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GPS is an utterly pervasive and wonderful technology, but it’s increasingly not accurate enough for modern demands. Now a team of researchers can make it accurate right down to an inch.

Regular GPS registers your location and velocity by measuring the time it takes to receive signals from four or more satellites, that were sent into space by the military. Alone, it can tell you where you are to within 30 feet. More recently a technique called Differential GPS (DGPS) improved on that resolution by adding ground-based reference stations—increasing accuracy to within 3 feet.

Now, a team from the University of California, Riverside, has developed a technique that augments the regular GPS data with on-board inertial measurements from a sensor. Actually, that’s been tried before, but in the past it’s required large computers to combine the two data streams, rendering it ineffective for use in cars or mobile devices. Instead what the University of California team has done is create a set of new algorithms which, it claims, reduce the complexity of the calculation by several order of magnitude.

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Turn off the lights and maximize this image, you can thank me later.

=)


See more GIFs! Create and share your own GIFs, amazing moments and funny reactions with Gfycat.

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Minduploading.org is a collection of pages and articles designed to explore the concepts underlying mind uploading. The articles are intended to be a readable introduction to the basic technical and philosophical topics covering mind uploading and substrate-independent minds. The focus is on careful definitions of the common terms and what the implications are if mind uploading becomes possible.

Mind uploading is an ongoing area of active research, bringing together ideas from neuroscience, computer science, engineering, and philosophy. This site refers to a number of participants and researchers who are helping to make mind uploading possible.

Realistically, mind uploading likely lies many decades in the future, but the short-term offers the possibility of advanced neural prostheses that may benefit us.

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NASA’s Space Technology Mission Directorate is seeking proposals from accredited U.S. universities on behalf of outstanding early-career faculty members who are beginning independent research careers. The grants will sponsor research in specific high-priority areas of interest to America’s space program.

Aligned with NASA’s Space Technology Roadmaps and priorities identified by the National Research Council, the agency has identified topic areas that lend themselves to the early stage innovative approaches U.S. universities can offer for solving tough space technology challenges.

“These grants will allow us to support university faculty in conducting research and technology development to solve some of the challenges that we face on our journey to Mars,” said Steve Jurczyk, associate administrator for NASA’s Space Technology Mission Directorate in Washington. “Engaging the creative and innovative researchers at universities across the country provides opportunities to develop space technologies that drive robotic and human exploration of the solar system and beyond.”

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Researchers have used graphene to create a lens that’s so flat, it’s 300 times thinner than a sheet of paper and weighs just 1 microgram. That means it’s small enough to split a beam of single photons — something that’s going to be crucial if we ever want to develop optical computers that process data at the speed of light.

These optical computers require devices called photonic chips, which store information as photons rather than electrons, and allow that information to move at light speed — and people are pretty excited about it. NASA is already using it, and the technology is getting more and more impressive. But there are still some limitations, and one of those is having lenses thin enough to split beams of light and divert them around the chip.

Attempts to make these lenses in the past have required expensive and impractical materials such as gold, but researchers at Swinburne University of Technology in Australia have been working on a solution, and they’ve managed to produce a lens using graphene oxide that’s not only thin enough to overcome the diffraction limit, but is also cheap, strong, flexible, and easy to produce.

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MIT researchers have developed a chip that can run neural networks. It’s 10 times more efficient than a mobile graphics processors, and it could allow us to have AIs on mobile devices.

Despite the advances in artificial intelligence (AI) technology, most mobile devices remain behind in adapting and implementing these changes in their software. More glaringly, any kind of mobile software that utilizes AI software (such as deep learning and neural networks) offloads these tasks online to outside networks.

It’s all due to one main reason: Power consumption.

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