Machine learning

Tamara Broderick, assistant professor of electrical engineering and computer science at MIT, was a presenter at the 2016 Machine Intelligence Summit.

Meeting of the minds for machine intelligence

Industry leaders, computer scientists, and venture capitalists gather to discuss how smarter computers are remaking our world.

November 22, 2016

Information extraction — or automatically classifying data items stored as plain text — is a major topic of artificial-intelligence research.

Artificial-intelligence system surfs web to improve its performance

“Information extraction” system helps turn plain text into data for statistical analysis.

November 10, 2016

Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have devised a way to train neural networks so that they provide not only predictions and classifications but rationales for their decisions.

Making computers explain themselves

New training technique would reveal the basis for machine-learning systems’ decisions.

October 27, 2016

A team, including researchers from MIT’s Computer Science and Artificial Intelligence Laboratory, has created a new set of algorithms that can efficiently fit probability distributions to high-dimensional data.

Finding patterns in corrupted data

New model-fitting technique is efficient even for data sets with hundreds of variables.

October 26, 2016

Researchers used sample images, like the ones on the top row, to identify several visual features that are highly correlated with judgments that a particular area is safe or unsafe. The left side shows a low level of safety while the right shows a high level. Highlighted areas on the middle row show “unsafe” areas while the bottom row shows “safe” areas in the image.

Quantifying urban revitalization

Combining cellphone data with perceptions of public spaces could help guide urban planning.

October 24, 2016

“The goal of all this is to present the interesting stuff to the data scientists so that they can more quickly address all these new data sets that are coming in,” says Max Kanter MEng ’15.

Automating big-data analysis

With new algorithms, data scientists could accomplish in days what has traditionally taken months.

October 21, 2016

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.