DeepMind’s Demis Hassabis once pointed to the human brain as a paramount inspiration for building AI with human-like intelligence. He’s not the only one. The meteoric success of deep learning showcases how insights from neuroscience—memory, learning, decision-making, vision—can be distilled into algorithms that bestow silicon minds with a shadow of our cognitive prowess.

But what about the other way around?

This month, the prestigious journal Nature published an entire series highlighting the symbiotic growth between neuroscience and AI. It’s been a long time coming. At their core, both disciplines are solving the same central problem—intelligence—but coming from different angles, and at different levels of abstraction. In AI, scientists look to crack the mysteries of efficient, effective learning mathematically using the language of machines. In neuroscience, we dissect the ins and outs of the three-pound fatty goop between our ears, trying to understand intelligence by looking at the…
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