News

Novel Computer Chips Could Bridge Gap Between Computation and Storage

Software written by Jing Li, right, and her students — including Jialiang Zhang, left —allows programmers to directly use existing coding languages with the new Liquid Silicon chips. (Credit: Stephanie Precourt/UW–Madison College of Engineering) Computer chips in development at the University of Wisconsin–Madison could make future computers more efficient and powerful by combining tasks usually kept separate by design. Jing Li, an assistant professor of electrical and computer engineering at UW–Madison, is creating computer chips that can be configured to perform complex calculations and store massive amounts of information within the same integrated unit — and communicate efficiently with other chips. She calls them “liquid silicon.”

Posted in: News, Computers, Electronic Components, Electronics, Semiconductors & ICs

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Supersonic Spray Yields New Nanomaterial for Bendable, Wearable Electronics

Left, photograph of a large-scale silver nanowire-coated flexible film. Right, silver nanowire particles viewed under the microscope. (Credit: S.K. Yoon, Korea University) A new, ultrathin film that is both transparent and highly conductive to electric current has been produced by a cheap and simple method devised by an international team of nanomaterials researchers from the University of Illinois at Chicago and Korea University. The film is also bendable and stretchable, offering potential applications in roll-up touchscreen displays, wearable electronics, flexible solar cells and electronic skin.

Posted in: News, Electronics, Electronics & Computers, Materials, Sensors, Transducers

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Will we be a “multi-planetary” species?

This week's Question: In recent years, hundreds of millions of dollars have been invested into space ventures. SpaceX, an advanced spacecraft manufacturer founded by Elon Musk, has completed more than 30 successful launches since 2006, delivered cargo to the International Space Station, and secured contracts with NASA and other clients. Musk envisions the colonization of Mars as soon as 2022. In September, speaking to the International Astronautical Congress in Mexico, Musk described a 400-foot-tall rocket that would send 100 colonist-passengers at a time to Mars over a period of decades.“One [path] is that we stay on Earth forever and then there will be an inevitable extinction event,” Musk said. “The alternative is to become a spacefaring civilization, and a multi-planetary species.”What do you think? Will we be a “multi-planetary” species?

Posted in: Question of the Week, Aeronautics

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Machine-Learning System Recognizes Sounds from Video

A machine learning system from the Massachusetts Institute of Technology (MIT) recognizes sounds by watching video. The neural network interprets natural sounds in terms of image categories, without hand-annotated training data.

Posted in: News, Machinery & Automation

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Glowing Crystals Cleanse Contaminated Drinking Water

Motivated by public hazards associated with contaminated sources of drinking water, a group of scientists has successfully developed and tested tiny, glowing crystals that detect and trap heavy-metal toxins like mercury and lead.

Posted in: News

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Are you optimistic about AI possibilities?

This week's Question: Today's featured INSIDER story demonstrated a new achievement in artificial intelligence. According to a recently released Stanford University report developed by a standing group of AI scientists, the ability for robots to be self-determined and concerned with their own longevity is a leap far beyond current interest or capabilities. "I'm highly optimistic that artificial intelligence technologies are going to improve the world,” said lead author of the report and University of Texas computer scientist Peter Stone. The researchers cited autonomous transportation, healthcare data computation, and crime prevention as areas that may benefit from the use of AI. What do you think? Are you optimistic about AI possibilities?

Posted in: Question of the Week, Machinery & Automation, Robotics

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AI Algorithm 'Learns' Beyond its Training

A new machine-learning training method developed at the University of Toronto enables neural networks to learn directly from human-defined rules. The achievement supports new possibilities for artificial intelligence in medical diagnostics and self-driving cars.

Posted in: News, Diagnostics, Machinery & Automation, Robotics, Software

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