Boston Globe columnist Scott Kirsner speaks with Professors Regina Barzilay and Tommi Jaakkola about their Introduction to Machine Learning class. Jaakkola explains that the course connects “the more theoretical, algorithmic stuff students are learning to actual data and problems.”
MIT researchers have developed a new low-power chip that could make voice control practical for simple electronic devices, reports Tim Moynihan for Wired. While other speech-processing platforms use the cloud to process voice commands, “the MIT chip handles much more of that processing itself.”
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.
In a Huffington Post article, Prof. David Autor lists the pressing long-and short-term issues that economists will focus on in 2017. Among the long-term concerns are the effects of artificial intelligence and machine learning, which could potentially disrupt “the value of products produced using manual labor in the developing world.”
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.”
Saqib Shah writes for FOX News that researchers from the Media Lab’s Electome project are launching an interactive tool “that compares tweets shared by the White House with a sampling of those shared by the public.”
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."
Steven Melendez of NBC News writes that a new system developed by CSAIL researchers can predict the future by examining a photograph. Grad student Carl Vondrick explains that the system’s ability to forecast normal behavior could allow it to be used for applications like self-driving cars.
New Scientist reporter Victoria Turk writes that MIT researchers have developed a system that can predict the future based off of a still image. Turk writes that the system could enable “an AI assistant to recognize when someone is about to fall, or help a self-driving car foresee an accident.”
Researchers at MIT have created an algorithm that transforms faces and popular landmarks into scarier versions with impressionistic, sketchy qualities, according to the BBC News. To help teach the algorithm about the concept of scariness, the researchers are asking people vote for the scariest images.
Just in time for Halloween, MIT researchers have launched a website that uses algorithms to generate scary images based off of pictures of popular landmarks and public figures, reports Rebecca Hersher for NPR. The deep-learning algorithm creates “artistic images of high perceptual quality based on examples of images created by humans,” Hersher reports.
Alyssa Newcomb writes for NBC News about the Nightmare Machine, a new system developed by MIT researchers that generates scary images based off of familiar faces and locations. “The Nightmare Machine gets scarier with help from humans, who are asked to vote on which images are the scariest,” Newcomb explains.
Scott Clement of The Washington Post writes that researchers at the Laboratory for Social Machines have found that while the majority of Twitter conversation concerning the presidential campaign has centered around Donald Trump over the past week and a half, “battlegrounds differed in what particular issues or themes they focused on.”