NBC News highlights how researchers from MIT and MGH have developed a new AI tool, called Sybil, that can “accurately predict whether a person will develop lung cancer in the next year 86% to 94% of the time.” NBC News notes that according to experts, the tool "could be a leap forward in the early detection of lung cancer.”
Prof. Marzyeh Ghassemi speaks with WBUR reporter Geoff Brumfiel about her research studying the use of artificial intelligence in healthcare. “When you take state-of-the-art machine learning methods and systems and then evaluate them on different patient groups, they do not perform equally,” says Ghassemi.
Researchers at MIT have created a four-legged robot called DribbleBot, reports Caroline Goggin for WHDH. The robot “can dribble a soccer ball under the same conditions as humans, using onboard sensors to travel across different types of terrain.”
Popular Science reporter Andrew Paul spotlights how researchers from MIT CSAIL have developed a soccer-playing robot, dubbed DribbleBot, that can handle a variety of real-world terrains. “DribbleBot showcases extremely impressive strides in articulation and real-time environmental analysis. Using a combination of onboarding computing and sensing, the team’s four-legged athlete can reportedly handle gravel, grass, sand, snow, and pavement, as well as pick itself up if it falls.”
MIT researchers have created “Dribblebot,” a four-legged robot capable of playing soccer across varying terrain, reports Brian Heater for TechCrunch.
Researchers at MIT have created a four-legged robot capable of dribbling a soccer ball and running across a variety of terrains, reports Ross Cristantiello for Boston.com. “Researchers hope that they will be able to teach the robot how to lift a ball over a step in the future,” writes Cristantiello. “They will also explore how the technology behind DribbleBot can be applied to other robots, allowing machines to quickly transport a range of objects around outside using legs and arms.”
MIT researchers have developed Robust MADER, an updated version of a previous system developed in 2020 to help drones avoid in-air collisions, reports Brian Heater for TechCrunch. “The new version adds in a delay before setting out on a new trajectory,” explains Heater. “That added time will allow it to receive and process information from fellow drones and adjust as needed.”
Researchers at MIT have predicted that without improvements in hardware efficiency, energy consumption and emissions from autonomous vehicles could be “comparable to that of data centers today,” reports Sarah Wells for Popular Mechanics. “In order to reduce the future carbon footprint of AVs, scientists will need to make the computing systems of AVs, including smart sensors, far more efficient,” writes Wells.
Researchers at MIT developed a system that uses artificial intelligence to help predict future risk of developing breast cancer, reports Poppy Harlow for CNN. What this work does “is identifies risk. It can tell a woman that you’re at high risk for developing breast cancer before you develop breast cancer,” says Larry Norton, medical director of the Lauder Breast Center at the Memorial Sloan Kettering Cancer Center.
MIT researchers have constructed a mini city to test to safely test algorithms designed for autonomous vehicles, reports Mashable. “The idea of the mini city is that we have lots of cars going at the same time and we can actually test out new algorithms in a safe environment,” says graduate student Noam Buckman.
Researchers at MIT have developed a drone that can be controlled using hand gestures, reports Mashable. “I think it’s important to think carefully about how machine learning and robotics can help people to have a higher quality of life and be more productive,” says postdoc Joseph DelPreto. “So we want to combine what robots do well and what people do well so that they can be more effective teams.”
Motherboard reporter Tatyana Woodall writes that a new study co-authored by MIT researchers finds that AI models that can learn to perform new tasks from just a few examples create smaller models inside themselves to achieve these new tasks. “Learning is entangled with [existing] knowledge,” graduate student Ekin Akyürek explains. “We show that it is possible for these models to learn from examples on the fly without any parameter update we apply to the model.”
Researchers at MIT and Massachusetts General Hospital have developed “Sybil” – an artificial intelligence tool that can predict the risk of a patient developing lung cancer within six years, reports Mallika Marshall for CBS Boston.
Researchers at MIT have developed an autonomous vehicle with “mini sensors to allow it to see the world and also with an artificially intelligent computer brain that can allow it to drive,” explains postdoctoral associate Alexander Amini in an interview with Mashable. “Our autonomous vehicles are able to learn directly from humans how to drive a car so they can be deployed and interact in brand new environments that they’ve never seen before,” Amini notes.
MIT researchers have developed a new AI tool called Sybil that could help predict whether a patient will get lung cancer up to six years in advance, reports Pranshu Verma for The Washington Post. “Much of the technology involves analyzing large troves of medical scans, data sets or images, then feeding them into complex artificial intelligence software,” Verma explains. “From there, computers are trained to spot images of tumors or other abnormalities.”