Rana el Kaliouby, co-founder of MIT spinoff Affectiva, speaks to Asma Khalid from WBUR’s Bostonomix about her company’s work making tech devices that are more emotionally intelligent. “We envision a world where our devices and our technologies are emotional-wear,” says el Kaliouby. “They can sense and respond to your emotions in real time in a way that makes the interaction more positive.”
IBM is joining forces with MIT to establish a new lab dedicated to fundamental AI research, reports the AP. The new lab will focus on, “advancing the hardware, software and algorithms used for artificial intelligence. It also will tackle some of the economic and ethical implications of intelligent machines and look at its commercial application.”
IBM has invested $240 million to develop a new AI research lab with MIT, reports Jing Cao for Bloomberg News. “The MIT-IBM Watson AI Lab will fund projects in four broad areas, including creating better hardware to handle complex computations and figuring out applications of AI in specific industries,” Cao explains.
CNBC reporter Jordan Novet writes that MIT and IBM have established a new lab to pursue fundamental AI research. Novet notes that MIT, “was home to one of the first AI labs and continues to be well regarded as a place to do work in the sector.”
Boston Globe reporter Andy Rosen writes that MIT and IBM have established a new AI research lab. “It’s amazing that we have a company that’s also interested in the fundamental research,” explains Anantha Chandrakasan, dean of the School of Engineering. “That’s very basic research that may not be in a product next year, but provides very important insights.”
Writing for Fortune, Barb Darrow highlights how IBM has committed $240 million to establish a new joint AI lab with MIT. Darrow explains that, “the resulting MIT–IBM Watson AI Lab will focus on a handful of key AI areas including the development of new 'deep learning' algorithms.”
New Scientist reporter Matt Reynolds writes that MIT researchers have developed a new system that can determine how much pain a patient is experiencing. “By examining tiny facial expressions and calibrating the system to each person, it provides a level of objectivity in an area where that’s normally hard to come by,” explains Reynolds.
MIT researchers have developed a new “socially aware” robot that can follow the rules of pedestrian conduct, reports Ben Thompson for The Boston Globe. Thompson explains that the robot, “can seamlessly move with people in public spaces. The technology could eventually lead to robots that perform a variety of delivery and transportation tasks.”
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.
An algorithm developed by Prof. Iyad Rahwan and graduate student Bjarke Felbo has been trained to detect sarcasm in tweets that use emojis, writes Josh Lowe for Newsweek. After reading over 1 billion tweets with emojis, the algorithm predicted, “which emoji would be associated with a given tweet based on its emotional tone,” explains Lowe.
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 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.