Computer Science and Artificial Intelligence Laboratory (CSAIL)

In lane-merging scenarios, a system developed at MIT could distinguish between altruistic and egoistic driving behavior.

Predicting people's driving personalities

System from MIT CSAIL sizes up drivers as selfish or selfless. Could this help self-driving cars navigate in traffic?

November 18, 2019

"What does it mean," Aidinoff asks "when civil rights become about access to computers and the internet? When lack of internet access is considered a form of poverty? These questions were getting under my skin," he says. "I wanted to know how social and economic policy were tied to changing ideas about technology."

PhD student Marc Aidinoff explores how technology impacts public policy

Historian's research focuses on understanding how visions for social and economic policy are tied to changing ideas about technology.

November 18, 2019

A new tool reveals what AI models leave out in recreating a scene. Here, a GAN, or generative adversarial network, has dropped the pair of newlyweds from its reconstruction (right) of the photo it was asked to draw (left).

Visualizing an AI model’s blind spots

New tool highlights what generative models leave out when reconstructing a scene.

November 8, 2019

Even in unexplored waters, an MIT-developed robotic system can efficiently sniff out valuable, hard-to-find spots to collect samples from. When implemented in autonomous boats deployed off the coast of Barbados (pictured), the system quickly found the most exposed coral head —meaning it was located in the shallowest spot — which is useful for studying how sun exposure impacts coral organisms.

Autonomous system improves environmental sampling at sea

Robotic boats could more rapidly locate the most valuable sampling spots in uncharted waters.

November 4, 2019

MIT and Toyota researchers have designed a new model that weighs various uncertainties and risks to help autonomous vehicles determine when it’s safe to merge into traffic at intersections with objects obstructing views, such as buildings blocking the line of sight.

Better autonomous “reasoning” at tricky intersections

Model alerts driverless cars when it’s safest to merge into traffic at intersections with obstructed views.

November 4, 2019

In a study using machine-generated art to understand what makes a picture memorable, researchers found that the images people remembered best had bright colors, simple backgrounds, and subjects centered prominently in the frame.

What makes an image memorable? Ask a computer

An artificial intelligence model developed at MIT shows in striking detail what makes some images stick in our minds.

November 1, 2019

One modular robotic cube snaps into place with rest of the M-blocks.

Self-transforming robot blocks jump, spin, flip, and identify each other

Developed at MIT’s Computer Science and Artificial Intelligence Laboratory, robots can self-assemble to form various structures with applications including inspection.

October 30, 2019

MIT engineers have developed a system for autonomous vehicles that senses tiny changes in shadows on the ground to determine if there’s a moving object coming around the corner, such as when another car is approaching from behind a pillar in a parking garage.

Helping autonomous vehicles see around corners

By sensing tiny changes in shadows, a new system identifies approaching objects that may cause a collision.

October 27, 2019

A key to compiling the novel Omnipush dataset was building modular objects (pictured) that enabled the robotic system to capture a vast diversity of pushing behavior. The central pieces contain markers on their centers and points so a motion-detection system can detect their position within a millimeter.

Pushy robots learn the fundamentals of object manipulation

Systems “learn” from novel dataset that captures how pushed objects move, to improve their physical interactions with new objects.

October 21, 2019

At left, EdgeConv, a method developed at MIT, successfully finds meaningful parts of 3D shapes, like the surface of a table, wings of an airplane, and wheels of a skateboard. At right is the ground-truth comparison.

Deep learning with point clouds

Research aims to make it easier for self-driving cars, robotics, and other applications to understand the 3D world.

October 21, 2019

The Ad Hoc Task Force on Open Access to MIT’s Research has released its final recommendations, which aim to support and increase the open sharing of MIT publications, data, software, and educational materials.

Open access task force releases final recommendations

Report urges MIT community to openly share the products of its research and teaching.

October 17, 2019

Applied mathematics Professor Alan Edelman has been selected to receive the 2019 IEEE Computer Society Sidney Fernbach Award.

Alan Edelman recognized with 2019 IEEE Computer Society Sidney Fernbach Award

Edelman's Julia programming language was recognized for solving large computational problems for high-performance computers.

October 17, 2019

MIT Professor Regina Barzilay (left) and CSAIL PhD student Tal Schuster are studying detectors of machine-generated text.

Better fact-checking for fake news

New research reveals biases in fake news datasets and improves the use of automatic detectors.

October 17, 2019

A new algorithm speeds up the planning process for robotic grippers to manipulate objects using the surrounding environment.

Giving robots a faster grasp

An algorithm speeds up the planning process robots use to adjust their grip on objects, for picking and sorting, or tool use.

October 17, 2019

A novel model developed at MIT recovers valuable data lost from images and video that have been “collapsed” into lower dimensions. It can, for instance, recreate video from motion-blurred images or from cameras that capture people’s movement around corners as vague one-dimensional lines.

Recovering “lost dimensions” of images and video

Model could recreate video from motion-blurred images and “corner cameras,” may someday retrieve 3D data from 2D medical images.

October 16, 2019

MIT News | Massachusetts Institute of Technology

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Predicting people's driving personalities

PhD student Marc Aidinoff explores how technology impacts public policy

Visualizing an AI model’s blind spots

Autonomous system improves environmental sampling at sea

Better autonomous “reasoning” at tricky intersections

What makes an image memorable? Ask a computer

Self-transforming robot blocks jump, spin, flip, and identify each other

Helping autonomous vehicles see around corners

Pushy robots learn the fundamentals of object manipulation

Deep learning with point clouds

Open access task force releases final recommendations

Alan Edelman recognized with 2019 IEEE Computer Society Sidney Fernbach Award

Better fact-checking for fake news

Giving robots a faster grasp

Recovering “lost dimensions” of images and video

Browse By

Topics

Departments

Centers, Labs, & Programs

Schools

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Computer Science and Artificial Intelligence Laboratory (CSAIL)