Photonic AI Accelerators vs. GPUs – The Battle for AI’s Future in Efficiency, Cost, and Scale
1. Performance per Watt: Photon vs. Electron Efficiency One of the biggest promises of photonic AI accelerators is superior energy efficiency. By using light to perform computations (especially matrix multiplications at the heart of AI models), photonic chips can potentially execute more operations per joule than electronic GPUs: Bottom Line: On raw efficiency, photonic accelerators can theoretically leave GPUs in the dust, performing AI computations with 10× to 1000× less energy. Early evidence (both academic and startup) backs significant gains – e.g. >10× energy reduction for optical matrix math earlybird.com. However, achieving these gains outside the lab will require overcoming
