Computer Science and Artificial Intelligence Laboratory (CSAIL)

Tomaso Poggio, a professor of brain and cognitive sciences at MIT and director of the Center for Brains, Minds, and Machines, has long thought that the brain must produce “invariant” representations of faces and other objects, meaning representations that are indifferent to objects’ orientation in space, their distance from the viewer, or their location in the visual field.

How the brain recognizes faces

Machine-learning system spontaneously reproduces aspects of human neurology.

December 1, 2016

Given a still image from a scene, new deep-learning algorithm can create a brief video that simulates the future of that scene.

Creating videos of the future

Given a still image, CSAIL deep-learning system generates videos that predict what will happen next in a scene.

November 29, 2016

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

2016 MIT AAAS Fellows: (clockwise from top left) William Green, Wolfgang Ketterle, Howard Shrobe, and Elly Nedivi.

Four MIT faculty elected 2016 AAAS Fellows

Green, Ketterle, Nedivi, and Shrobe are among those recognized for their efforts toward advancing science.

November 21, 2016

CoolThink@JC will target 16,000 students at 32 primary schools across the city of Hong Kong, offering tools and expertise to boost computational thinking abilities. Insights from the initiative, being done in collaboration with MIT and others, will eventually inform the development of curriculum for all Hong Kong teachers and students.

Teaching Hong Kong students to embrace computational thinking

Powered by MIT expertise and regional universities, CoolThink@JC will offer training to primary teachers and students at 32 schools.

November 15, 2016

A new cordless virtual reality device consists of two directional "phased-array" antennas, each less than half the size of a credit card.

Enabling wireless virtual reality

Developed at Computer Science and Artificial Intelligence Laboratory, “MoVR” system allows VR headsets to communicate without a cord

November 14, 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

A system developed by researchers at MIT and Stony Brook University should make it easier for researchers to solve complex computational problems using dynamic programming optimized for multicore chips — without the expertise that such programming typically requires.

Faster programs, easier programming

New system lets nonexperts optimize programs that run on multiprocessor chips.

November 7, 2016

An autonomous mobility scooter and related software were designed by researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), the National University of Singapore, and the Singapore-MIT Alliance for Research and Technology (SMART).

Driverless-vehicle options now include scooters

Self-driving scooter demonstrated at MIT complements autonomous golf carts and city cars.

November 7, 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

“Gitless" removes complicated concepts like "staging" and "stashing," without fundamentally changing Git's core functionality.

Making it easier to collaborate on code

CSAIL team's “Gitless” fixes Git’s biggest issues — and suggests their approach could help improve systems like Gmail and Dropbox.

October 25, 2016

A team led by Polina Golland’s group at MIT’s Computer Science and Artificial Intelligence Laboratory has made a new algorithm for identifying organs in fetal MRI scans, which should make MRI monitoring much more useful. Pictured is a stock image of a fetal MRI.

MRIs for fetal health

Algorithm could help analyze fetal scans to determine whether interventions are warranted.

October 21, 2016

“One thing you realize working in this lab is that we are really far away from the robot apocalypse,” says MIT senior Sarah Hensley, who is working with a team of researchers to prepare Valkyrie, a humanoid robot, for future space missions.

Prepping a robot for its journey to Mars

Senior Sarah Hensley aims to improve Earth's most advanced humanoid robot, in advance of its trip to the Red Planet.

October 18, 2016

Professor Emeritus Whitman Richards dies at 84

Longtime professor and beloved advisor was known for advances in experimental and theoretical studies of vision, perception, and cognition.

October 17, 2016

MIT News | Massachusetts Institute of Technology

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