“Doing machine learning the right way”
Professor Aleksander Madry strives to build machine-learning models that are more reliable, understandable, and robust.
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A new model of vision
Computer model of face processing could reveal how the brain produces richly detailed visual representations so quickly.
President Reif testifies before Congress on U.S. competitiveness
“To stay ahead, the U.S. needs to do more to capitalize on our own strengths,” he tells representatives.
Bringing deep learning to life
MIT duo uses music, videos, and real-world examples to teach students the foundations of artificial intelligence.
A human-machine collaboration to defend against cyberattacks
PatternEx merges human and machine expertise to spot and respond to hacks.
A road map for artificial intelligence policy
In a Starr Forum talk, Luis Videgaray, director of MIT’s AI Policy for the World Project, outlines key facets of regulating new technologies.
Benjamin Chang: Might technology tip the global scales?
MIT graduate student is assessing the impacts of artificial intelligence on military power, with a focus on the US and China.
Bringing artificial intelligence into the classroom, research lab, and beyond
Through the Undergraduate Research Opportunities Program, students work to build AI tools with impact.
SENSE.nano awards seed grants in optoelectronics, interactive manufacturing
The mission of SENSE.nano is to foster the development and use of novel sensors, sensing systems, and sensing solutions.
Rethinking fire with data analytics and systems design
MIT frameworks are helping the U.S. Forest Service find solutions to fire.
Maintaining the equipment that powers our world
By organizing performance data and predicting problems, Tagup helps energy companies keep their equipment running.
Bridging the gap between human and machine vision
Researchers develop a more robust machine-vision architecture by studying how human vision responds to changing viewpoints of objects.
Brainstorming energy-saving hacks on Satori, MIT’s new supercomputer
Three-day hackathon explores methods for making artificial intelligence faster and more sustainable.
Hey Alexa! Sorry I fooled you ...
MIT’s new system TextFooler can trick the types of natural-language-processing systems that Google uses to help power its search results, including audio for Google Home.
A college for the computing age
With the initial organizational structure in place, the MIT Schwarzman College of Computing moves forward with implementation.