A report released by MIT startup Cambridge Mobile Telematics (CMT) shows that one in four drivers were using a smartphone just before an accident occurred, reports The Boston Globe’s Matt Rocheleau. Prof. Samuel Madden, founder and chief scientist at CMT, explains that the study shows “people are using their phones a lot, and that’s playing a role in the accidents.”
Prof. Sertac Karaman and postdoc Lex Fridman speak with Boston Globe columnist Scott Kirsner about why companies developing self-driving cars should share data. Kirsner writes that Fridman explains it would be “‘extremely useful’ to create some kind of database where manufacturers could deposit — or withdraw — models and strategies that would make their vehicles safer.”
Graduate student Maimuna Majumder writes for NPR about her research examining what caused an outbreak of the mumps in Arkansas in 2016. Majumder writes that her research shows, “why herd immunity is so important. When we vaccinate, we protect not only ourselves but the most vulnerable members of our communities, too.”
Patrick Rishe of Forbes writes about the 2017 MIT Sloan Sports Analytics Conference. Rishe notes that the conference’s “combination of knowledge, presentations, and networking opportunities is off-the-charts, and a must for programs who wish to be taken seriously in the Sports Business space.”
Quentin Palfrey, executive director of J-PAL North America, speaks with Devin Thorpe of Forbes about how J-PAL aims to reduce poverty through academic research. Palfrey explains that “by transforming government and building a movement for evidence-based policy, we can help lift millions in the United States out of poverty.”
Nima, a startup founded by alumni Shireen Yates and Scott Sundvor, has been named to CNBC’s list of 25 promising start-ups for its portable food allergy detector, reports Ashley McHugh-Chiappone. “I just wanted a quick, easy way to test a piece of the dish and see for myself if it was gluten-free," says Yates of her inspiration for the device.
BBC reporter Lorelei Mihala highlights DriveWell, an app developed by Profs. Hari Balakrishnan and Sam Madden, aimed at addressing the problem of distracted driving. “We wanted to show that smartphones could be used to make drivers better,” says Balakrishnan.
Inside Higher Ed reporter Colleen Flaherty reports on a study by MIT researchers on a data-driven model aimed at providing predictions of faculty research success. The study suggests that “operations research scholars recommended for tenure by the new model had better future research records, on average, than those granted tenure by the tenure committees at top institutions.”
MIT researchers have developed a technique to make big data more manageable, writes Kevin Murnane for Forbes. The technique creates "coresets" that can be used by data analysis tools “often applied in computer vision, natural language processing, neuroscience, weather prediction, recommendation systems and more.”
Wall Street Journal reporter Sara Castellanos speaks with research affiliate Matthias Winkenbach about plans to develop a new lab at MIT that would allow researchers to experiment with computer-generated hologram-like images and interactive touch-screen walls. “AR can be a game changer in data and analytics because it’s so much more immersive,” explains Winkenbach.
A new system developed by MIT researchers can predict how a scene will unfold, similar to how humans can visually imagine the future, reports Ed Gent for Scientific American. Graduate student Carl Vondrick explains that the system is “an encouraging development in suggesting that computer scientists can imbue machines with much more advanced situational understanding."
Steven Melendez of NBC News writes that a new system developed by CSAIL researchers can predict the future by examining a photograph. Grad student Carl Vondrick explains that the system’s ability to forecast normal behavior could allow it to be used for applications like self-driving cars.
New Scientist reporter Victoria Turk writes that MIT researchers have developed a system that can predict the future based off of a still image. Turk writes that the system could enable “an AI assistant to recognize when someone is about to fall, or help a self-driving car foresee an accident.”
In an article about food allergies for WBUR’s Bostonomix site, Rachel Zimmerman spotlights the Nima gluten tester, a portable device developed by two MIT graduates that can detect gluten in foods within minutes. The device “can detect gluten in concentrations as low as 20 parts per million,” Zimmerman explains.
Scott Clement of The Washington Post writes that researchers at the Laboratory for Social Machines have found that while the majority of Twitter conversation concerning the presidential campaign has centered around Donald Trump over the past week and a half, “battlegrounds differed in what particular issues or themes they focused on.”