Lifeboat Foundation

Living on a houseboat may seem very romantic, but the day-to-day misery of hauling water from shore and listening to the thump of the generator can soon take the icing off the cupcake. As a glimpse into what could be the future of aquatic living, two Fraunhofer Institutes and their partners are working on a self-sufficient floating home that creates its own water, electricity, and heat without looking like a works barge.

Housing shortages are a recurring problem in many parts of Europe and the canals of Amsterdam and London show that floating homes are hardly a new idea. But such residences must either be situated in the few places where power and water hook-ups are practical or find tenants who don’t mind living off the grid.

To make it feasible to live comfortably without being tied up to a pier, Fraunhofer and its associates have initiated the Lusation autartec project, which is aimed at a Germany that is looking more toward floating homes for both recreation and residency.

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Poor, old Pluto. Once considered the ninth planet, it was demoted about a decade ago to “dwarf planet” status, meaning that it has different characteristics than the other major planets of our solar system.

Since then, several other dwarf planets about Pluto’s size or bigger have been discovered.

If all of these dwarf planets —and those yet to be seen — were classified as regular planets, we would have an ever-changing number of planets in our solar system. That would be unsettling to astronomers, so they decided Pluto would better fit into this new classification.

Continue reading “Astronomy: Lots of questions about the existence of mysterious Planet Nine” »

The job advertisement was highly specific: applicants had to be passionate about computer games and live in the UK. Oh, and they also had to be amputees who were interested in wearing a futuristic prosthetic limb.

James Young knew straight away he had a better shot than most. After losing an arm and a leg in a rail accident in 2012, the 25-year-old Londoner had taught himself to use a video-game controller with one hand and his teeth. “How many amputee gamers can there be?” he asked himself.

In the end, more than 60 people replied to the ad, which was looking for a games-mad amputee to become the recipient of a bespoke high-tech prosthetic arm inspired by Metal Gear Solid, one of the world’s best-selling computer games. Designed and built by a team of 10 experts led by London-based prosthetic sculptor Sophie de Oliveira Barata, the £60,000 carbon-fibre limb is part art project, part engineering marvel.

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The trolls have gone retro.

This is how Aurora are produced…

Sharing is appreciated!

Google Brain software engineer Quoc Le shares his belief that artificial intelligence and deep learning will shape the future of the world.

The “unbeatable” bot still has much to learn from human players.

Help start a revolution in heathcare!

Sign onto our new letter of support and let your Senator know — the time is NOW to fund the first ever FDA approved research to target ALL the diseases of aging at once.

http://tame.healthspanpolicy.org/

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Whether in the brain or in code, neural networks are shaping up to be one of the most critical areas of research in both neuroscience and computer science. An increasing amount of attention, funding, and development has been pushed toward technologies that mimic the brain in both hardware and software to create more efficient, high performance systems capable of advanced, fast learning.

One aspect of all the efforts toward more scalable, efficient, and practical neural networks and deep learning frameworks we have been tracking here at The Next Platform is how such systems might be implemented in research and enterprise over the next ten years. One of the missing elements, at least based on the conversations that make their way into various pieces here, for such eventual end users is reducing the complexity of the training process for neural networks to make them more practically useful–and without all of the computational overhead and specialized systems training requires now. Crucial then, is a whittling down of how neural networks are trained and implemented. And not surprisingly, the key answers lie in the brain, and specifically, functions in the brain and how it “trains” its own network that are still not completely understood, even by top neuroscientists.

In many senses, neural networks, cognitive hardware and software, and advances in new chip architectures are shaping up to be the next important platform. But there are still some fundamental gaps in knowledge about our own brains versus what has been developed in software to mimic them that are holding research at bay. Accordingly, the Intelligence Advanced Research Projects Activity (IARPA) in the U.S. is getting behind an effort spearheaded by Tai Sing Lee, a computer science professor at Carnegie Mellon University’s Center for the Neural Basis of Cognition, and researchers at Johns Hopkins University, among others, to make new connections between the brain’s neural function and how those same processes might map to neural networks and other computational frameworks. The project called the Machine Intelligence from Cortical Networks (MICRONS).

Continue reading “IARPA Project Targets Hidden Algorithms of the Brain” »