Associated Press reporter Jimmy Golen writes about this year’s Sloan Sports Analytics Conference, highlighting the growing use of analytics in sports. “Over two days, college math majors rubbed elbows with team and tech executives looking for fresh ideas and talented minds to implement them,” writes Golen.
Forbes reporter Jessica Baron writes that MIT researchers have developed a platform that “addresses the key issue in cloud computing, which is that the data (or “breadcrumbs”) we leave behind online when we search the web, sign up for subscriptions, use social media, make purchases, etc. is stored on remote data servers where the information is then combined and sold to advertisers.”
New York Times reporter Steve Lohr writes about the MIT AI Policy Conference, which examined how society, industry and governments should manage the policy questions surrounding the evolution of AI technologies. “If you want people to trust this stuff, government has to play a role,” says CSAIL principal research scientist Daniel Weitzner.
Writing for Wired, Prof. Joi Ito, director of the Media Lab, writes about the need for creating more open, global datasets for such critical issues as air quality monitoring. “We need to start using data for more than commercial exploitation,” argues Ito, “deploying it to understand the long-term effects of policy, and create transparency around those in power—not of private citizens.”
Boston Globe reporter Jessie Scanlon spotlights Prof. Regina Barzilay’s work developing machine learning systems that can identify patients at risk of developing breast cancer. Barzilay is creating “software that aims to teach a computer to analyze mammogram images more effectively than the human eye can and to catch signs of cancer in its earliest phases.”
MIT researchers have found that it’s easy to reidentify anonymized data compiled in massive datasets, reports Kelsey Campbell-Dollaghan for Fast Company. The findings show that urban planners, tech companies and designers, “who stand to learn so much from these big urban datasets,” writes Campbell-Dollaghan, “need to be careful about whether all that data could be combined to deanonymize it.”
A new study by MIT researchers provides evidence that compiling massive anonymized datasets of people’s movement patterns can put their private data at risk, reports the Xinhua news agency. The researchers found “data containing ‘location stamps’ – information with geographical coordinates and time stamps – could be used to easily track the mobility trajectories of how people live and work.”
MIT researchers examined why a third of Wikipedia deliberations go unresolved and developed a new tool that could be used to help resolve more discussions, reports Samantha Cole for Motherboard. Cole explains that “the tool uses the data they found and analyzed in this research, to summarize threads and predict when they’re at risk of going stale.”
TechCrunch reporter Ingrid Lunden highlights RapidSOS, an MIT startup that “helps increase the funnel of information that is transmitted to emergency services alongside a call for help.”
Smithsonian reporter Randy Rieland writes that MIT researchers have developed a machine learning model that can detect speech and language patterns associated with depression. The researchers note that the system is intended to assist, not replace clinicians. “We’re hopeful we can provide a complementary form of analysis,” explains Senior Research Scientist James Glass.
Wall Street Journal reporter Ryan Dezember writes about Thasos Group, a company co-founded by Prof. Alex “Sandy” Pentland that aims to “paint detailed pictures of the ebb and flow of people, and thus their money” by gathering anonymous data about people’s activities through their smartphone usage.
Motherboard reporter Daniel Oberhaus writes that MIT researchers have developed an AI system that can generate theories about the physical laws of imaginary universes. Oberhaus writes that in the future the system could be used to help understand “massively complex datasets, such as those used in climate modeling or economics.”
MIT researchers have developed a language translation model that operates without human annotations and guidance, reports Liangyu for Xinhua news agency. The system, which may enable computer-based translations of the thousands of languages spoken worldwide, is “a step toward one of the major goals of machine translation, which is fully unsupervised word alignment,” Liangyu explains.
MIT researchers have developed a new technique to store information using lasers, reports Meriame Berboucha for Forbes. “By using pulses of light, a material can be flipped from one state to another and return to its original state,” Berboucha explains. “As a result, a wave of new-generation data storage devices could be in our homes and workplaces very soon.”
Tom Loftus of The Wall Street Journal highlights a study co-authored by MIT Prof. Maryam Farboodi that finds big data plays an important role in raising capital from investors and could contribute to the growing divide between large and small companies.