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.”
New Scientist reporter Matt Reynolds writes that MIT researchers have developed a new brain-computer interface that enables people to correct robots’ mistakes using brain signals. “We’re taking baby steps towards having machines learn about us, and having them adjust to what we think,” explains Prof. Daniela Rus, director of CSAIL.
In this video, TechCrunch explores how MIT researchers are designing new techniques to make it easier for robots to grasp and manipulate objects. Graduate student Nikhil Chavan-Dafle explains that he and his colleagues developed a model that allows robots to “predict how an object is going to move in the grasp.”
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.
The Media Lab will serve as one of the first anchor institutions for a new initiative, the Ethics and Governance of Artificial Intelligence Fund, which will “support research and development to make AI beneficial for humans,” reports Jordan Graham for the Boston Herald.
The Media Lab will serve as a founding institution for a new effort focused on advancing artificial intelligence research for the public good, reports April Glaser for CNBC. Research will focus on everything from investigating how” socially responsible artificially intelligent systems can be designed” to fostering “understanding of the complexities of artificial intelligence.”
CSAIL researchers have found that ride-sharing services could reduce the number of cars on the road by 75 percent, reports Marisa Kendall for The Mercury News. The researchers developed an algorithm that can increase service speeds by 20 percent by rerouting cars to “their most efficient routes, including automatically sending idle cars to areas of high demand.”
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.”
A new study by MIT researchers provides evidence that if more people in New York City were willing to carpool, the city would only need 3,000 taxis, reports Hiawatha Bray for The Boston Globe. With carpooling, “we have fewer vehicles, we have less pollution and we have a better travel situation for everyone,” explains Prof. Daniela Rus.
CSAIL researchers have found that ride-sharing taxis controlled by a citywide computer system could decrease the number of cars on the road in New York City, reports Clive Cookson for the Financial Times. The researchers found that “3,000 four-passenger cars could satisfy 98 per cent of the city’s demand.”
Washington Post reporter Faiz Siddiqui writes that MIT researchers have found that 3,000 four-person cars could serve 98 percent of New York City’s taxi demand. “Fewer cars on roads means improved quality of life for everyone, it means better traffic, it means lower pollution, it’s a better transportation experience,” explains Prof. Daniela Rus.
CNN reporter Matt McFarland writes about a new MIT study that finds ridesharing would allow the number of taxi cabs in Manhattan to be reduced by 78 percent, cutting congestion and pollution in the city. The study showed that “only 3,000 four-person sedans are needed to serve 98% of ride demands in Manhattan.”
Kevin Murnane of Forbes spotlights five innovations developed by CSAIL researchers in 2016. Murnane highlights an ingestible origami robot, a 3-D printed robot with solid and liquid components, a robot that can assist with scheduling decisions, an artificial neural network that can explain its decisions, and an algorithm that can predict human interactions.
MIT researchers have developed a technique to make big data more manageable, writes Kevin Murnane for Forbes. The technique creates "coresets" that can be used by data analysis tools “often applied in computer vision, natural language processing, neuroscience, weather prediction, recommendation systems and more.”
A new system developed by MIT researchers can predict how a scene will unfold, similar to how humans can visually imagine the future, reports Ed Gent for Scientific American. Graduate student Carl Vondrick explains that the system is “an encouraging development in suggesting that computer scientists can imbue machines with much more advanced situational understanding."