Big Brain Burnout: What’s Wrong with AI Computing?

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If our brains processed information the same way today’s machine learning products consume computing power, you could fry an egg on your head. If you think about the brain like a circuit board that “lights up” when we need to process a thought, you’d see that only the neurons local to that specific thought would activate — not the entire brain. In machine learning computing, the entire “brain” is lighting up, which is incredibly inefficient — not to mention terrible for the environment. There’s got to be a better way. Instead of processing a petabyte of compute in a cell phone’s worth of memory (which is happening with today’s machine learning algorithms), we need to flip the script and process a petabyte’s worth of memory in a cell phone’s worth of compute power.

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photo of Nir Shavit
Nir Shavit

Neural Magic

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