The explosion of digital information has brought with it major benefits as well as drawbacks, and among the latter is the paucity of storage space to house all that data and the increasing difficulty of guaranteeing data security and shielding privacy. Factors underlying the surfeit of information include technological innovations, coupled with plummeting prices for digital devices. The volume of digital information increases by a factor of 10 every five years, and Cisco projects that the amount of traffic streaming over the Internet annually will balloon to 667 exabytes by 2013. Accompanying the growth of data is the advent of data scientists, who combine the talents of software programmers, statisticians, and storytellers/artists to sift meaning out of the information deluge. Although the increasing digitization of the world is likely to bring advantages to all kinds of fields and industries via data aggregation and analysis, currently the data flood has greatly contributed to major problems such as the recent financial crisis, where it became apparent that banks and rating agencies were long reliant on models which, although they required a massive amount of data to be fed in, did not mirror actual financial risk.
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University of Washington computer science professor Pedro Domingos is developing CALO, a massive, four-year-old artificial intelligence project to help computers understand human intentions. The DARPA-funded project involves researchers from 25 universities and corporations focusing on many areas of artificial intelligence, including machine learning, natural-language processing, and Semantic Web technologies. CALO, which stands for “cognitive assistant that learns and organizes,” tries to help users by managing information about key people and projects, understanding and organizing information from meetings, and learning and automating routine tasks. For example, CALO can learn about projects and who is involved in those projects, so emails from those people can be given priority and categorized based on subject matter. CALO can also be used to make transcripts of meetings through voice recognition, or perform routine tasks such as purchasing books online, searching for a hotel that meets specific criteria, scheduling meetings, and coordinating people’s schedules. The ultimate goal is to build an artificial intelligence that can serve as a personal assistant that can learn about a user’s needs and preferences and adapt to them without having to be reprogrammed. “It’s an amazingly large thing, and it’s insanely ambitious,” Domingos says. “But if CALO succeeds, it’ll be quite a revolution.”
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Recently discovered problems with the paper records produced by electronic voting machines in Cuyahoga Country, Ohio, could make a recount after next year’s presidential election a disaster. More than 20 percent of the paper printouts from touch-screen voting machines were found to be unreadable. The recount was necessary because the vote counting software crashed twice on election night and the margin of victory was one-half of one percent or less. Election workers found the unreadable ballots while conducting a recount of two races, which involved only 17 of the county’s 1,436 precincts. Board of Elections director Jane Platten says recounting the ballots for the entire county in the 2008 presidential election could take more than a week. Cuyahoga County uses Premier Elections Solutions (formerly Diebold) touch-screen voting machines that store votes on a memory card inside each machine. During the election a paper record of each vote is printed on a long reel of paper that is stored inside the machine. The paper record is used during recounts, but can be damaged or unreadable, usually because of a paper jam while printing. Premier Elections Solutions’ Chris Riggall says the company will investigate the situation.
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Technological advancements in sensing technology makes it possible to take more accurate measurements of brain activity, something computer scientists and neuroscientists say could lead to the discovery of the complex neuronal networks in the brain that allow for simple, automatic movements such as reaching for a glass of water. Virginia Tech and General Motors Research are opening the Laboratory for Neuroinformatics for the purpose of creating algorithms that process the massive amounts of data neuroscientists collect from the brain. The lab will be co-directed by Virginia Tech computer science professor Naren Ramakrishnan and General Motors research scientist K.P. Unnikrishnan. “Neuroscientists are making the transition from studying neurons to studying networks–the sequences of firings and spikes of activity across big groups of neurons,” Ramakrishnan says. “What we are trying to do is analyze all this data and discover something about the network–the connections and relationships.” Unnikrishnan says the many possible applications of neuroscience-related research include analyzing data from cars and maintaining vehicle health. But even greater applications are possible, Unnikrishnan says. “Creation of brain-machine interfaces is the next frontier,” Unnikrishnan says. “Giving senses to people who have lost them–vision, touch, hearing, and motor–would be a contribution to humanity.”
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The number of doctorates awarded in science and engineering (S&E) fields has risen for the fourth consecutive year, according to the National Science Foundation. Last year the United States produced 29,854 doctorate degrees in S&E fields, an increase of nearly 7 percent from the previous year. Computer science doctorates led the way with a 28 percent increase to 1,452 degrees, following a double-digit increase in CS doctorates from the previous year. CS doctorates are up 79 percent since 2002 and now represent a considerable share of not only S&E doctorates but all doctorate degrees. Non-U.S. citizens have been key to the growth in CS doctorate degree production. In the mid-to-late 1990s permanent or temporary visa holders received about half of CS doctorates, but last year they accounted for 61 percent. CS doctorates to U.S. citizens rose 42 percent from 2002 to 2006, but jumped 115 percent for non-U.S. citizens over the same period.
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Rensselaer Polytechnic Institute’s “Adaptive Use Musical Instruments for the Physically Challenged” program enables students with severe physical disabilities to make music by just moving their heads. The system uses a digital video camera to track a student’s head movements on a computer screen and then translates the movements into piano scales or drum beats. Zane Van Dusen, a RPI undergraduate student in computer science and electronic media arts and communication, developed the idea of using a digital video camera to track the user’s head. A cursor is digitally placed on a portion of the student’s head, usually the tip of the nose, to follow the user’s movements. As the cursor moves, sounds are created based on the user’s movements. Moving the head completely in one direction will create a scale climb on the piano or a quick series of drum beats or a drum roll. The project’s ultimate goal is to eventually enable students to compose their own pieces to help students learn the creative process and build communication skills. “The client or patient doesn’t have to be a musician to participate,” says the American Musical Therapy Association’s Al Bumanis. “The goal is not usually a performance, it’s increasing communication skills, understanding, relearning lost skills.”
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