Optical Tech Could Update a Robot’s AI on the Fly
Cornell Tech researchers have developed an optical receiver that can directly alter its own memory using photocurrents generated by a beamed array of light, bypassing the need for power-hungry analog conversion. This technology could reduce energy costs for AI systems in data centers, self-driving cars, and robots by enabling direct optical updates of AI model parameters.
Why it matters: This optical approach could help lower the energy and cost bottlenecks of moving AI model data between memory and processors, enabling more efficient edge AI and robotics.
Full story at: IEEE Spectrum / AI ↗