Playing Pictionary With Computers Can Assist AI Get Common Sense – ZMR News Blog

Playing Pictionary With Computers Can Assist AI Get Common Sense

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Educating computers how the globe fits together is a difficult process. No matter how much info you give to an algorithm, there are particular kinds of knowledge that cannot simply be written down. Answers to queries such as, “Can I have spaghetti suing a straw?” and “Who must I go for drinks with this evening: a rhino, my friends, or the Pope?” (The answer to the former being “Sure, but just with loads of patience.”)

But AI scientists claim they have software that may assist: Pictionary. Now, researchers from the AI2 (Allen Institute for Artificial Intelligence) issued an online Pictionary-akin game dubbed as Iconary, which they claim can assist sharpen common sense of AI. In Iconary, users must show complex scenes such as “playing on a beach with a tennis ball” or “a crowd rejoicing a win,” while a computer program dubbed AllenAI attempts to guess what they have illustrated. Most prominently: the AI has never seen these statements earlier.

On a related note, researchers earlier generated an artificial 3D printed neural network. It is a machine modeled on how the human brain operates. This machine can identify objects and analyze huge volumes of information at the speed of light. Various devices in daily life employ computerized cameras to verify objects, such as Internet search engines that can rapidly match images to other analogous pictures, claimed scientists at the UCLA (University of California, Los Angeles) in the U.S.

On the other hand, those systems depend on a piece of device to image the object, first by viewing it with an optical sensor or camera, then processing what it views into information, and lastly employing computing programs to understand what it is. The new machine, dubbed as a diffractive deep neural network, employs the light reflecting from the object itself to verify that object in as less time as it will take for a device to simply look at the object.

2 Comments
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