MIT researchers have invented a way to efficiently optimize the control and design of soft robots for target tasks, which has traditionally been a monumental undertaking in computation.

In opening the AI and the Work of the Future Congress, MIT Professor Daniela Rus presented diverging views of how artificial intelligence will impact jobs worldwide.

By automating certain menial tasks, experts think AI is poised to improve human quality of life, boost profits, and create jobs, said Rus, director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science.

A new demo by the MIT-IBM Watson AI Lab reveals what a model trained on scenes of churches and monuments decides to leave out when it draws its own version of, say, the Pantheon in Paris, or the Piazza di Spagna in Rome. The larger study, Seeing What a GAN Cannot Generate, was presented at the International Conference on Computer Vision last week.

MIT and Toyota researchers have designed a new model to help autonomous vehicles determine when it’s safe to merge into traffic at intersections with obstructed views.

An autonomous robotic system invented by researchers at MIT and the Woods Hole Oceanographic Institution (WHOI) efficiently sniffs out the most scientifically interesting — but hard-to-find — sampling spots in vast, unexplored waters.

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

MIT researchers have compiled a dataset that captures the detailed behavior of a robotic system physically pushing hundreds of different objects.

MIT researchers have developed a model that recovers valuable data lost from images and video that have been “collapsed” into lower dimensions.

The model could be used to recreate video from motion-blurred images, or from new types of cameras that capture a person’s movement around corners but only as vague one-dimensional lines. While more testing is needed, the researchers think this approach could someday could be used to convert 2D medical images into more informative — but more expensive — 3D body scans, which could benefit medical imaging in poorer nations.

“There’s a growing concern about machine-generated fake text, and for a good reason,” says CSAIL PhD student Tal Schuster, lead author on a new paper on their findings. “I had an inkling that something was lacking in the current approaches to identifying fake information by detecting auto-generated text — is auto-generated text always fake? Is human-generated text always real?”

If you’ve ever seen a self-driving car in the wild, you might wonder about that spinning cylinder on top of it. 

It’s a “lidar sensor,” and it’s what allows the car to navigate the world. By sending out pulses of infrared light and measuring the time it takes for them to bounce off objects, the sensor creates a “point cloud” that builds a 3D snapshot of the car’s surroundings.