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.
In an article for HuffPost highlighting new developments in AI research, Jovan Kurbalija and Sorina Teleanu feature how MIT researchers, “are one step closer to finding a way to determine why an AI system makes one decision over another.”
Prof. Max Tegmark speaks with Ariel Conn of HuffPost about his new book “Life 3.0: Being Human in the Age of Artificial Intelligence.” “I’m optimistic that we can create a great future with AI,” says Tegmark. “It’s going to require that we really think things through in advance.”
Prof. Max Tegmark speaks with Ira Flatow of PRI’s Science Friday about his new book, “Life 3.0,” which examines how AI might reshape the future. “We should try to create a great future with [technology] by winning this race between the growing power of technology, and the growing wisdom with which we manage it," says Tegmark.
Wall Street Journal reporter Frank Rose reviews Prof. Max Tegmark’s new book, “Life 3.0: Being Human in the Age of Artificial Intelligence.” The book asks reader to ponder the possibility that “a computer program will become not just intelligent but wildly so—and that we humans will find ourselves unable to do anything about it.”
Two new papers from CSAIL researchers “aim to help doctors make better use of the digital information they’re presented with,” writes Adi Gaskell for The Huffington Post. One examines a tool that uses ICU data to choose the best treatment option based on a range of symptoms, while the other facilitates “predictive models based upon an electronic health record system.”
Prof. Max Tegmark speaks to Ian Sample of The Guardian about the likelihood of creating superintelligent AI. “From my perspective as a physicist, intelligence is simply a kind of information processing formed by elementary particles moving around, and there’s no law of physics that says we can’t build machines more intelligent than us,” says Prof. Tegmark.
Renée Richardson Gosline, a senior lecturer in the Sloan School of Management, writes for WBUR’s Cognoscenti about whether it is a good idea to integrate artificial intelligence in all aspects of the online shopping experience. People often “outsource decisions and tasks to technology based on the assumption that it will improve your performance,” explains Gosline.
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.
Wired reporter Liz Stinson writes that researchers from MIT and Google have developed a new algorithm that can automatically retouch images on a mobile phone. “The neural network identifies exactly how to make it look better—increase contrast a smidge, tone down brightness, whatever—and apply the changes in under 20 milliseconds,” Stinson explains.
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.