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http://www.ted.com Stephen Wolfram, creator of Mathematica, talks about his quest to make all knowledge computational — able to be searched, processed and manipulated. His new search engine, Wolfram Alpha, has no lesser goal than to model and explain the physics underlying the universe.

TEDTalks is a daily video podcast of the best talks and performances from the TED Conference, where the world’s leading thinkers and doers give the talk of their lives in 18 minutes. Featured speakers have included Al Gore on climate change, Philippe Starck on design, Jill Bolte Taylor on observing her own stroke, Nicholas Negroponte on One Laptop per Child, Jane Goodall on chimpanzees, Bill Gates on malaria and mosquitoes, Pattie Maes on the “Sixth Sense” wearable tech, and “Lost” producer JJ Abrams on the allure of mystery. TED stands for Technology, Entertainment, Design, and TEDTalks cover these topics as well as science, business, development and the arts. Closed captions and translated subtitles in a variety of languages are now available on TED.com, at http://www.ted.com/translate. Watch a highlight reel of the Top 10 TEDTalks at http://www.ted.com/index.php/talks/top10

Continue reading “Computing a theory of everything | Stephen Wolfram” | >

A potentially better way to make oxygen for astronauts in space using magnetism has been proposed by an international team of scientists, including a University of Warwick chemist.

The conclusion is from new research on magnetic phase separation in microgravity published in npj Microgravity by researchers from the University of Warwick in the United Kingdom, University of Colorado Boulder and Freie Universität Berlin in Germany.

Keeping astronauts breathing aboard the International Space Station and other is a complicated and costly process. As humans plan future missions to the Moon or Mars better technology will be needed.

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Capturing details of faraway members of our universe is an understandably complicated affair, but translating these details into the stunning space images that we see from space agencies around the world is equally difficult. It is here that supercomputers step in, helping process the massive amounts of data that are captured by terrestrial and space telescopes. On August 11, that is exactly what Australia’s upcoming supercomputer, called Setonix, helped achieve.

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Capturing details of faraway members of our universe is an understandably complicated affair, but translating these details into the stunning space images that we see from space agencies around the world is equally difficult. It is here that supercomputers step in, helping process the massive amounts of data that are captured by terrestrial and space telescopes. On August 11, that is exactly what Australia’s upcoming supercomputer, called Setonix, helped achieve.

As its first project, Setonix processed the image of a dying supernova — the last stages of a dying star — from data sent to it by the Australian Square Kilometer Array Pathfinder (Askap). The latter is a terrestrial radio telescope, which has 36 individual antennas working together to capture radio frequency data about objects that are far away in space.

Such data contains intricate details about the object being observed. This not only increases the volume of the data being captured by the telescope, but also puts increasing pressure on a supercomputer to process it into a composite image.

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“We are aiming to provide capabilities in the tens to hundreds of milliwatts range, depending on the use case,” Makhijani said.

Compared to the first–gen chip GrAI One, the third–gen GrAI VIP is slightly physically smaller at 7.6 × 7.6 mm, but the company has skipped a process node and migrated to TSMC 12 nm. The chip has slightly fewer neuron cores, 144 compared to 196, but each core is bigger. The result is a jump from 200,000 neuron cores (250,000 parameters) to around 18 million neurons for a total of 48 million parameters. On–chip memory has jumped from 4 MB to 36 MB.

An M.2 hardware development kit featuring GrAI VIP is available now, shipping with GrAI Matter’s GrAI Flow software stack and model zoo for image classification, object detection, and image segmentation.

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The U.S. Brain Research Through Advancing Innovative Neurotechnologies (BRAIN) Initiative is a collaboration among the National Institutes of Health, Defense Advanced Research Projects Agency, National Science Foundation, Food and Drug Administration, Intelligence Advanced Research Projects Activity, and others. Since its inception in 2013, its goal has been to develop and use new technologies to examine how each neuron and neural circuit come together to “record, process, utilize, store, and retrieve vast quantities of information, all at the speed of thought.”

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