Artificial intelligence

Daniela Rus (far right), director of the Computer Science and Artificial Intelligence Laboratory (CSAIL), moderated a panel on dispelling the myths of AI technologies in the workplace. The AI and the Work of the Future Congress was co-organized by CSAIL, the MIT Initiative on the Digital Economy, and the MIT Work of the Future Task Force.

MIT conference focuses on preparing workers for the era of artificial intelligence

As automation rises in the workplace, speakers explore ways to train students and reskill workers.

November 22, 2019

DeepRole, an MIT-invented gaming bot equipped with “deductive reasoning,” can beat human players in tricky online multiplayer games where player roles and motives are kept secret.

Bot can beat humans in multiplayer hidden-role games

Using deductive reasoning, the bot identifies friend or foe to ensure victory over humans in certain online games.

November 19, 2019

“We believe that AI plays a key role now, and in the future development of the region, if it’s used in the right way,” says Omar Costilla Reyes, one of four MIT graduate students working to help Latin America adopt artificial intelligence technologies. Pictured here (left to right) are Costilla Reyes, Emilia Simison, Pedro Antonio Colon-Hernandez, and Guillermo Bernal.

Students push to speed up artificial intelligence adoption in Latin America

To help the region catch up, students organize summit to bring Latin policymakers and researchers to MIT.

November 19, 2019

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

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

Brian Storey, director of accelerated materials design and discovery at Toyota Research Institute, speaks at the MIT MRL Materials Day Symposium.

Driving toward a healthier planet

Materials Day speaker Brian Storey describes how the Toyota Research Institute is embracing machine learning to advance the use of electric vehicles.

November 7, 2019

Eight distinguished researchers spoke at the 2019 Materials Day Symposium. Pictured here (l-r) are MIT professors Carl Thompson, Asu Ozdaglar, Elsa Olivetti, and Ju Li.

Materials Day talks examine the promises and challenges of AI and machine learning

The ability to predict and make new materials faster highlights the need for safety, reliability, and accurate data.

November 5, 2019

3 Questions: When the student becomes the teacher

Grad student Brandon Leshchinskiy created EarthDNA Ambassadors, an outreach program “for the Earth, for future generations.”

November 5, 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

Using a supercomputing system, MIT researchers developed a model that captures what global web traffic could look like on a given day, including previously unseen isolated links (left) that rarely connect but seem to impact core web traffic (right).

Supercomputer analyzes web traffic across entire internet

Modeling web traffic could aid cybersecurity, computing infrastructure design, Internet policy, and more.

October 27, 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

Computer science in service of medicine

Senior Kristy Carpenter aims to leverage artificial intelligence and other computational tools to develop new, more affordable drugs.

October 18, 2019

MIT News | Massachusetts Institute of Technology

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