Scientists make printer that needs no ink, only water

© Flickr.com/zaveqna/cc-by-nc-sa 2.0 Scientists have created a printer that uses just water to print instead of ink. After about 22 hours, the paper fades back to a plain sheet of white paper, allowing it to be reused. A group of chemists assert that the “water-jet” technology, that is capable of reprinting numerous times, spares people their money and saves trees. "Several international statistics indicate that about 40 percent of office prints [are] taken to the waste paper basket after a single reading," Sean Xiao-An Zhang, a chemistry professor at Jilin University in China, who supervised the work, said. The paper alone is not ordinary at all, as it is coated with an invisible dye that shows color when water hits it. Later on, the print slowly fades away within a matter of 22 hours, but disappears much faster if exposed to high levels of heat. According to the designers, the print comes out clear and the technology is not expensive at all. "Based on 50 times of rewriting, the cost is only about 1 percent of the inkjet prints," Zhang said in a video. If one page were reused just 12 times, the cost would only be one-seventeenth that of its inkjet counterpart. Zhang said dye-treating the paper, of the type generally used for printing, added about five percent to its price, but this is more than compensated for by the saving...
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Researchers Teach Machines To Learn Like Humans

A team of scientists has developed an algorithm that captures our learning abilities, enabling computers to recognize and draw simple visual concepts that are mostly indistinguishable from those created by humans. The work, which appears in the latest issue of the journal Science, marks a significant advance in the field -- one that dramatically shortens the time it takes computers to 'learn' new concepts and broadens their application to more creative tasks. A team of scientists has developed an algorithm that captures our learning abilities, enabling computers to recognize and draw simple visual concepts that are mostly indistinguishable from those created by humans. "Our results show that by reverse engineering how people think about a problem, we can develop better algorithms," explains Brenden Lake, a Moore-Sloan Data Science Fellow at New York University and the paper's lead author. "Moreover, this work points to promising methods to narrow the gap for other machine learning tasks." The paper's other authors were Ruslan Salakhutdinov, an assistant professor of Computer Science at the University of Toronto, and Joshua Tenenbaum, a professor at MIT in the Department of Brain and Cognitive Sciences and the Center for Brains, Minds and Machines. When humans are exposed to a new concept -- such as new piece of kitchen equipment,...
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