AI-accelerated scientific simulation

This post introduces the application of AI, specifically large language models and neural networks, to accelerate complex scientific simulations, such as fluid dynamics (Navier-Stokes equations). It highlights how AI can provide near real-time solutions, drastically reducing computation time compared to traditional numerical methods. This advancement opens doors for more interactive and rapid scientific discovery and engineering design. The specific contribution of this post is the demonstration of Claude AI's ability to solve a notoriously difficult mathematical problem (Riemann Hypothesis related) by failing 650 times and then ultimately surpassing human records, showcasing advanced problem-solving capabilities in AI.