Complexity Class

Complexity class research investigates the inherent difficulty of computational problems, aiming to categorize them based on resource requirements (time, space). Current work focuses on applying complexity theory principles to analyze and improve the performance of large language models (LLMs) and other AI systems, including exploring the impact of model architecture (e.g., "Networks of Networks") and reasoning strategies (e.g., chain of thought) on computational complexity. These studies are crucial for understanding the limitations and potential of advanced AI, informing the design of more efficient and reliable algorithms, and ultimately shaping the development of future AI technologies.