A simulation system invented at MIT to train driverless cars creates a photorealistic world with infinite steering possibilities, helping the cars learn to navigate a host of worse-case scenarios before cruising down real streets.
As more Covid-19 cases appear in the United States and around the world, the need for fast, easy-to-use diagnostic tests is becoming ever more pressing. A startup company spun out from MIT is now working on a paper-based test that can deliver results in under half an hour, based on technology developed at MIT’s Institute for Medical Engineering and Science (IMES).
A team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) has developed a new system that uses an existing technology called ground-penetrating radar (GPR) to send electromagnetic pulses underground that measure the area’s specific combination of soil, rocks, and roots.
“Most updated digital maps are from places that big companies care the most about. If you’re in places they don’t care about much, you’re at a disadvantage with respect to the quality of map,” says co-author Sam Madden, a professor in the Department of Electrical Engineering and Computer Science (EECS) and a researcher in the Computer Science and Artificial Intelligence Laboratory (CSAIL). “Our goal is to automate the process of generating high-quality digital maps, so they can be available in any country.”
Given that our smartphones have largely become appendages over the last decade, it’s hard to imagine that ten years ago there was no Instagram, Uber, TikTok or Tinder. The ways we move, shop, eat and communicate continue to evolve thanks to the technologies we use. It can be easy to forget how quickly things have changed - so let’s turn back the clocks and reminisce about some of the computing breakthroughs that have transformed our lives in the ’10s.
Recently a team led by researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) has been exploring whether self-driving cars can be programmed to classify the social personalities of other drivers, so that they can better predict what different cars will do — and, therefore, be able to drive more safely among them.
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.
To improve the safety of autonomous systems, MIT CSAIL scientists have developed a system that can sense tiny changes in shadows on the ground to determine if there’s a moving object coming around the corner.
