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Paul N

Computers Learn How to Paint Whatever You Tell Them To - 3 views

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    Most self-respecting artists wouldn't agree to paint a portrait of a toilet in the middle of a field. Fortunately, advancements in artificial intelligence have given computers the ability to imagine just about any scenario, no matter how bizarre, and illustrate it. Take a look at this image.
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    Those are some creepy faces among them.. This is also just completely random isn't it?
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    Well, biased to the data it was trained on. Computing a net is pretty deterministic. But not everything is perfectly correlated yet. Still nice progress.
hannalakk

AI software helped NASA dream up this spider-like interplanetary lander - The Verge - 2 views

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    We should apply this also for space habitats
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    Yeah, put everything in a computer and let it think about it.
domineo

Can you rewire your brain as a shortcut to health? | Metro Newspaper UK - 1 views

shared by domineo on 09 Jan 18 - No Cached
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    An overview of all the neurotech companies messing with the brain. When reading this I really wonder why we need ethical approval for everything in human research.
Luís F. Simões

Why Is It So Hard to Predict the Future? - The Atlantic - 1 views

  • The Peculiar Blindness of Experts Credentialed authorities are comically bad at predicting the future. But reliable forecasting is possible.
  • The result: The experts were, by and large, horrific forecasters. Their areas of specialty, years of experience, and (for some) access to classified information made no difference. They were bad at short-term forecasting and bad at long-term forecasting. They were bad at forecasting in every domain. When experts declared that future events were impossible or nearly impossible, 15 percent of them occurred nonetheless. When they declared events to be a sure thing, more than one-quarter of them failed to transpire. As the Danish proverb warns, “It is difficult to make predictions, especially about the future.”
  • Tetlock and Mellers found that not only were the best forecasters foxy as individuals, but they tended to have qualities that made them particularly effective collaborators. They were “curious about, well, really everything,” as one of the top forecasters told me. They crossed disciplines, and viewed their teammates as sources for learning, rather than peers to be convinced. When those foxes were later grouped into much smaller teams—12 members each—they became even more accurate. They outperformed—by a lot—a group of experienced intelligence analysts with access to classified data.
  • ...1 more annotation...
  • This article is adapted from David Epstein’s book Range: Why Generalists Triumph in a Specialized World.
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