AI chip design
Applying machine learning to automate the stages of semiconductor design — from logic specification to layout — that once required large engineering teams and months of iteration.
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Designing a chip means translating a logical specification into a physical layout of billions of transistors — a chain of steps (synthesis, place-and-route, timing closure, verification) that each require specialist tools and human judgment. ML enters as a drop-in optimizer at individual stages, or as an agent that drives the whole flow. The hard part is that each step has tight physical constraints: a placement decision made early propagates timing errors downstream that are expensive to unwind. Progress here compresses the design cycle, which matters because the gap between "we need this chip" and "we have this chip" currently runs 18–24 months.
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Design Conductor
Handed a 219-word spec, an AI agent designed a working RISC-V processor and carried it alone all the way to a tape-out-ready layout in twelve hours — no engineer in the loop.
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