The AI in Business Podcast Building Better PCB Layouts with AI Driven Optimization - with Alain-Sam Cohen of InstaDeep
Jun 6, 2025
Alain-Sam Cohen, Head of Product at InstaDeep, is revolutionizing PCB design using advanced AI techniques like reinforcement learning. He discusses the persistent challenges engineers face in PCB layout and how AI can overcome these bottlenecks. Alain-Sam highlights real-world examples of improved efficiency and ROI. The conversation also delves into the balance of human oversight with automation, the future of AI in electronic design automation, and the ethical considerations that come with this technological transformation.
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PCB Design Complexity
- PCB design is a sequential problem with many constraints and trade-offs.
- Optimization requires balancing conflicting requirements rather than absolute perfection.
Reinforcement Learning Benefits
- Reinforcement learning enables AI to learn PCB design through simulated trial and error at scale.
- This approach adapts and improves by accumulating experience from large data volumes.
Balance AI and Human Work
- Let AI tools handle 80-90% of repetitive PCB design work.
- Engineers should apply expertise only to critical areas and finish with manual refinement.