Deep learning is having a serious moment right now in the world of AI.
And for good reason. Loosely based on the brain's computing architecture, artificial neural networks have vastly outperformed their predecessors in a variety of tasks that had previously stumped our silicon-minded comrades.
But as these algorithms continuously forge new grounds in machine intelligence, we're coming to an uncomfortable realization: transistor-based computers have hard limits, and those limits are approaching rapidly.
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