Light-based processing replaces electrons to execute matrix multiplications at higher speeds with lower power. Photonic chips bypass the thermal limits of traditional silicon. This shift targets the massive energy demands of large-scale model training. Practitioners should monitor these developments as a potential alternative to GPU clusters for high-throughput inference tasks.