Ion-based technology may enable energy-efficient simulations of the brain’s learning process, for neural network AI systems.
Teams around the world are building ever more sophisticated artificial intelligence systems of a type called neural networks, designed in some ways to mimic the wiring of the brain, for carrying out tasks such as computer vision and natural language processing.
Using state-of-the-art semiconductor circuits to simulate neural networks requires large amounts of memory and high power consumption. Now, an MIT team has made strides toward an alternative system, which uses physical, analog devices that can much more efficiently mimic brain processes.
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