Artificial intelligence

In an article for The Wall Street Journal about next generation technologies that can create and quantify personal health data, Laura Cooper spotlights Prof. Dina Katabi’s work developing a noninvasive device that sits in a person’s home and can help track breathing, heart rate, movement, gait, time in bed and the length and quality of sleep. The device “could be used in the homes of seniors and others to help detect early signs of serious medical conditions, and as an alternative to wearables,” writes Cooper.

IEEE Spectrum reporter Prachi Patel writes that researchers from MIT and Google Brain have developed a new open-source tool that could streamline solar cell improvement and discovery. The new system should “speed up development of more efficient solar cells by allowing quick assessment of a wide variety of possible materials and device structures,” writes Patel.

Prof. Regina Barzilay speaks with Good Morning America about her work developing a new AI tool that could “revolutionize early breast cancer detection” by identifying patients at high risk of developing the disease. “If this technology is used in a uniform way,” says Barzilay, “we can identify early who are high-risk patients and intervene.”

Washington Post reporter Steve Zeitchik spotlights Prof. Regina Barzilay and graduate student Adam Yala’s work developing a new AI system, called Mirai, that could transform how breast cancer is diagnosed, “an innovation that could seriously disrupt how we think about the disease.” Zeitchik writes: “Mirai could transform how mammograms are used, open up a whole new world of testing and prevention, allow patients to avoid aggressive treatments and even save the lives of countless people who get breast cancer.”

STAT reporter Katie Palmer writes that MIT researchers have developed a new machine learning model that can "flag treatments for sepsis patients that are likely to lead to a ‘medical dead-end,/ the point after which a patient will die no matter what care is provided.”

Wise Systems, an AI-based delivery management platform originating from MIT’s Media Lab, has applied machine learning to real-time data to better plan delivery routes and schedules for delivery drivers, reports Susan Galer for Forbes. “The system can more accurately predict service times, taking into account the time it takes to complete a stop, and factoring in the preferences of the retailer, hotel, medical institution, or other type of client,” says Allison Parker of Wise Systems.

Ikigai, an MIT startup, is building automated workflows where human decision making will be a part of the process, reports Ron Miller for Tech Crunch. “What we saw is that there are use cases… [that involve] manual processes in the organizations that were extremely difficult to automate because a fundamental step involved humans making judgements or decisions with data, and where both the data and rules they’re operating on would change very often,” co-founder and CEO Vinayak Ramesh M.Eng ‘18, ‘12 tells Miller.

Air & Space Forces Magazine reporter Amanda Miller spotlights the Department of Air Force-MIT AI Accelerator, which is focused on furthering the science of AI. Thanks to such a close connection with “a world-class academic institution,” said Col. Tucker Hamilton, “we’re making advancements revolutionary to the entire field—the entire world.”

Writing for The Wall Street Journal, Prof. Kate Kellogg explores how managers can more effectively help their employees transition to using new technologies. “Managers need to realize that introducing emerging technologies such as artificial intelligence, data analytics and robotics aren’t straightforward,” writes Kellogg. “Managers who hope to successfully implement these technologies need to focus on issues of employee status and roles, and the amount of new work that will need to be done.”

MIT researchers developed a new control system for the mini robotic cheetah that allows the robot to jump and traverse uneven terrain, reports Jules Suzdaltsev for Mashable. “There’s a camera for processing real-time input from a video camera that then translates that information into body movements for the robot,” Suzdaltsev explains.

Writing for Popular Science, Sarah Scoles spotlights DAILy (Developing AI Literacy) initiative, a project by MIT researchers and students aimed at teaching middle schoolers “the technical, creative, and ethical implications of AI, taking them from building PB&Js to totally redesigning YouTube’s recommendation algorithm.”

During CNBC’s Technology Executive Council summit, Prof. Christopher Magee related how “allocating R&D resources efficiently is a critical skill, but one that most companies struggle with,” according to CNBC reporter Susan Caminiti. Magee's latest research “uses AI to predict the speed of the development of specific new innovations, all with the goal of deploying resources smartly and effectively,” writes Caminiti.

New York Times Style Magazine reporter Zoë Lescaze explores the work of artist Agnieszka Kurant and her new installation at MIT. “Looping black lines composed of high-tech lights were designed to simulate the flow of ink scrawl across the facades of two new buildings, as though an invisible hand were repeatedly signing the walls,” writes Lescaze. “Kurant worked with computer scientists to create two collective signatures — one for the scientific and academic community at MIT and another for Cambridge residents.”

Institute Prof. Daron Acemoglu and his colleagues make the case in a piece for Wired that using the Turing test to help develop AI technologies for businesses has led to a “fundamental mismatch between the needs of business and the way AI is currently being conceived by many in the technology sector.” They write: “Businesses that find a productive way of using machine intelligence will lead by example, and their example can be followed by other companies and researchers freeing themselves from the increasingly unhelpful AI paradigm.”

Prof. Julie Shah speaks with Washington Post reporter Tatum Hunter about whether AI technologies will ever surpass human intelligence. “Any positive or negative use or outcome of this technology isn't predetermined. We have a lot of choices that we make,” Shah says. “And these should not be decisions that are left solely to technologists. Everybody needs to be involved because this technology has such a broad impact on all of us.”