Writing for Wired, Prof. Ethan Zuckerman and Chelsea Barabas and Neha Narula of the Digital Currency Initiative address the difficulties in creating decentralized social media networks. “If users have more control of their data, including the right to export and reuse content they’ve created and friends they follow, they’ll be more willing to experiment with new platforms,” the researchers suggest.
CSAIL researchers have developed an artificial intelligence system that can reduce video buffering, writes Kevin Murnane for Forbes. The system, “adapts on the fly to current network and buffers conditions,” enabling smoother streaming than other methods.
CSAIL researchers have developed an artificial neural network that generates recipes from pictures of food, reports Laurel Dalrymple for NPR. The researchers input recipes into an AI system, which learned patterns “connections between the ingredients in the recipes and the photos of food,” explains Dalrymple.
In an article for The Washington Post, Stephen Pettigrew and Mayya Komisarchik of the MIT Election Data and Science Lab examine the problem with trying to identify duplicate voter registrations using limited information. They write that, “working with registration records that lack essential details…could cause us to draw wildly inaccurate conclusions about the potential for voter fraud.”
In this video for USA Today, Sean Dowling highlights Pic2Recipe, the artificial intelligence system developed by CSAIL researchers that can predict recipes based off images of food. The researchers hope the app could one day be used to help, “people track daily nutrition by seeing what’s in their food.”
Researchers at MIT have developed an algorithm that can identify recipes based on a photo, writes BBC News reporter Zoe Kleinman. The algorithm, which was trained using a database of over one million photos, could be developed to show “how a food is prepared and could also be adapted to provide nutritional information,” writes Kleinman.
MIT researchers have developed a new machine learning algorithm that can look at photos of food and suggest a recipe to create the pictured dish, reports Matt Reynolds for New Scientist. Reynolds explains that, “eventually people could use an improved version of the algorithm to help them track their diet throughout the day.”
CSAIL researchers have trained an AI system to look at images of food, predict the ingredients used, and even suggest recipes, writes Matt Burgess for Wired. The system could also analyze meals to determine their nutritional value or “manipulate an existing recipe to be healthier or to conform to certain dietary restrictions," explains graduate student Nick Hynes.
Forbes reporter Kevin Murnane writes about how MIT researchers have used a computer vision system to examine how several American cities physically improved or deteriorated over time. Murnane writes that the study “provides important support for nuanced versions of traditional theories about why urban neighborhoods change over time.”
Avantika Chilkoti of The New York Times assesses news coverage of the health care debate using Media Cloud, a platform that tracks online stories developed in part by researchers from the MIT Center for Civic Media. Since May, news about Russia and former FBI director James Comey “outstripped coverage of the health care bill on 30 of 67 days,” writes Chilkoti.
UPI reporter Amy Wallace writes that MIT researchers have applied a computer vision system to help quantify the physical improvement of American neighborhoods. The researchers found that “density of highly educated residents, proximity to central business districts and other attractive areas, and the initial safety score assigned by the computer system are strongly related to improvements.”
Wall Street Journal reporter Jason Bordoff writes that MIT researchers have produced a map of the Nairobi bus system using GPS data collected from riders’ mobile phones. “With these networks now mapped, users can access the system more easily and efficiently, and local officials can plan bus and train routes around it,” writes Bordoff.
Prof. Jeff Gore has developed a new technique to help predict the collapse of some ecosystems, writes Gabriel Popkin for Science. Gores hopes the method could be used, “in fisheries where protected areas abut heavily fished ones: If the method works, he hopes fishery managers can use it to set catch limits to avoid a collapse.”
Prof. Marta González writes for Salon about her research showing drivers typically do not choose the optimal route that minimizes travel time. She explains her findings can be used to “design incentive mechanisms to alleviate congestion on busier roads, or carpooling plans based on individuals’ preferred routes.”
Writing for The Guardian, Zofia Niemtus highlights iSpots, a program developed by Prof. Carlo Ratti that uses WiFi to track which spaces are being used at MIT. “Understanding occupancy can help us to use space in a more efficient way – and also improve interaction among the campus community,” Ratti says.