How Autonomous AI Is Transforming Chip and System Design

The race to build AI factories is on. But each new generation of chips powering them is more complex than the last. Every chip travels the same path. Design. Verification. Implementation. Sign-off. The systems they power must meet relentless demands. Performance. Power. Area. Thermal. Hundreds of engineers. Months of work. One goal. First pass silicon. The answer? Autonomous AI agents across the entire EDA and systems engineering stack. At design, Cadence's autonomous AI engineer compresses RTL development from weeks to hours and drives the flow itself. In verification and implementation, Synopsys' broad set of agents autonomously handle RTL to GDS with human supervision. And Synopsys' PrimeSim SPICE accelerates simulation up to 18 times faster on NVIDIA GPUs. At sign-off, Siemens FUSE EDA AI agent performs autonomous physical verification. Next, Cadence Aura Stack AI unifies 3D IC packaging and PCB design from exploration through physical implementation and sign-off. While NVIDIA CUDSS accelerates thermal closure for stacked systems. Beyond the chip, agents use NVIDIA Physics NEMO to predict fluid, thermal, and structural behavior. While Synopsys extends from EDA into system design. Silicon to systems. Accelerated by NVIDIA CUISS. Fewer iterations give engineers more time to invent what comes next. This is how next-generation chips get built with NVIDIA technology. Designed, verified, and delivered at the speed AI and the world demand.