General partner Eric Vishria from Benchmark and Quilter Founder Sergiy Nesterenko discuss Benchmark's investment philosophy in the AI era, emphasizing the importance of solving enduring problems, Quilter's innovative use of reinforcement learning in circuit board designs, the shift towards fully automated AI solutions, and the balance between research and engineering in the AI space.

Eric Vishria from Benchmark and Sergiy Nesterenko from Quilter discuss AI investments, hardware design, and VC strategies. They highlight the importance of solving enduring problems in AI, avoiding foundation model companies, and utilizing AI in hard tech projects. The conversation delves into simplifying complex AI problems, benefits of AI in physics, challenges in AI development, and the intersection of technology and business innovation.

Sergiy Nesterenko, Founder of Quilter, delves into automating circuit board design using reinforcement learning. Topics include challenges in traditional processes, AI trustworthiness, future possibilities of AI-driven design, labor dynamics, PCB design considerations, and leveraging reinforcement learning for optimal designs.

Sergiy Nesterenko, CEO of Quilter, discusses using reinforcement learning in PCB design, automating complex processes. They explore challenges in PCB design, integrating AI with real-world applications, and the future of electronic design. Team dynamics, research challenges, and applying AI in physics simulations are also covered.

Sergiy Nesterenko, CEO of Quilter, discusses automating circuit board design with AI, challenges of hardware design, importance of curiosity and empathy in engineering, and potential of 3D printing. They explore the link between quantum mechanics and semiconductors, evolution of computer vision algorithms, and philosophical reflections on artificial intelligence and human intelligence.

Sergiy Nesterenko, expert in automated PCB design, discusses challenges like iteration cycles, octilinear traces, and first-principles design. He explores the design space, benchmarks, and the balance between automation and human expertise in PCB design. The podcast delves into utilizing neural networks and reinforcement learning for automating circuit board design while addressing potential risks and seeking community feedback.