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Anthony Cuthbertson of Newsweek writes that CSAIL researchers have developed a system that allows robots to change their actions based on feedback from the brain waves of a human operator. “Imagine robots or smartphones that could immediately correct themselves when you realize they’re making a mistake,” says PhD candidate Joseph DelPreto.
CSAIL researchers have developed a system that allows robots to detect brain signals generated by human operators, writes Oscar Williams of Huffington Post. The researchers hope the new system could “pave the way for more seamless interactions between robots and humans.”
A feedback system developed by CSAIL researchers allows humans to correct a robot’s mistakes using brain signals, writes Janet Burns for Forbes. The system could be used as a “communication method for those who can't use verbal means, such as immobilized or even 'locked in' victims of paralysis,” explains Burns.
MIT researchers have developed a device that allows humans to guide robots using brainwaves, reports Clive Cookson for the Financial Times. The prototype brain-computer interface “enables a human observer to transmit an immediate error message to a robot, telling it to fix a mistake when it does something wrong.”
Daniel Akst of The Wall Street Journal writes about the wearable device developed by CSAIL researchers that can detect the emotional tone of a conversation. The researchers “are pushing the boundaries by training a computer to take account of such a wide range of factors in making judgments about emotion,” writes Akst.
Science Friday reporter Ira Flatow and Motherboard reporter Daniel Oberhaus discuss a wearable device developed by CSAIL researchers that can detect the emotional tone of a conversation. Oberhaus explains that the researchers hope the device could one day be “applied with much finer emotional granularity, to the point where you can tell if the story was exciting or funny.”
Jonathan Amos reports for the BBC News that scientists around the world are close to obtaining the first image of a black hole. Data from multiple observatories will be compiled at MIT’s Haystack Observatory where “very smart imaging algorithms have had to be developed to make sense of the [Event Horizon Telescope]'s observations,” writes Amos.
In this episode of NOVA that explores how origami is being used in scientific innovations, Prof. Erik Demaine speaks about his work applying math to create new origami figures. “It’s mind blowing that the simple operation of folding lets you transform a boring square of paper into super complicated, crazy 3-D shapes," he explains.
TechCrunch reporter Brian Heater writes that MIT researchers have developed a speech recognition chip that uses a fraction of the power of existing technologies. “The chip is essentially designed to be always on in a low-power mode, switching over when voice is detected, thus making it ideal for technologies like wearable devices,” Heater explains.
CSAIL researchers Tuka Al-Hanai and Mohammad Ghassemi speak to the BBC’s Gareth Mitchell about their system that can detect the tone of a conversation. Ghassemi explains that this research will provide “the first steps toward feedback,” for people who struggle to read social cues.
CSAIL researchers have developed a wearable AI system that allows users to detect the tone of a conversation in real-time, reports Janet Burns for Forbes. Using two algorithms to analyze data, the researchers were able to “classify each five-second chunk of conversation as positive, neutral, or negative,” explains Burns.
A new study conducted by MIT researchers shows that ride-sharing services could reduce the number of cars on the road in New York City by 75 percent, according to the BBC News. The researchers found that “a fleet of 3,000 four-passenger taxis could do the same job as the current fleet of 13,000 yellow cabs in New York City.”
BBC News reports that CSAIL researchers have created an algorithm that can manipulate still objects in photographs and videos. The technique doesn’t require any special cameras, which makes it great for improving the realism in augmented reality games like Pokémon Go.
Dan Misener reports for CBC News that MIT researchers have developed a new wireless tracking system, called Chronos, that can pinpoint a user’s location to within centimeters. Misener explains that Chronos, “can be used to turn a regular Wi-Fi router into a sort of radar system that can detect objects and where they are in the world.”
MIT researchers have developed a device that can trace the movement of a person’s silhouette through a wall using wireless signals, reports Robert Ferris for CNBC. The device can "distinguish up to 15 different individuals with 90 percent accuracy,” Ferris explains.