Decoding AI: Past, Present, and Future
A single forward pass through a large language model consumes roughly the same energy as charging your phone. Multiply that by billions of queries a day, and the arithmetic gets uncomfortable fast. Now imagine routing that computation through light instead of electrons — cutting the energy per operation by an order of magnitude, running matrix…
Light moves through glass without resistance, carries no heat, and can transmit billions of bits per second down a fiber thinner than a human hair. So why are we still doing the most computationally intensive work in human history using electrons squeezed through nanometer-scale silicon transistors, generating enormous heat, hitting physical walls that Moore’s Law…
A photon travels through silicon at the speed of light and consumes almost no energy doing it. That sounds obvious — it’s a photon, after all — but the implications for AI inference are staggering. Every matrix multiplication your GPU executes burns energy moving electrons through resistive metal. A photonic processor does the same multiplication…
A photonic chip performing a matrix multiplication doesn’t heat up the way a GPU does. The photons carrying the signal travel through waveguides etched into silicon, interfere with each other, and produce a result — at the speed of light, consuming a fraction of the energy. That’s not a metaphor. That’s physics, and a growing…