Topics covered include: representation and inference in first-order logic, modern deterministic and decision-theoretic planning techniques, basic supervised learning methods, and Bayesian network inference and learning. This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5504 (Techniques in Artificial Intelligence).

Projects that target aid toward villages and rural areas in the developing world often face time-consuming challenges, even at the most basic level of figuring out where the most appropriate sites are for pilot programs or deployment of new systems such as solar-power for regions that have no access to electricity. Often, even the sizes and locations of villages are poorly mapped, so time-consuming field studies are needed to locate suitable sites. Now, a team of graduate students at MIT and a social-service group of data scientists have come up with a way of automating parts of that evaluation process, by developing software that can identify houses and even types of houses from readily-available satellite imagery -- potentially saving considerable time that would otherwise be spent sending teams from village to village. Their findings have now been published in the journal Big Data. The multidisciplinary team came together in the course of discussions at MIT's Sidney Pacific graduate dormitory, explains team member Brian Spatocco: "We started talking about this problem, and we realized we all had skills that were relevant."

Researchers at MIT have proven that the brain's cortex doesn't process specific tasks in highly specialized modules -- showing that the cortex is, in fact, quite dynamic when sharing information. Previous studies of the brain have depicted the cortex as a patchwork of function-specific regions. Parts of the visual cortex at the back of the brain, for instance, encode color and motion, while specific frontal and middle regions control more complex functions, such as decision-making. Neuroscientists have long criticized this view as too compartmentalized. In a paper published today in Science, the researchers from the Picower Institute for Learning and Memory at MIT show that, indeed, multiple cortical regions work together simultaneously to process sensorimotor information -- sensory input coupled with related actions -- despite their predetermined specialized roles.

The sequencing of the human genome laid the foundation for the study of genetic variation and its links to a wide range of diseases. But the genome itself is only part of the story, as genes can be switched on and off by a range of chemical modifications, known as "epigenetic marks." Now, a decade after the human genome was sequenced, the National Institutes of Health's Roadmap Epigenomics Consortium has created a similar map of the human epigenome. Manolis Kellis, a professor of computer science and a member of MIT's Computer Science and Artificial Intelligence Laboratory and of the Broad Institute, led the effort to integrate and analyze the datasets produced by the project, which constitute the most comprehensive view of the human epigenome to date. In a paper published today in the journal Nature, Kellis and his colleagues report 111 reference human epigenomes and study their regulatory circuitry, in a bid to understand their role in human traits and diseases.

Today the Association for Computer Machinery (ACM) announced its 2014 fellows, and among the awardees were five researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) -- more than any other academic institution in the world. Srini Devadas, Eric Grimson, Robert Morris, Ronitt Rubinfeld, and CSAIL Director Daniela Rus were among the 1 percent of ACM members to receive the distinction, according to the association's press release. The ACM fellows, chosen from universities, corporations, and research labs, were selected for contributions that have provided key knowledge to the computing field and generated multiple technology advances in industry, commerce, healthcare, entertainment, and education. "While it certainly isn't unprecedented for CSAIL researchers to receive this honor, it is quite remarkable that this year ACM has chosen to recognize five members of our community," said Daniel Jackson, associate director of CSAIL. "We are extremely proud of our PIs who have been selected to be part of such esteemed company."

Scientists have long known that our ability to think quickly and recall information, also known as fluid intelligence, peaks around age 20 and then begins a slow decline. However, more recent findings, including a new study from neuroscientists at MIT and Massachusetts General Hospital (MGH), suggest that the real picture is much more complex. The study, which appears in the journal Psychological Science, finds that different components of fluid intelligence peak at different ages, some as late as age 40. "At any given age, you're getting better at some things, you're getting worse at some other things, and you're at a plateau at some other things. There's probably not one age at which you're peak on most things, much less all of them," says Joshua Hartshorne, a postdoc in MIT's Department of Brain and Cognitive Sciences and one of the paper's authors.

To some degree, that's inevitable: Many people who enroll in MOOCs may have no interest in doing homework, but simply plan to listen to video lectures in their spare time. Others, however, may begin courses with the firm intention of completing them but get derailed by life's other demands. Identifying those people before they drop out and providing them with extra help could make their MOOC participation much more productive. The problem is that you don't know who's actually dropped out -- or, in MOOC parlance, "stopped out" -- until the MOOC has been completed. One missed deadline does not a stopout make; but after the second or third missed deadline, it may be too late for an intervention to do any good.

With the advent of "inherently safe" robots, industrial designers are changing their ideas about the factory of the future. Robots such as ABB's Frida and the Baxter robot from MIT spinoff Rethink Robotics are working "elbow to elbow with people," says Julie Shah, an assistant professor in MIT's Department of Aeronautics and Astronautics and director of the MIT Interactive Robotics Group. "They're designed so that if they hit a person they don't significantly harm them." Working in the Interactive Robotics Group at MIT's Computer Science and Artificial Intelligence Laboratory, Shah is taking the next step: teaching these inherently safe robots how to work together in teams with people, and vice versa. "We're focused on robot learning, planning, and decision making, and how they interact with humans in high intensity and safety critical environments," Shah says.

Today, the National Institutes of Health (NIH) announced the first round of Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative award recipients, including several MIT interdisciplinary teams. The BRAIN Initiative, spearheaded by President Obama in April 2013, challenges the nation's leading scientists to advance our sophisticated understanding of the human mind and discover new ways to treat, prevent, and cure neurological disorders like Alzheimer's, schizophrenia, autism, and traumatic brain injury. "The human brain is one of the most complicated structures in the known universe," said NIH Director Francis Collins. "We have an unprecedented opportunity to develop new technologies that will allow us to map the circuits of the brain, measure activity within those circuits, and understand how their interactions maintain health and modulate human behavior." With the NIH Brain Initiative, the scientific community is charged with accelerating the invention of cutting-edge technologies that can produce dynamic images of complex neural circuits and illuminate the interaction of lightning-fast brain cells.

Seth Teller, a professor of computer science and engineering at MIT who was well known for his efforts to advance human-robot interactions, died yesterday. He was 50, and he had been a member of the MIT faculty since 1994. President L. Rafael Reif announced the news in an email to the MIT community. "I knew Seth as a person of great human warmth and intellectual intensity," Reif wrote in his letter. "He was a brilliant engineer and a gifted advisor with a passion for new challenges. His loss is difficult to grasp."