#photonic computing

data centers are becoming a serious problem. the energy cost of running AI is growing fast and most people assume the solution is better power sources, cleaner energy, more efficient cooling. those things matter. but i've been thinking about something more fundamental.

the problem might be that we're running AI on the wrong kind of computer entirely.

here's what i mean. AI at its core is pattern matching. that's it. transformers, neural networks, all of it finding patterns in data. but the hardware we run it on was designed in the 1940s for something completely different: sequential processing, a central clock ticking billions of times per second, memory and processing separated so data has to constantly travel between them. every tick costs energy whether there's work to do or not.

we're running a brain-like process on a machine that was never designed to think that way.

so i started thinking about the brain. your brain runs more computation than any data center on about 20 watts. how? a few reasons but the big one is that neurons only fire when something actually changes. most of the time, most of the brain is quiet. silence is the default.

what if we built hardware around that principle instead?

i've been developing a conceptual architecture for what i'm calling physics-native pattern computing. instead of a clock driving everything, the system is event-driven it only activates when a pattern arrives that matches something it's tuned to recognize. light interference handles the signal propagation (light naturally does parallel comparison at physics speed, no computation required). resonant physical structures handle the recognition tuned to specific pattern signatures, silent unless matched. a threshold gate made of phase-change materials sits between recognition and activation, so near-matches don't accidentally trigger a response. and when nothing matches, the whole system sits in its ground state using almost no energy at all.

the architecture has been reviewed independently by grok, chatgpt, and gemini. all three confirmed the logic holds and mapped onto active research in photonic computing and neuromorphic hardware.

i'm not an engineer. i derived this from observation and systems thinking, same way i build everything. and i think that's actually part of why it hangs together, i wasn't constrained by how things are usually done.