Lifeboat Foundation

With the Zappi, Myenergi offers a compact charging station that can charge the electric vehicle in the garage or carport at home with solar power from the roof without any additional components.

Researchers from the Skolkovo Institute of Science and Technology and Saratov State University have come up with an inexpensive method for visualizing blood flow in the brain. The new technique is so precise it discerns the motions of individual red blood cells — all without the use of toxic dyeing agents or expensive genetic engineering. The study was published in The European Physical Journal Plus.

To understand more about how the brain’s blood supply works, researchers map its blood vessel networks. The resulting visualizations can rely on a variety of methods. One highly precise technique involves injecting fluorescent dyes into the blood flow and detecting the infrared light they emit. The problem with dyes is they are toxic and also may distort mapping results by affecting the vessels. Alternatively, researchers employ genetically modified animals, whose interior lining of blood vessels is engineered to give off light with no foreign substances involved. Both methods are very expensive, though.

Researchers from Skoltech and Saratov State University have devised an inexpensive method for visualizing even the smallest capillaries in the brain. The method — which integrates optical microscopy and image processing — is dye-free and very fine-grained, owing to its ability to detect each and every red blood cell travelling along a blood vessel. Since the number of RBCs in capillaries is not that high, every cell counts, so this is an important advantage over other methods, including dye-free ones.

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Researchers at Human Brain Project partner University of Granada in Spain have designed a new artificial neural network that mimics the structure of the cerebellum, one of the evolutionarily older parts of the brain, which plays an important role in motor coordination. When linked to a robotic arm, their system learned to perform precise movements and interact with humans in different circumstances, surpassing performance of previous AI-based robotic steering systems. The results have been published in the journal Science Robotics.

Johns Hopkins gets the grant to use artificial intelligence to promote healthy aging. The National Institute of Aging has allocated over $20M to Hopkins for them to execute their plans to promote healthy aging.

This new development will considerably help in providing a better lifestyle and living experience to senior citizens. Johns Hopkins will use the allocated funds over five years to build an AI and technology collaboratory (AITC).

The new collaboratory will have members from the Johns Hopkins University schools of medicine and nursing, the Whiting School of Engineering, and the Carey Business School. The collaboratory will also have members from various industries, senior citizens of the country, and technology developers.

Americans have become accustomed to images of Hellfire missiles raining down from Predator and Reaper drones to hit terrorist targets in Pakistan or Yemen. But that was yesterday’s drone war.

A revolution in unmanned aerial vehicles is unfolding, and the U.S. has lost its monopoly on the technology.

Some experts believe the spread of the semi-autonomous weapons will change ground warfare as profoundly as the machine gun did.

Probably some of the best robotic hands developed to date. definitely worth a look, for robotics people.

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How do you collect meaningful data in industrial facilities and generate actionable insights? The Spot API makes it easy to create end-to-end applications that … See more.

Spot’s robust, flexible API and advanced mobility make it a powerful platform to unlock the operational data you really need.

In recent years, computational tools based on reinforcement learning have achieved remarkable results in numerous tasks, including image classification and robotic object manipulation. Meanwhile, computer scientists have also been training reinforcement learning models to play specific human games and videogames.

To challenge research teams working on reinforcement learning techniques, the Neural Information Processing Systems (NeurIPS) annual conference introduced the MineRL competition, a contest in which different algorithms are tested on the same task in Minecraft, the renowned computer game developed by Mojang Studios. More specifically, contestants are asked to create algorithms that will need to obtain a diamond from raw pixels in the Minecraft game.

The algorithms can only be trained for four days and on 8,000,000 samples created by the MineRL simulator, using a single GPU machine. In addition to the training dataset, participants are also provided with a large collection of human demonstrations (i.e., video frames in which the task is solved by human players).

A new study suggests that systems governed by quantum mechanics do not show an exclusively linear evolution in time: in this way, they are sometimes able to unfold into the past and into the future simultaneously.

An international group of physicists concludes in a recent research published in the journal Communications Physics that quantum systems that evolve in one direction or another in time can also be found evolving in unison along both directions. This property shown by quantum systems in certain contexts breaks with the classical temporal conception, in which it is only possible to move forward or backward in time.

The work, carried out by scientists from the universities of Bristol (United Kingdom), Vienna (Austria), the Balearic Islands (Spain) and the Institute of Quantum Optics and Quantum Information (IQOQI-Vienna), shows that the limit between the time that going back and forth can be blurred in quantum mechanics. According to a press release from the University of Bristol, the new study forces us to rethink how the flow of time manifests itself in contexts in which quantum laws play a fundamental role.