This podcast episode delves into the advancements and challenges of machine learning, from pre-trained language models and retrieval-augmented models to the adaptation of large language models. It explores the concept of modularity and the constant evolution of AI techniques, including prompt tuning, Simfluence, and model surgery. Key topics discussed include the incorporation of human-like features, such as fear and memory consolidation, into AI models, as well as the evolving nature of valuable skills as AI advances.