The Riemann Hypothesis remains one of the greatest unsolved problems in mathematics, deeply tied to the distribution of prime numbers and the zeros of the Riemann zeta function. In this topic, we investigate how large language models (LLMs) like GPT-4 and beyond can contribute to the mathematical discovery process. We explore:
- How LLMs can be used to understand, generate, and critique mathematical proofs.
- Prompt engineering strategies to extract useful insights on complex mathematical conjectures.
- Case studies of LLMs analyzing patterns in the zeta function.
- The limits and ethical implications of using AI to approach foundational problems in pure mathematics.
- Hybrid approaches that combine symbolic reasoning, numerical analysis, and language-based models.
This topic bridges deep learning, symbolic mathematics, and foundational theoretical inquiry, and aims to inspire researchers to explore uncharted intersections between AI and pure math.