Prof. Josh Tenenbaum spoke with Bob Oakes on WBUR’s Morning Edition about MIT Intelligence Quest. “This is fundamentally about coupling the basic science of how intelligence works in the human mind and brain, with the quest to engineer new more powerful, more humanlike machines. And to do all of this in service of our mission to make a better world, with a longer-term vision that really only a university like MIT can have,” said Tenenbaum.
Jeff Engel writes for Xconomy about MIT’s ambitions for its newly announced Institute-wide initiative, MIT Intelligence Quest. “If we want A.I. breakthroughs, it’s going to take research in new science. That’s a central inspiration for MIT IQ,” said President Reif.
“The MIT Intelligence Quest or MIT IQ, based at an institution that has been at the forefront of artificial intelligence research since the 1950s, is a far-reaching academic effort to regain the initiative in AI,” writes Clive Cookson for The Financial Times.
Graduate student Joy Buolamwini is featured on NPR’s TED Radio Hour explaining the racial bias of facial recognition software and how these problems can be rectified. “The minimum thing we can do is actually check for the performance of these systems across groups that we already know have historically been disenfranchised,” says Buolanwini.
MIT researchers are stress-testing AI systems by tricking them into misidentifying images, writes Dana Smith of Scientific American. Graduate student Anish Athalye notes that some neural nets are outperforming humans, “but they have this weird property that it seems that we can trick them pretty easily.”
Wired reporter Sandy Ong highlights the work of Prof. Suranga Nanayakkara, who as a postdoc at MIT helped develop the Finger Reader, a device aimed at helping people with visual impairments read without the need for clunky hardware. The Finger Reader, “lets people read only what they’re pointing at, promising a relatively fuss-free experience, especially when out and about.”
Reuters Video visits MIT to learn more about how researchers have developed a new robot, dubbed Jackal, which can navigate pedestrian traffic. Graduate student Michael Everett explains that the robot was designed to operate, “just like people do, so [it] fits in with the flow of traffic.”
Fortune reporter David Morris writes that MIT researchers have tricked an artificial intelligence system into thinking that a photo of a machine gun was a helicopter. Morris explains that, “the research points towards potential vulnerabilities in the systems behind technology like self-driving cars, automated security screening systems, or facial-recognition tools.”
Abigail Beall of New Scientist writes that MIT researchers have developed an algorithm that can trick an AI system, highlighting potential weaknesses in new image-recognition technologies used in everything from self-driving cars to facial recognition systems. “If a driverless car failed to spot a pedestrian or a security camera misidentified a gun the consequences could be incredibly serious.”
Newsweek reporter Katherine Hignett writes that MIT and Harvard researchers have successfully manipulated individual atoms using lasers in one of the largest quantum computer simulations. Hignett writes that, “their technology could help make superfast quantum computers a working reality.”
Boston Globe reporter Alyssa Meyers writes that researchers from MIT and Harvard have demonstrated one of the largest quantum simulators that can trap individual atoms in laser beams. Prof. Vladan Vuletić explains that it is, “a major advance is to be able to align and arrange individual atoms so we can hold on to them and track them.”
CSAIL researchers have developed a system that detects objects and people hidden around blind corners, writes Anthony Cuthbertson for Newsweek. “We show that walls and other obstructions with edges can be exploited as naturally occurring ‘cameras’ that reveal the hidden scenes beyond them,” says lead author and MIT graduate Katherine Bouman.
MIT researchers have developed a new system that can spot moving objects hidden from view by corners, reports Douglas Heaven for New Scientist. “A lot of our work involves finding hidden signals you wouldn’t think would be there,” explains lead author and MIT graduate Katie Bouman.
Wired reporter Matt Simon writes that MIT researchers have developed a new system that analyzes the light at the edges of walls to see around corners. Simon notes that the technology could be used to improve self-driving cars, autonomous wheelchairs, health care robots and more.
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.”