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Computer Science and Artificial Intelligence Laboratory (CSAIL)

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The Washington Post

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.”

Mashable

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

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.

Mashable

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

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.

Wired

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.”

Nature

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.

Marketplace

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

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. 

Popular Science

Popular Science reporter Charlotte Hu writes that MIT researchers have developed a new machine learning model that can depict how the sound around a listener changes as they move through a certain space. “We’re mostly modeling the spatial acoustics, so the [focus is on] reverberations,” explains graduate student Yilun Du. “Maybe if you’re in a concert hall, there are a lot of reverberations, maybe if you’re in a cathedral, there are many echoes versus if you’re in a small room, there isn’t really any echo.”

Forbes

MIT researchers have developed a new technique aimed at protecting images from AI generators, reports Kyle Barr for Gizmodo. The program uses "data poisoning techniques to essentially disturb pixels within an image to create invisible noise, effectively making AI art generators incapable of generating realistic deepfakes based on the photos they’re fed,” reports Kyle Barr for Gizmodo." 

Fast Company

Prof. Emeritus Tim Berners-Lee spoke at Lisbon’s Web Summit conference about Solid, an “open-sourced gambit to reinvent the web through new decentralized privacy-minded tools for wrangling data,” reports Harry McCracken for Fast Company. Solid was originally started as an MIT research project.

TechCrunch

Scientists at MIT have developed “a machine learning model that can capture how sounds in a room will propagate through space,” report Kyle Wiggers and Devin Coldewey for TechCrunch. “By modeling the acoustics, the system can learn a room’s geometry from sound recordings, which can then be used to build a visual rendering of a room,” write Wiggers and Coldewey.

Newsweek

MIT researchers have developed a new machine learning model that can identify and track blobs of plasma created in controlled nuclear-fusion research, reports Ed Browne for Newsweek. “Fusion research is a complex, multidisciplinary project that requires technologies from many fields,” explains graduate student Woonghee “Harry” Han.

Nature

Prof. Peter Shor has been named one of the winners of the 2023 Breakthrough Prize in Fundamental Physics, reports Nature. “Shor’s most renowned contribution is the development of quantum algorithms for prime number factorization,” writes Nature.