The Sequence Opinion #819: How AI Chips are Made?
From Silicon to Intelligence: What Actually Goes Into Designing an AI Chip
A deep dive into the architecture, physics, and craft of building hardware for neural networks — from RTL, Verilog to tape-out.
Let me tell you something that took me an embarrassingly long time to truly internalize: the reason deep learning works as well as it does in 2026 is only maybe 40% algorithms. The rest is hardware. We got lucky — spectacularly lucky — that the GPU, a chip originally designed to make triangles pretty in Quake III, turned out to be almost exactly the right computational substrate for training neural networks. But “almost exactly right” is doing a lot of heavy lifting in that sentence. The story of AI chips is the story of closing that gap, and it’s one of the most fascinating engineering stories of our time.