Steve Worswick, botmaster of Mitsuku, was awarded the bronze medal and $4000 cash prize for creating the world's "most human computer" in the Loebner Prize Contest 2013, an annual Turing Test. The contest this year was held at the Ulster University, Magee Campus, Londonderry/Derry, Northern Ireland. Steve Worswick is a native of Yorkshire, UK, and has worked on Mitsuku for 9 years. This year the Loebner Prize Contest attracted 15 entries from around the world. Pandorabots submitted 6 of those entries, based on the results of an internal Divabot contest to select the best, most unique AIML bots hosted by Pandorabots.

The National Information Infrastructure (NII) will have profound effects on the lives of every citizen. It promises to deliver to people in their homes and offices a vast array of information in many forms, changing the ways in which business is conducted, offering new educational opportunities, bringing geographically dispersed library resources and entertainment materials to everyone's doorstep. It will connect people to people, and help them with their jobs and tasks. For the NII to be useful, however, people will need easy and efficient access to its resources. Today's computers are complex and difficult to use, even for experts. The NII will be orders of magnitude more complex than current systems; it could easily become a labyrinth of databases and services that is inconvenient for experts and inaccessible to many Americans. The field of artificial intelligence (AI) can play a pivotal role in meeting major challenges of the NII. AI uses the theoretical and experimental tools of ...

The Annual Conference on Innovative Applications of Artificial Intelligence offers case studies of deployed applications with measurable benefits whose value depends on the use of AI technology. In addition, many conferences supplement these case studies with papers and invited talksthat address emerging areas of AI technology or applications. IAAI was an independent conference during its early years. Recently, it has been organized as an independent program within the National Conference, with schedules coordinated to allow attendees to move freely between IAAI and National Conference sessions. Most years IAAI and the National Conference papers are published in a joint proceedings.

For the first time ever, a poker-playing computer program challenged two top-level poker professionals in a controlled scientific experiment with real money on the line. The program, Polaris, took on two of the sharpest poker players in the world - Phil "The Unabomber" Laak and Ali Eslami. The $50,000 match took place in Vancouver, Canada, in conjunction with the annual conference of the Association for the Advancement of Artificial Intelligence (AAAI), July 23 and 24. The competition consisted of four 500-hand duplicate matches. In each duplicate match, the same series of cards were dealt in two parallel Man versus Machine matches, with teammates playing the opposite hands in each game.

Imagine seeing a dozen pictures flash by in a fraction of a second. You might think it would be impossible to identify any images you see for such a short time. However, a team of neuroscientists from MIT has found that the human brain can process entire images that the eye sees for as little as 13 milliseconds -- the first evidence of such rapid processing speed. That speed is far faster than the 100 milliseconds suggested by previous studies. In the new study, which appears in the journal Attention, Perception, and Psychophysics, researchers asked subjects to look for a particular type of image, such as "picnic" or "smiling couple," as they viewed a series of six or 12 images, each presented for between 13 and 80 milliseconds.

Every time you open your eyes, visual information flows into your brain, which interprets what you're seeing. Now, for the first time, MIT neuroscientists have noninvasively mapped this flow of information in the human brain with unique accuracy, using a novel brain-scanning technique. This technique, which combines two existing technologies, allows researchers to identify precisely both the location and timing of human brain activity. Using this new approach, the MIT researchers scanned individuals' brains as they looked at different images and were able to pinpoint, to the millisecond, when the brain recognizes and categorizes an object, and where these processes occur. "This method gives you a visualization of'when' and'where' at the same time. It's a window into processes happening at the millisecond and millimeter scale," says Aude Oliva, a principal research scientist in MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL).

Do you have a forgettable face? Many of us go to great lengths to make our faces more memorable, using makeup and hairstyles to give ourselves a more distinctive look. Now your face could be instantly transformed into a more memorable one without the need for an expensive makeover, thanks to an algorithm developed by researchers in MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). The algorithm, which makes subtle changes to various points on the face to make it more memorable without changing a person's overall appearance, was unveiled earlier this month at the International Conference on Computer Vision in Sydney. "We want to modify the extent to which people will actually remember a face," says lead author Aditya Khosla, a graduate student in the Computer Vision group within CSAIL.

The human brain has 100 billion neurons, connected to each other in networks that allow us to interpret the world around us, plan for the future, and control our actions and movements. MIT neuroscientist Sebastian Seung wants to map those networks, creating a wiring diagram of the brain that could help scientists learn how we each become our unique selves. In a paper appearing in the Aug. 7 online edition of Nature, Seung and collaborators at MIT and the Max Planck Institute for Medical Research in Germany have reported their first step toward this goal: Using a combination of human and artificial intelligence, they have mapped all the wiring among 950 neurons within a tiny patch of the mouse retina. Composed of neurons that process visual information, the retina is technically part of the brain and is a more approachable starting point, Seung says. They also identified a new type of retinal cell that had not been seen before.

About 10 percent of the U.S. population suffers from dyslexia, a condition that makes learning to read difficult. Dyslexia is usually diagnosed around second grade, but the results of a new study from MIT could help identify those children before they even begin reading, so they can be given extra help earlier. The study, done with researchers at Boston Children's Hospital, found a correlation between poor pre-reading skills in kindergartners and the size of a brain structure that connects two language-processing areas. Previous studies have shown that in adults with poor reading skills, this structure, known as the arcuate fasciculus, is smaller and less organized than in adults who read normally. However, it was unknown if these differences cause reading difficulties or result from lack of reading experience.

With the recent launch of MIT's Institute for Medical Engineering and Science, MIT News examines research with the potential to reshape medicine and health care through new scientific knowledge, novel treatments and products, better management of medical data, and improvements in health-care delivery. At the end of 2012, the National Public Radio show "Fresh Air" featured a segment in which its linguistics commentator argued that "big data" should be the word of the year. The term refers not only to the deluge of data produced by the proliferation of Internet-connected, sensor-studded portable devices but also to innovative techniques for analyzing that data; and big data has received a good deal of credit for Barack Obama's victory in the last presidential election. Certainly, the term was in heavy use around MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), which in 2012 launched a new big-data initiative called bigdata@CSAIL. Several of the researchers affiliated with bigdata@CSAIL are developing new techniques for processing medical data, to make it more accessible to both physicians and patients and to find correlations that could improve diagnosis or choice of therapies.