Quilter uses a physics-driven AI approach called reinforcement learning to create PCB layouts—similar to how AlphaGo learned to play Go by playing against itself repeatedly. Instead of relying on human-designed boards as examples, Quilter explores numerous layout possibilities on its own, evaluating each with detailed physics assessments we call Physics Rule Checks (PRCs).
Over time, this self-guided approach lets Quilter continuously improve and adapt, optimizing designs based on real-world physics considerations like thermal management, EMI, impedance control, and more. Right now, our focus is on quickly generating designs for rapid real-world testing, and we’ll keep expanding the complexity and depth of physics feedback built directly into Quilter’s automated layout process.