Q&A: Climate change, tough tech startups, and the future of energy intelligence
MIT Energy Initiative Director Robert Armstrong offers his perspective on the takeaways from MITEI’s annual research conference.
MIT Task Force on the Work of the Future announces advisory and research boards
Leaders from industry, academia, labor, government, foundations, and other organizations, as well as leading scholars in related fields, will provide guidance.
Cryptographic protocol enables greater collaboration in drug discovery
Neural network that securely finds potential drugs could encourage large-scale pooling of sensitive data.
Tang family gift supports MIT.nano, MIT Quest for Intelligence
$20 million gift names imaging suite in new facility, creates catalyst fund.
Technique quickly identifies extreme event statistics
Machine-learning model provides risk assessment for complex nonlinear systems, including boats and offshore platforms.
MIT reshapes itself to shape the future
Gift of $350 million establishes the MIT Stephen A. Schwarzman College of Computing, an unprecedented, $1 billion commitment to world-changing breakthroughs and their ethical application.
Model helps robots navigate more like humans do
In simulations, robots move through new environments by exploring, observing, and drawing from learned experiences.
Regina Barzilay, James Collins, and Phil Sharp join leadership of new effort on machine learning in health
MacArthur “geniuses” in machine learning and synthetic biology to serve as faculty co-leads; Nobel laureate to chair advisory board of new research center.
3Q: David Simchi-Levi on advancing global retail operations through analytics and machine learning
David Simchi-Levi discusses insights from recent research in collaboration with some of the world's largest retailers.
Recognizing the partially seen
Advances in computer vision inspired by human physiological and anatomical constraints are improving pattern completion in machines.
Reducing false positives in credit card fraud detection
Model extracts granular behavioral patterns from transaction data to more accurately flag suspicious activity.
Machine-learning system tackles speech and object recognition, all at once
Model learns to pick out objects within an image, using spoken descriptions.