Download RSS feed: News Articles / In the Media / Audio
Prof. Daniela Rus, director of CSAIL, writes for Forbes about Prof. Dina Katabi’s work using insights from wireless systems to help glean information about patient health. “Incorporating continuous time data collection in healthcare using ambient WiFi detectable by machine learning promises an era where early and accurate diagnosis becomes the norm rather than the exception,” writes Rus.
Researchers from MIT and Massachusetts General Hospital have developed “Sybil,” an AI tool that can detect the risk of a patient developing lung cancer within six years, reports Mary Kekatos for ABC News. “Sybil was trained on low-dose chest computer tomography scans, which is recommended for those between ages 50 and 80 who either have a significant history of smoking or currently smoke,” explains Kekatos.
Prof. Daniela Rus, director of CSAIL, emphasizes the central role universities play in fostering innovation and the importance of ensuring universities have the computing resources necessary to help tackle major global challenges. Rus writes, “academia needs a large-scale research cloud that allows researchers to efficiently share resources” to address hot-button issues like generative AI. “It would provide an integrated platform for large-scale data management, encourage collaborative studies across research organizations, and offer access to cutting-edge technologies, while ensuring cost efficiency,” Rus explains.
Writing for Forbes, research affiliate John Werner spotlights Prof. Stefanie Mueller’s presentation at the CSAIL Imagination in Action event on her work developing a new type of paint that allows users to change the color and pattern of different objects. “The long-term vision here, really, is to give those physical objects the same capabilities as we have in digital,” said Mueller. “I hope in the future we will all get some free stuff, and we would just have an [app] where we can download different textures we can apply, and change our outfits.”
During her talk at CSAIL’s Imagination in Action event, Prof. Daniela Rus, director of CSAIL, explored the promise of using liquid neural networks “to solve some of AI’s notorious complexity problems,” writes research affiliate John Werner for Forbes. “Liquid networks are a new model for machine learning,” said Rus. “They're compact, interpretable and causal. And they have shown great promise in generalization under heavy distribution shifts.”
In an article for Forbes, research affiliate John Werner spotlights Prof. Dina Katabi and her work showcasing how AI can boost the capabilities of clinical data. “We are going to collect data, clinical data from patients continuously in their homes, track the symptoms, the evolution of those symptoms, and process this data with machine learning so that we can get insights before problems occur,” says Katabi.
Prof. Regina Barzilay speaks with Nicole Estephan of WCVB-TV’s Chronicle about her work developing new AI systems that could be used to help diagnose breast and lung cancer before the cancers are detectable to the human eye.
Writing for Forbes, Prof. Daniela Rus, director of CSAIL, makes the case that liquid neural networks “offer an elegant and efficient computational framework for training and inference in machine learning. With their compactness, adaptability, and streamlined computation, these networks have the potential to reshape the landscape of artificial intelligence and drive further breakthroughs in the field.”
Researchers at MIT have developed PIGINet (Plans, Images, Goal and Initial facts), a neural network designed to bring task and motion planning to home robotics, reports Brian Heater for Tech Crunch. “The system is largely focused on kitchen-based activities at present. It draws on simulated home environments to build plans that require interactions with various different elements of the environment, like counters, cabinets, the fridge, sinks, etc,” says Heater.
Former MIT Prof. Edward Fredkin, “a pioneer in artificial intelligence and a maverick theorist,” has died at 88, reports Alex Williams for The New York Times. Williams notes that Fredkin, who worked on Project MAC during his time at MIT, was “fueled by a seemingly limitless scientific imagination and a blithe indifference to conventional thinking.” Prof. Gerald Sussman recalls that “Ed Fredkin had more ideas per day than most people have in a month.”
Prof. Marzyeh Ghassemi speaks with Yahoo News reporter Rebecca Corey about the benefits and risks posed by the use of AI tools in health care. “I think the problem is when you try to naively replace humans with AI in health care settings, you get really poor results,” says Ghassemi. “You should be looking at it as an augmentation tool, not as a replacement tool.”
Boston Globe reporter Mike Orcutt spotlights Prof. Silvio Micali and Prof. Shafi Goldwasser for their work developing the theory behind zero-knowledge proofs and their contributions to the field of modern cryptography.
New York Times reporter Natasha Singer spotlights the Day of AI, an MIT RAISE program aimed at teaching K-12 students about AI. “Because AI is such a powerful new technology, in order for it to work well in society, it really needs some rules,” said MIT President Sally Kornbluth. Prof. Cynthia Breazeal, MIT’s dean of digital learning, added: “We want students to be informed, responsible users and informed, responsible designers of these technologies.”
Graduate student Kartik Chandra writes for Inside Higher Education about how many of this year’s college graduates are feeling anxiety about new AI technologies. “We scientists are still debating the details of how AI is and is not humanlike in its use of language,” writes Chandra. “But let’s not forget the big picture: unlike AI, you speak because you have something to say.”
Neil Thompson, director of the FutureTech research project at MIT CSAIL and a principal investigator MIT’s Initiative on the Digital Economy, speaks with Politico reporter Mohar Chatterjee about generative AI, the pace of computer progress and the need for the U.S. to invest more in developing the future of computing. “We need to make sure we have good secure factories that can produce cutting-edge semiconductors,” says Thompson. “The CHIPS Act covers that. And people are starting to invest in some of these post-CMOS technologies — but it just needs to be much more. These are incredibly important technologies.”