Artificial intelligence

“Doing machine learning the right way”

Professor Aleksander Madry strives to build machine-learning models that are more reliable, understandable, and robust.

March 7, 2020

Roboticists are developing automated robots that can learn new tasks solely by observing humans. At home, you might someday show a domestic robot how to do routine chores.

Showing robots how to do your chores

By observing humans, robots learn to perform complex tasks, such as setting a table.

March 5, 2020

MIT cognitive scientists have developed a computer model of face recognition that performs a series of computations that reverse the steps that a computer graphics program would use to generate a 2D representation of a face.

A new model of vision

Computer model of face processing could reveal how the brain produces richly detailed visual representations so quickly.

March 4, 2020

MIT researchers (left to right) Qianli Liao, Tomaso Poggio, and Andrzej Banburski stand with their equations.

Demystifying the world of deep networks

Researchers discover that no magic is required to explain why deep networks generalize despite going against statistical intuition.

February 28, 2020

MIT researchers have used a neural network to identify low-frequency seismic waves hidden in earthquake data. The technique may help scientists more accurately map the Earth’s interior.

Machine learning picks out hidden vibrations from earthquake data

Technique may help scientists more accurately map vast underground geologic structures.

February 28, 2020

MIT's new system allows a self-driving car to situate itself in snowy conditions.

To self-drive in the snow, look under the road

Weather’s a problem for autonomous cars. MIT’s new system shows promise by using “ground-penetrating radar” instead of cameras or lasers.

February 26, 2020

Renewed products consist of upcycled or recycling materials. The Renewal Workshop is an MIT Solver team that works to save textiles from landfill.

MIT Solve announces 2020 global challenges

Tech-based solutions sought for challenges in work environments, education for girls and women, maternal and newborn health, and sustainable food.

February 25, 2020

A crash course in deep learning organized and taught by grad students Alexander Amini (right) and Ava Soleimany reaches more than 350 MIT students each year; more than a million other people have watched their lectures online over the past three years.

Bringing deep learning to life

MIT duo uses music, videos, and real-world examples to teach students the foundations of artificial intelligence.

February 24, 2020

PatternEx’s Virtual Analyst Platform uses machine learning models to detect suspicious activity on a network. That activity is then presented to human analysts for feedback that improves the systems’ ability to flag activity analysts care about.

A human-machine collaboration to defend against cyberattacks

PatternEx merges human and machine expertise to spot and respond to hacks.

February 21, 2020

Luis Videgaray, director of MIT’s AI Policy for the World Project, talking at his Starr Forum lecture, hosted by the Center for International Studies, on February 19, 2020.

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.

February 20, 2020