Scientific and Research Applications

Social Robot Jibo Has Enough Charm to Raise Nearly $600K

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Kris Holt of Tech News World reports, “A crowdfunding campaign for Jibo, a little robot designed to become one of the family, kicked off Wednesday on Indiegogo, and with 29 days remaining, it already has raised more than US$577,000 — nearly six times its $100,000 target. The voice-controlled robot with a friendly face is a do-it-all personal assistant. Communicating with users in a human voice, it can learn individual preferences, relay messages and reminders, and function as a video conferencing device, for starters. It can take pictures, provide information from the Web or apps, order food and display e-books.” Read more

Deep Neural Networks Could Help Discover Unique Particles Like Higgs Boson

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Derrick Harris of GigaOM reports, “Researchers from the University of California, Irvine, have published a paper demonstrating the effectiveness of deep learning in helping discover exotic particles such as Higgs bosons and supersymmetric particles. The research, which was published in Nature Communications, found that modern approaches to deep neural networks might be significantly more accurate than the types of machine learning scientists traditionally use for particle discovery and might also save scientists a lot of work. To get a sense of how challenging particle discovery is, consider that a collider can produce 100 billion collisions per hour and only about 300 will produce a Higgs boson. Because the particles decay almost immediately, scientists can’t expressly identify them, but instead must analyze (and sometimes infer) the products of their decay.” Read more

Cornell Team Teaching a Robot to Do Complex Tasks

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John Biggs of Tech Crunch reports, “A new research project by a computer science team at Cornell University is using human volunteers to train robots to perform tasks. How is it unique? They’re showing robots how to infer actions based on very complex, human comments. Instead of having to say ‘move arm left 5 inches’ they are hoping that, one day, robots will respond to ‘Make me some ramen’ or ‘Clean up my mess.’ The commands are quite rudimentary right now and focus mostly around loose requests like “boil the ramen for a few minutes” which, with enough processing, can be turned into a step-by-step set of commands. For example, in the video above a subject asks for an affogato, basically coffee with ice cream. The robot has learned the basic recipe and so uses what is at hand — a barrel of ice cream, a bowl, and a coffee dispenser — to produce a tasty treat for its human customer.” Read more

NSF Funds Claremont McKenna Mathematics Professor to Research Compressive Signal Processing

cmCLAREMONT, Calif.–(BUSINESS WIRE)–Claremont McKenna College assistant professor of mathematics Deanna Needell has been awarded a prestigious, five-year National Science Foundation CAREER grant of more than $413,000 for her research on the practical application of compressive signal processing (CSP). The grant, from the NSF’s Faculty Early Career Development Program, supports junior faculty who exemplify the role of teacher-scholars through outstanding research, excellent education, and integration of education and research within the context of the mission of their organizations. Read more

Does AI System Eugene Goostman Pass the Turing Test?

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Dante D’Orazio of The Verge reports, “Eugene Goostman seems like a typical 13-year-old Ukrainian boy — at least, that’s what a third of judges at a Turing Test competition this Saturday thought. Goostman says that he likes hamburgers and candy and that his father is a gynecologist, but it’s all a lie. This boy is a program created by computer engineers led by Russian Vladimir Veselov and Ukrainian Eugene Demchenko. That a third of judges were convinced that Goostman was a human is significant — at least 30 percent of judges must be swayed for a computer to pass the famous Turing Test. The test, created by legendary computer scientist Alan Turing in 1950, was designed to answer the question ‘Can machines think?’ and is a well-known staple of artificial intelligence studies.” Read more

“Watt-sun” Hopes to Improve Solar Power with Machine Learning

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Katie Fehrenbacher of GigaOM recently asked, “What happens when you leverage technologies like IBM’s artificial intelligence engine Watson for clean power? The answer is the awesomely named Watt-sun project, a machine learning platform that IBM Research has quietly been building over the last year, and which is now highly accurate at predicting how cloud cover, weather and atmosphere (among many other data points) affect the way solar panel systems operate.Solar forecasting has been around as long as solar panels have been plugged into the grid. But the forecasting systems historically haven’t been all that accurate, given that so many factors can contribute to the amount of sunlight that’s able to descend from the sky and onto the solar panel and then get converted into electricity.” Read more

New Supercomputer at Lawrence Livermore Available for Collaborative Research

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Donald B. Johnston of Phys.org reports, “Catalyst, a first-of-a-kind supercomputer at Lawrence Livermore National Laboratory (LLNL), is available to industry collaborators to test big data technologies, architectures and applications. Developed by a partnership of Cray, Intel and Lawrence Livermore, this Cray CS300 high performance computing (HPC) cluster is available for collaborative projects with industry through Livermore’s High Performance Computing Innovation Center (HPCIC). ‘Over the next decade, global data volume is forecasted to reach more than 35 zettabytes,’ (a zettabyte is a trillion gigabytes) said Fred Streitz, director of the HPCIC. ‘That enormous amount of unstructured data provides an opportunity. But how do we extract value and inform better decisions out of that wealth of raw information?’ ” Read more

MIT, UW Researchers Develop System that Can Solve Word Problems

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Alexander Saltarin of Tech Times reports, “Computer science researchers have developed a new computer system that has the capability of solving word problems automatically. The new system was developed by researchers from the Massachusetts Institute of Technology (MIT) with the help of other researchers from the University of Washington. Most of the research to develop the new system was conducted at the Computer Science and Artificial Intelligence Laboratory in the MIT. Linguistic problems have always been a tricky subject for computer scientists. Unlike math, which is considered by many experts as a pure and accurate ‘language,’ computers often have difficulties in understanding the sometimes vague and confusing languages that humans use on a daily basis. However, the new computer system can actually be used to solve word problems often seen in basic math lessons at schools.” Read more

SMArc: Optimizing Energy Consumption with Semantic Technologies

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The Daily Fusion reports, “Semantic Middleware Architecture (SMArc) is the result of a research conducted by the Department of Engineering and Telematics Architectures of Centro de Investigación en Tecnologías del Software y Sistemas Multimedia (CITSEM) of the Technical University of Madrid (Universidad Politécnica de Madrid, UPM). SMArc aims to optimize data transmission for smart grid users thanks to an effective mechanism for data exchange. This way, users can be simultaneously consumers and energy producers.” Read more

Top Tech Companies Setting Their Sights on True Artificial Intelligence

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Brandon Bailey of San Jose Mercury News reports, “The latest Silicon Valley arms race is a contest to build the best artificial brains. Facebook, Google and other leading tech companies are jockeying to hire top scientists in the field of artificial intelligence, while spending heavily on a quest to make computers think more like people. They’re not building humanoid robots — not yet, anyway. But a number of tech giants and startups are trying to build computer systems that understand what you want, perhaps before you knew you wanted it. ‘It’s important to position yourself in this market for the next decade,’ said Yann LeCunn, a leading New York University researcher hired to run Facebook’s new A.I. division in December. ‘A lot is riding on artificial intelligence and content analysis, and on being smarter about how people and computers interact’.” Read more

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