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Explore the intersection of meaning and intelligence in language models through this keynote presentation delivered by Christopher Manning at KDD 2025. Delve into cutting-edge research on how computers can intelligently process, understand, and generate human languages, presented by Stanford University's Thomas M. Siebel Professor in Machine Learning and former Director of the Stanford Artificial Intelligence Laboratory. Examine the evolution from traditional natural language processing approaches to modern neural network and deep learning methodologies that have shaped today's Large Language Models and Generative AI systems. Gain insights from the most-cited researcher in Natural Language Processing, whose pioneering work has fundamentally transformed how machines understand human language. Learn about the theoretical foundations and practical implications of meaning representation in computational systems, drawing from decades of research that has earned recognition including the IEEE John von Neumann Medal and multiple best paper awards at premier AI conferences. Understand how semantic understanding and intelligence emerge in language models, with perspectives from both academic research and industry applications through the lens of someone who has bridged theoretical advances with practical implementations in the field of artificial intelligence.
