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During a news conference in Washington DC Wednesday, NASA revealed that, using the Spitzer Space Telescope, they've found seven new Earth-sized planets orbiting a star just 40 light years away from us. What's more, three of those exist within the "Goldilocks zone" which could be habitable for life.

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The DeepMind team described their test in a blog post this way:

“We let the agents play this game many thousands of times and let them learn how to behave rationally using deep multi-agent reinforcement learning. Rather naturally, when there are enough apples in the environment, the agents learn to peacefully coexist and collect as many apples as they can. However, as the number of apples is reduced, the agents learn that it may be better for them to tag the other agent to give themselves time on their own to collect the scarce apples.”

“This model... shows that some aspects of human-like behaviour emerge as a product of the environment and learning. Less aggressive policies emerge from learning in relatively abundant environments with less possibility for costly action. The greed motivation reflects the temptation to take out a rival and collect all the apples oneself,” said Joel Z. Leibo from the DeepMind team to Wired. 

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What if you could lose weight and reduce your risk of life-threatening disease without any changes in what you eat—other than a five-day special diet once every few months?

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New imaging techniques enable exploration of the brain in much more detail than ever before, opening the door to greater understanding of neurological problems and possibly new treatments, researchers say.

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Magnetically controlled swarms of microscopic robots might one day help fight cancer inside the body, new research suggests.

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Stop worrying about outsourcing. Start planning for automation.

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Machine learning is becoming extremely powerful, but it requires extreme amounts of data.

You can, for instance, train a deep-learning algorithm to recognize a cat with a cat-fancier’s level of expertise, but you’ll need to feed it tens or even hundreds of thousands of images of felines, capturing a huge amount of variation in size, shape, texture, lighting, and orientation. It would be lot more efficient if, a bit like a person, an algorithm could develop an idea about what makes a cat a cat from fewer examples.

A Boston-based startup called Gamalon has developed technology that lets computers do this in some situations, and it is releasing two products Tuesday based on the approach.

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Imagine patterning and visualizing silicon at the atomic level, something which, if done successfully, will revolutionize the quantum and classical computing industry. A team of scientists in Edmonton, Canada has done just that, led by a world-renowned physicist and his up-and-coming protégé.

He has his long-term sights set on making ultra-fast and ultra-low-power silicon-based circuits, potentially consuming ten thousand times less power than what is on the market.

"Imagine instead of your phone battery lasting a day that it could last weeks at a time, because you're only using a couple of electrons per computational pattern," says Huff, who explains that the precision of the work will allow the group and potential industry investors to geometrically pattern atoms to make just about any kind of logic structure imaginable.

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Although we spend a lot of our time online nowadays—streaming music and video, checking email and social media, or obsessively reading the news—few of us know about the mathematical algorithms that manage how our content is delivered. But deciding how to route information fairly and efficiently through a distributed system with no central authority was a priority for the Internet's founders. Now, a Salk Institute discovery shows that an algorithm used for the Internet is also at work in the human brain, an insight that improves our understanding of engineered and neural networks and potentially even learning disabilities.

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As bees slip onto the endangered species lists, researchers in Japan are pollinating lilies with insect-sized drones. The undersides of these artificial pollinators are coated with horse hairs and an ionic gel just sticky enough to pick up pollen from one flower and deposit it onto another. The drones' designers are hopeful that their invention could someday help carry the burden that modern agricultural demand has put on colonies.
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