Tag: silver (page 1 of 3)

Seeds of New Light, Christ, the Anti Christ, Oh My!! Lisa Gawlas

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VERY AUSPICIOUS TIME – Sananda & One Who Serves Galactic Federation of Light

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Supporting Water’s Ascension – by Silvina Mer Being – October-13-2016

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BELEN DE LA PAZ CHANNELING SEPTEMBER – PORTAL 999

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BELEN DE LA PAZ September Portall 9 9 9 Autum Equinox by Belén de la Paz in Fatima

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Enter the Apex of Grace ~ Solene Cosmos September 03 2016

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Sheldan Nidle August-16-2016 Galactic Federation of Light

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Archangel Michael August-09-2016 Galactic Federation of Light

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Sheldan Nidle September 01 2015 Galactic Federation of Light

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8 possible explanations for those bright spots on dwarf planet Ceres

Ceres  Excerpt from cnet.com It's a real-life mystery cliffhanger. We've come up with a list of possible reasons a large crater on the biggest object in the asteroid belt looks lit up like a Christmas tree.  We could be approachin...

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Confirmed: Space Rock Created Swedish Lake

A photo taken through a microscope of shocked minerals from the Hummeln crater in Sweden. Excerpt from news.yahoo.comAfter two centuries of arguing about its origin, scientists have finally confirmed that Hummeln Lake in souther...

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Is playing ‘Space Invaders’ a milestone in artificial intelligence?





Excerpt from latimes.com

Computers have beaten humans at chess and "Jeopardy!," and now they can master old Atari games such as "Space Invaders" or "Breakout" without knowing anything about their rules or strategies.

Playing Atari 2600 games from the 1980s may seem a bit "Back to the Future," but researchers with Google's DeepMind project say they have taken a small but crucial step toward a general learning machine that can mimic the way human brains learn from new experience.

Unlike the Watson and Deep Blue computers that beat "Jeopardy!" and chess champions with intensive programming specific to those games, the Deep-Q Network built its winning strategies from keystrokes up, through trial and error and constant reprocessing of feedback to find winning strategies.

Image result for space invaders

“The ultimate goal is to build smart, general-purpose [learning] machines. We’re many decades off from doing that," said artificial intelligence researcher Demis Hassabis, coauthor of the study published online Wednesday in the journal Nature. "But I do think this is the first significant rung of the ladder that we’re on." 
The Deep-Q Network computer, developed by the London-based Google DeepMind, played 49 old-school Atari games, scoring "at or better than human level," on 29 of them, according to the study.
The algorithm approach, based loosely on the architecture of human neural networks, could eventually be applied to any complex and multidimensional task requiring a series of decisions, according to the researchers. 

The algorithms employed in this type of machine learning depart strongly from approaches that rely on a computer's ability to weigh stunning amounts of inputs and outcomes and choose programmed models to "explain" the data. Those approaches, known as supervised learning, required artful tailoring of algorithms around specific problems, such as a chess game.

The computer instead relies on random exploration of keystrokes bolstered by human-like reinforcement learning, where a reward essentially takes the place of such supervision.
“In supervised learning, there’s a teacher that says what the right answer was," said study coauthor David Silver. "In reinforcement learning, there is no teacher. No one says what the right action was, and the system needs to discover by trial and error what the correct action or sequence of actions was that led to the best possible desired outcome.”

The computer "learned" over the course of several weeks of training, in hundreds of trials, based only on the video pixels of the game -- the equivalent of a human looking at screens and manipulating a cursor without reading any instructions, according to the study.

Over the course of that training, the computer built up progressively more abstract representations of the data in ways similar to human neural networks, according to the study.
There was nothing about the learning algorithms, however, that was specific to Atari, or to video games for that matter, the researchers said.
The computer eventually figured out such insider gaming strategies as carving a tunnel through the bricks in "Breakout" to reach the back of the wall. And it found a few tricks that were unknown to the programmers, such as keeping a submarine hovering just below the surface of the ocean in "Seaquest."

The computer's limits, however, became evident in the games at which it failed, sometimes spectacularly. It was miserable at "Montezuma's Revenge," and performed nearly as poorly at "Ms. Pac-Man." That's because those games also require more sophisticated exploration, planning and complex route-finding, said coauthor Volodymyr Mnih.

And though the computer may be able to match the video-gaming proficiency of a 1980s teenager, its overall "intelligence" hardly reaches that of a pre-verbal toddler. It cannot build conceptual or abstract knowledge, doesn't find novel solutions and can get stuck trying to exploit its accumulated knowledge rather than abandoning it and resort to random exploration, as humans do. 

“It’s mastering and understanding the construction of these games, but we wouldn’t say yet that it’s building conceptual knowledge, or abstract knowledge," said Hassabis.

The researchers chose the Atari 2600 platform in part because it offered an engineering sweet spot -- not too easy and not too hard. They plan to move into the 1990s, toward 3-D games involving complex environments, such as the "Grand Theft Auto" franchise. That milestone could come within five years, said Hassabis.

“With a few tweaks, it should be able to drive a real car,” Hassabis said.

DeepMind was formed in 2010 by Hassabis, Shane Legg and Mustafa Suleyman, and received funding from Tesla Motors' Elon Musk and Facebook investor Peter Thiel, among others. It was purchased by Google last year, for a reported $650 million. 

Hassabis, a chess prodigy and game designer, met Legg, an algorithm specialist, while studying at the Gatsby Computational Neuroscience Unit at University College, London. Suleyman, an entrepreneur who dropped out of Oxford University, is a partner in Reos, a conflict-resolution consulting group.

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A ‘bionic leaf’ that turns sunlight into fuel


Excerpt from cnbc.com

By Robert Ferris



The invention could pave the way for numerous innovations—by converting solar power into biofuels, it may help solve the vexing difficulty of storing unused solar energy, which is one of the most common criticisms of solar power as a viable energy source.
The process could also help make plastics and other chemicals and substances useful to industry and research.


The current experiment builds on previous research led by Harvard engineer Daniel Nocera, who in 2011 demonstrated an "artificial leaf" device that uses solar power to generate usable energy. 

Nocera's original invention was a wafer-like electrode suspended in water. When a current runs through the electrode from a power source such as a solar panel, for example, it causes the water to break down into its two components: hydrogen and oxygen. 

Nocera's device garnered a lot of attention for opening up the possibility of using sunlight to create hydrogen fuel—once considered a possible alternative to gasoline. 

But hydrogen has not taken off as a fuel source, even as other alternative energy sources survive and grow amid historically low oil prices. Hydrogen is expensive to transport, and the costs of adopting and distributing hydrogen are high. A gas station owner could more easily switch a pump from gasoline to biofuel, for example.


Now, Nocera and a team of Harvard researchers figured out how to use the bionic leaf to make a burnable biofuel, according to a study published Monday in the journal PNAS. The biologists on the team genetically modified a strain of bacteria that consumes hydrogen and produces isopropanol—the active ingredient in rubbing alcohol. In doing so, they successfully mimicked the natural process of photosynthesis—the way plants use energy from the sun to survive and grow.

This makes two things possible that have always been serious challenges for alternative energy space—solar energy can be converted into a storable form of energy, and the hydrogen can generate a more easily used fuel.


To be sure, the bionic leaf developments are highly unlikely to replace fossil fuels such as oil and natural gas any time soon—especially as the prices of both are currently so low. But it could be a good supplemental source. 

"One idea Dan [Nocera] and I share, which might seem a little wacky, is personalized energy" that doesn't rely on the power grid, biochemist Pamela Silver, who participated in the study, told CNBC in a telephone interview. 


Typically, people's energy needs are met by central energy production facilities—they get their electricity from the power grid, which is fed by coal- or gas-burning power plants, or solar farms, for example. Silver said locally produced energy could be feasible in developing countries that lack stable energy infrastructure, or could even appeal to people who choose to live off the grid.

"Instead of having to buy and store fuel, you can have your bucket of bacteria in your backyard," Silver said. 

Besides, the experiment was an attempt at proof-of-concept—the scientists wanted to demonstrate what could be done, Silver said. Now that they have mastered this process, further possibilities can be explored.  

"No insult to chemists, but biology is the best chemist there is, so we don't even know what we can make," said Silver. "We can make drugs, materials—we are just at the tip of the iceberg." 

The team hopes to develop many different kinds of bacteria that can produce all sorts of substances. That would mean, potentially at least, setting up the bionic leaf device and then plugging in whatever kind of bacteria might be needed at the moment.

For now, they want to increase the efficiency of the device, which is already much more efficient at photosynthesizing than plants are. Then they will focus on developing other kinds of bacteria to plug into the device.

"The uber goal, which is probably 20 years out," Silver said, "is converting the commodity industry away from petroleum."

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