Download RSS feed: News Articles / In the Media
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.
CSAIL researchers are developing a drone that could be used to assist humans in search and rescue operations, reports Mashable. “If you are trying to detect someone in an avalanche and you can maybe just send a drone, and if they can find them out and then fly towards them and send a help signal. It would be probably be something that would be beneficial to people as an immediate application.”
Prof. Daniela Rus, director of CSAIL, speaks with Popular Science reporter Charlotte Hu about the field of artificial intelligence, explaining the difference between AI, robotics and machine learning, and exploring the future of AI. “[AI algorithms] can do really extraordinary things much faster than we can. But the way to think about it is that they’re tools that are supposed to augment and enhance how we operate,” says Rus. “And like any other tools, these solutions are not inherently good or bad. They are what we choose to do with them.”
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.”
Researchers at MIT developed SoFi, a soft robotic fish designed to study underwater organisms and their environments, reports Mashable. “The soft robotic fish serves a nice purpose for hopefully minimizing impact on the environments that we’re studying and also helps us study different types of behaviors and also study the actual mechanics of these organisms as well,” says graduate student Levi Cai.
National Geographic reporter Maya Wei-Haas explores how the ancient art of origami is being applied to fields such a robotics, medicine and space exploration. Wei-Haas notes that Prof. Daniela Rus and her team developed a robot that can fold to fit inside a pill capsule, while Prof. Erik Demaine has designed complex, curving fold patterns. “You get these really impressive 3D forms with very simple creasing,” says Demaine.
Prof. Daniela Rus, director of CSAIL, discusses the future of artificial intelligence, emphasizing the importance of balancing the development of new technologies with the need to ensure they are deployed in a way that benefits humanity. “We have to advance the science and engineering of autonomy and the science and engineering of intelligence to create the kinds of machines that will be friendly to people, that will be assistive and supportive for people and that will augment people with the tasks that they need help with,” Rus explains.
NBC 1st Look host Chelsea Cabarcas visits MIT to learn more about how faculty, researchers and students are “pioneering the world of tomorrow.” Cabarcas meets the MIT Solar Electric Vehicle team and gets a peek at Nimbus, the single-occupant vehicle that team members raced in the American Solar Challenge from Kansas City to New Mexico. Cabarcas also sees the back-flipping MIT mini cheetah that could one day be used in disaster-relief operations.
Prof. Joshua Tenenbaum speaks with Wired reporter Will Knight about AI image generators and the limitations of AI tools. “It's amazing what they can do,” says Tenenbaum, “but their ability to imagine what the world might be like from simple descriptions is often very limited and counterintuitive.”
A review led Prof. Marzyeh Ghassemi has found that a major issue in health-related machine learning models “is the relative scarcity of publicly available data sets in medicine,” reports Emily Sohn for Nature.
Research affiliate Ramin Hasani speaks with Kimberly Adams of Marketplace about how he and his CSAIL colleagues solved a differential equation dating back to the early 1900s, enabling researchers to create an AI algorithm that can learn on the spot and adapt to evolving patterns. The new algorithm “will enable larger-scale brain simulations,” Hasani explains.
Nature reporter Elie Dolgin writes that a new study by MIT researchers explores the role of the gene variant APOE4 in Alzheimer’s, and finds that the gene is linked with faulty cholesterol processing in the brain, impacting the insulation around nerve cells and potentially causing memory and learning deficits. “The work suggests that drugs that restore the brain’s cholesterol processing could treat the disease,” writes Dolgin.