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NPR

Prof. Marzyeh Ghassemi speaks with NPR host Emily Kwong and correspondent Geoff Brumfiel about how artificial intelligence could impact medicine. “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.

Science

Research from MIT and elsewhere have developed a mobile app that uses computer-vision techniques and AI to detect post-surgery signs of infection as part of an effort to help community workers in Kirehe, a district in Rwanda’s Eastern province, reports Shefali Malhotra for Science. “The researchers are now improving the app so it can be used across more diverse populations such as in Ghana and parts of South America,” writes Malhotra.

Popular Science

Popular Science reporter Jamie Dickman writes that using liquid neural networks, MIT researchers have “trained a drone to identify and navigate toward objects in varying environments.” Dickman notes that: “These robust networks enable the drone to adapt in real-time, even after initial training, allowing it to identify a target object despite changes in their environment.”

The Daily Beast

Researchers at MIT have developed a new type of autonomous drone that uses advanced neural networks to fly, reports Tony Ho Tran for The Daily Beast. “The new design allows the drone to make better decisions when flying through completely new environments,” writes Tran, “and could have future applications in self-driving cars, search and rescue operations, wildlife monitoring, or even diagnosing medical issues.”

NBC News

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.”

WBUR

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.

WHDH 7

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

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.”

TechCrunch

MIT researchers have created “Dribblebot,” a four-legged robot capable of playing soccer across varying terrain, reports Brian Heater for TechCrunch.

Boston.com

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.”

TechCrunch

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.”

Popular Mechanics

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. 

CNN

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.

Mashable

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.

Mashable

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.”