present, and future of generative adversarial networks, or GANs.
Teaching language models grammar really does make them smarter
Researchers submit deep learning models to a set of psychology tests to see which ones grasp key linguistic rules.
3 Questions: The social implications and responsibilities of computing
In helping envision the MIT Schwarzman College of Computing, working group is focusing on ethical and societal questions.
3 Questions: Faculty appointments and the MIT Schwarzman College of Computing
Working group studies options for creating a new set of faculty hires for MIT’s new college.
Developing artificial intelligence tools for all
MIT Quest for Intelligence-sponsored undergraduate research projects demystify AI.
Bringing human-like reasoning to driverless car navigation
Autonomous control system “learns” to use simple maps and image data to navigate new, complex routes.
This robot helps you lift objects — by looking at your biceps
CSAIL system can mirror a user's motions and follow nonverbal commands by monitoring arm muscles.
MIT Policy Hackathon connects data-driven problem solvers
Interdisciplinary teams propose creative policy solutions addressing societal challenges at the Institute for Data, Systems, and Society student-organized event.
How to tell whether machine-learning systems are robust enough for the real world
New method quickly detects instances when neural networks make mistakes they shouldn’t.
Painting a fuller picture of how antibiotics act
Machine learning reveals metabolic pathways disrupted by the drugs, offering new targets to combat resistance.
Using AI to predict breast cancer and personalize care
MIT/MGH's image-based deep learning model can predict breast cancer up to five years in advance.
Smarter training of neural networks
MIT CSAIL project shows the neural nets we typically train contain smaller “subnetworks” that can learn just as well, and often faster.