Laura Ruis

Laura Ruis, a PhD student at University College London and researcher at Cohere, discusses her groundbreaking work on reasoning capabilities of large language models. She delves into whether these models rely on fact retrieval or procedural knowledge. The conversation highlights the influence of pre-training data on AI behavior and examines the complexities in defining intelligence. Ruis also explores the philosophical implications of AI agency and creativity, raising questions about how AI models mimic human reasoning and the potential risks they pose.

In this insightful discussion, Laura Ruis, a researcher focused on pragmatic inferences in conversational AI, delves into the limitations of large language models. She reveals how these models struggle with context and implicature, causing misunderstandings in communication. Ruis also examines zero-shot learning capabilities, showcasing disparities in performance across different models. Additionally, she highlights the importance of human feedback in refining these AI systems, aiming for a future where they can more effectively interpret and engage in nuanced conversations.