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While AI designers are creating powerful machines that can beat humans at many complex cognitive endeavors, they’re still envious of the human brain’s facility with certain seemingly simple tasks: such as recognizing a face after seeing it only once or when it’s partially obscured. The U.S. intelligence agency IARPA is particularly interested in developing AI deep learning programs with visual recognition skills, so last year it launched a US $100 million program called Microns
Under Microns, three teams of researchers are looking for answers on the micro scale and in rodent brains. Each team is studying 1 cubic millimeter of brain tissue from a rodent’s visual cortex, using precision instruments to map the 50,000 neurons and 500 million neural connections within that chunk. The researchers hope to discover patterns of neural activation that can be translated to architectures for AI programs known as deep neural networks.
One team, led by Harvard assistant professor David Cox, is examining its brain cubes using a process that starts with rats playing video games and ends with 2-petabyte digital representations of those cubes.
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neuroscience
AI
neural networks
Microns
IARPA
machine learning
brain
artificial intelligence
deep learning