Lifeboat Foundation

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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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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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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This is a excellent use for the robots.

Brenau University students will soon be able to “be in the classroom” even from remote locations thanks to robots the school will be using.

Continue reading “Brenau aiming to make off-site students more connected through robot computers” »

Computer scientists say as cloud computing allows machines to become more life-like, robots may become the ‘perfect companion’ and people may even go to court in a bid to marry their robots.

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DARPA’s efforts to teach AI “Empathy & Ethics”

The rapid pace of artificial intelligence (AI) has raised fears about whether robots could act unethically or soon choose to harm humans. Some are calling for bans on robotics research; others are calling for more research to understand how AI might be constrained. But how can robots learn ethical behavior if there is no “user manual” for being human?

Researchers Mark Riedl and Brent Harrison from the School of Interactive Computing at the Georgia Institute of Technology believe the answer lies in “Quixote” — to be unveiled at the AAAI-16 Conference in Phoenix, Ariz. (Feb. 12 — 17, 2016). Quixote teaches “value alignment” to robots by training them to read stories, learn acceptable sequences of events and understand successful ways to behave in human societies.

Continue reading “Using stories to teach human values to artificial agents” »

The new mobile AI Chip.

MIT researchers have designed a computer chip that will be able to power a truly mobile artificial intelligence device.

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Intel’s solid-state drives could be poised for a big jump in capacity and speed with new 3D flash chips coming from Micron.

Micron, which makes the flash in Intel’s SSDs, has started volume shipments of its 3D NAND flash chips. The chips could lead to SSDs the size of a pack of gum with more than 3.5TB of storage and standard 2.5-inch SSDs with capacities greater than 10TB.

SSDs have been advancing in capacity and durability. Fixstars last month shipped a 13TB SSD, which is priced at about $1 per gigabyte, or $13,000. This year, SanDisk plans to ship 6TB and 8TB SSDs, while Samsung is aiming to release a 4TB SSD.

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