Machines that learn language more like kids do
Computer model could improve human-machine interaction, provide insight into how children learn language.
Model paves way for faster, more efficient translations of more languages
New system may open up the world’s roughly 7,000 spoken languages to computer-based translation.
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.
How should autonomous vehicles be programmed?
Massive global survey reveals ethics preferences and regional differences.
Tang family gift supports MIT.nano, MIT Quest for Intelligence
$20 million gift names imaging suite in new facility, creates catalyst fund.
Automated system identifies dense tissue, a risk factor for breast cancer, in mammograms
Deep-learning model has been used successfully on patients, may lead to more consistent screening procedures.
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.
Ideas abound at Quest for Intelligence workshop
Community event generates ideas for sparking innovative and ambitious plans to advance research in human and machine intelligence.
Software finds the best way to stick a Mars landing
Program users can tinker with landing and path planning scenarios to identify optimal landing sites for Mars rovers.