Machine learning

Ankur Moitra named a 2016 Packard Fellow

October 17, 2016

MIT Media Lab Director Joi Ito (left), WIRED Editor-in-Chief Scott Dadich (center), and U.S. President Barack Obama confer in the Roosevelt Room of the White House.

President Obama discusses artificial intelligence with Media Lab Director Joi Ito

One-on-one conversation in WIRED focuses on advancements in artificial intelligence and how society should respond to related concerns.

October 14, 2016

The Laboratory for Social Machines, part of the MIT Media Lab, has launched a project called the Electome that charts Twitter in unique detail.

Q&A: How Twitter explains the 2016 election

“Electome” project charts the national conversation in unique detail.

September 26, 2016

A new computer system can automatically screen young children for speech and language disorders and, potentially, even provide specific diagnoses.

Automated screening for childhood communication disorders

Computer system could help identify subtle speech, language disorders in time for early intervention.

September 22, 2016

Imaging scientist and social impact inventor Ramesh Raskar of MIT is the 2016 recipient of the $500,000 Lemelson-MIT Prize.

Ramesh Raskar awarded $500,000 Lemelson-MIT Prize

Imaging scientist and inventor sets sights on launching peer-to-peer invention platforms for global impact.

September 13, 2016

English is the most used language on the Internet, and globally most of the people who speak or write in English are non-native speakers. A new database of annotated English sentences written by non-native speakers could help improve how computers handle the spoken or written language of non-native English speakers.

First major database of non-native English

Resource could yield linguistic insights, practical applications for non-native English speakers.

July 29, 2016

A localizing ground-penetrating radar system from the MIT Lincoln Laboratory complements existing technology, with the goal of achieving safe autonomous vehicles.

Pinpointing vehicles with high precision under adverse weather conditions

MIT Lincoln Laboratory radar system achieves centimeter-level localization; could help driverless cars stay in lane when road markings are obscured.

June 23, 2016

Building better trust between humans and machines

MIT-SUTD researchers are creating improved interfaces to help machines and humans work together to complete tasks.

June 21, 2016

From MIT CSAIL: The left-most column shows the frame before the action begins, with the algorithm's prediction below it. The right columns show the next frames of the video.

Teaching machines to predict the future

Deep-learning vision system from the Computer Science and Artificial Intelligence Lab anticipates human interactions using videos of TV shows.

June 21, 2016

Researchers developed a simple application for devices that use Apple’s iOS operating system. The application flashes a small dot somewhere on the device’s screen, attracting the user’s attention, then briefly replaces it with either an “R” or an “L,” instructing the user to swipe either the right or left side of the screen. Correctly executing the swipe ensures that the user has act...

Eye-tracking system uses ordinary cellphone camera

Crowd-sourced data yields system that determines where mobile-device users are looking.

June 15, 2016

Artificial intelligence produces realistic sounds that fool humans

Video-trained system from MIT’s Computer Science and Artificial Intelligence Lab could help robots understand how objects interact with the world.

June 13, 2016

IDSS conversations: Guy Bresler

Assistant professor of electrical engineering and computer science discusses his work focusing on learning graphical models from data.

March 11, 2016

“One of the most intriguing aspects of this research is that we’ve found that there are indeed universal properties of correct code that you can learn from one set of applications and apply to another set of applications,” Martin Rinard says.

Recognizing correct code

Automatic bug-repair system fixes 10 times as many errors as its predecessors.

January 29, 2016

MIT researchers fed their physics prediction system videos of collisions, shown as screenshots in (a) and (b), which were then converted into simulations generated by the 3-D physics engine, shown in (c) and (d).

Computer model matches humans at predicting how objects move

“3-D physics engine” from the Computer Science and Artificial Intelligence Laboratory simulates the human brain to infer physical properties.

January 4, 2016

Researchers have developed a computational model of visual representation intended to reflect the way the brain works.

Machines that learn like people

Algorithms could learn to recognize objects from a few examples, not millions; may better model human cognition.

December 23, 2015

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