A team from MIT Lincoln Laboratory's Bioengineering Systems and Technologies Group was named a first-place subchallenge winner at the 2014 Audio/Visual Emotion Challenge and Workshop (AVEC 2014), the fourth annual competition that invites participants to use multimedia processing and machine learning to analyze subjects' emotional states or estimate subjects' level of depression. Held at the annual Association for Computing Machinery (ACM) International Conference on Multimedia, the challenge gauges the success of entrants' approaches to automated emotion detection on a set of common benchmarks. In 2014, two subchallenges were presented: continuously distinguishing emotions and estimating the level of subjects' depression from audio and visual data. Of the 14 groups competing in the 2014 depression assessment subchallenge, Lincoln Laboratory's team was the most successful in predicting a depression score. Participants in this subchallenge estimate the severity of subjects' depression from either vocal characteristics detected in audio or facial signs identified in video recordings, or both.

The annual MIT IDEAS Global Challenge awards ceremony awarded $79,500 on Monday night to 13 student-led teams to further develop inventions and ideas intended to solve pressing environmental and health challenges in developing countries. "Today marks an important opportunity for emerging entrepreneurs to take a big leap forward in their journey to improve the quality of life in communities around the world," Keely Swan, the Public Service Center's IDEAS Global Challenge program administrator, said in her welcoming remarks. Launched and run by MIT students, the winning ventures took home prizes of $10,000, $7,500, $5,000, and $1,500, to further support prototyping and field-testing, among other things. CleanData-CleanWater, a $10,000 winner last night, plans to use its earnings to manufacture 1,000 of its sensors, which gather previously unavailable data on water filter usage in developing countries. The sensors fit on a filter's tap and track how long the tap stays up or down, measuring the frequency and duration of use. The company plans to integrate the sensors into a new line of ceramic pot water filters being installed across Ghana by the company Pure Home Water, a previous IDEAS winner.

Computer scientists at MIT and Israel's Technion have discovered an unexpected source of information about the world's languages: the habits of native speakers of those languages when writing in English. The work could enable computers chewing through relatively accessible documents to approximate data that might take trained linguists months in the field to collect. But that data could in turn lead to better computational tools. "These [linguistic] features that our system is learning are of course, on one hand, of nice theoretical interest for linguists," says Boris Katz, a principal research scientist at MIT's Computer Science and Artificial Intelligence Laboratory and one of the leaders of the new work. "But on the other, they're beginning to be used more and more often in applications. Everybody's very interested in building computational tools for world languages, but in order to build them, you need these features. So we may be able to do much more than just learn linguistic ...

This week a team featuring multiple Computer Science and Artificial Intelligence Laboratory (CSAIL) researchers took home the grand prize in an international competition centered on autonomous underwater vehicles (AUVs). Members of CSAIL's Marine Robotics Group joined forces with more than 20 other researchers from MIT and Olin College as one of 15 teams competing in the Maritime RobotX Challenge, which took place Oct. 20-26 in Marina Bay, Singapore. Each research group spent the past year developing sensors, computers, and software for the "WAM-V," a self-driving propeller-motored boat that resembles an oversized jet-ski. For the competition, teams traversed a special course to complete tasks that demonstrated motion-planning, control, and autonomy, including avoidance and detection of obstacles, identifying targets, and searching underwater for acoustic sources. MIT-Olin outperformed other universities from Australia, Japan, Singapore, South Korea, and the United States, earning the $24,000 grand prize -- and a not-insignificant amount of international respect.

Einstein's theory of relativity envisions time as a spatial dimension, like height, width, and depth. But unlike those other dimensions, time seems to permit motion in only one direction: forward. This directional asymmetry -- the "arrow of time" -- is something of a conundrum for theoretical physics. An international group of computer scientists believes that the answer is yes. At the IEEE Conference on Computer Vision and Pattern Recognition this month, they'll present a new algorithm that can, with roughly 80 percent accuracy, determine whether a given snippet of video is playing backward or forward.

A restaurant that opened this month in the eastern Chinese province of Shandong uses robots for waiters, boosting efficiency and providing further proof that human beings are superfluous. Machines don't grumble over tips. The traditional hotpot eatery is staffed by more than a dozen automated servers, the distant and brightly colored relations of Star Wars' golden droid C-3PO. The robots whir around the room on little bicycles carrying meat and veggies to be dipped by restaurant-goers into bubbling broth. Customers need not shout, weep or make obscene gestures to get their waiter's attention.

McCarthy created the term "artificial intelligence" and was a towering figure in computer science at Stanford most of his professional life. In his career, he developed the programming language LISP, played computer chess via telegraph with opponents in Russia and invented computer time-sharing. In 1966, John McCarthy hosted a series of four simultaneous computer chess matches carried out via telegraph against rivals in Russia. John McCarthy, a professor emeritus of computer science at Stanford, the man who coined the term "artificial intelligence" and subsequently went on to define the field for more than five decades, died suddenly at his home in Stanford in the early morning Monday, Oct. 24. McCarthy was a giant in the field of computer science and a seminal figure in the field of artificial intelligence.

Steven Flavell examines how the brain sustains or switches between behavioral states at the molecular and circuit levels. Using C. elegans as a model, he probes neuromodulators that coordinate activity throughout neural circuits to generate locomotion behaviors linked to the feeding or satiety states of an animal. Flavell seeks to uncover fundamental principles of neuromodulation of circuit function and to examine these neuromodulatory principles in mammalian models of switchable behavioral states. His long-term goal is to understand how neural circuits generate sustained behavioral states, and how physiological and environmental information is integrated into these circuits. Gaining a mechanistic understanding of how these circuits function will be essential to decipher the neural bases of sleep and mood disorders.

In recent years, some of the most exciting advances in artificial intelligence have come courtesy of convolutional neural networks, large virtual networks of simple information-processing units, which are loosely modeled on the anatomy of the human brain. Neural networks are typically implemented using graphics processing units (GPUs), special-purpose graphics chips found in all computing devices with screens. A mobile GPU, of the type found in a cell phone, might have almost 200 cores, or processing units, making it well suited to simulating a network of distributed processors. At the International Solid State Circuits Conference in San Francisco this week, MIT researchers presented a new chip designed specifically to implement neural networks. It is 10 times as efficient as a mobile GPU, so it could enable mobile devices to run powerful artificial-intelligence algorithms locally, rather than uploading data to the Internet for processing.

In 2008, Krishna Gupta '09 launched Romulus Capital, a venture capital seed firm, out of his MIT dorm room, scraping together $850,000 to invest in tech startups launched by his classmates. Today, Romulus controls $150 million in funds and other assets, having just raised a new fund of $75 million in June. Now Romulus plans to fund 20 new startups, adding to its existing portfolio of 30 startups, many of which are MIT spinouts. That's not bad for someone completely unfamiliar with the venture capital industry when he launched Romulus as an MIT junior studying materials science and management. "I knew nothing about venture capital, nothing of investing," Gupta says.