Decoding AI: Past, Present, and Future
Here is a number worth sitting with: a researcher today, working at the frontier of a mature field, might produce one genuinely novel result per year. Maybe two. The rest is reading, dead ends, grant writing, seminar attendance, and the slow grinding work of elimination. This is not a failure of talent. It is the…
HAL 9000 didn’t just process commands. It noticed things. It read stress in Dave Bowman’s voice, detected deception in his words, inferred intent from behavior. That quality — situational awareness fused with emotional inference, running continuously and silently in the background — was what made HAL feel genuinely alive on screen, and genuinely terrifying. For…
A matrix multiplication — the fundamental arithmetic of every neural network — takes a photonic processor roughly the time it takes light to cross a thumbnail. Not microseconds. Not nanoseconds. Picoseconds. That is not a rounding error on conventional silicon; it is a different regime of physics entirely. For the better part of a decade,…
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…
There’s a moment in human problem-solving that’s easy to overlook: the pause before the answer. Not silence, exactly — something is happening in there, some rearrangement of partial ideas that never surfaces as words. For decades, language models had no equivalent. They generated token after token in a single forward pass, their “thinking” invisible even…
Give a frontier reasoning model a hard mathematical olympiad problem and something unusual happens: it argues with itself. It proposes an approach, notices a flaw three steps in, backtracks, tries a different decomposition, and eventually converges on a proof that checks out. The final answer looks clean. The path to it looked almost human. This…
Watch a human catch a thrown object and you’ll notice something almost unremarkable: the hand shapes itself before contact, fingers pre-curving into a configuration that anticipates trajectory, weight, and spin. It takes years of childhood development to wire this up. Robots, until very recently, simply couldn’t do it. Not the catching — the anticipating. The…
Start with a number: roughly 1060. That’s a conservative estimate of the number of drug-like molecules that could theoretically exist. The entire history of pharmaceutical chemistry has explored maybe 108 of them. We have been, by any honest accounting, searching a beach by examining individual grains of sand. That situation is changing fast, and the…
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…