Episode 28: Beyond Supervised Learning: The Rise of In-Context Learning with LLMs

This podcast episode explores the evolution and integration of language understanding models (LLMs) in chatbots and conversational AI systems. The conversation discusses the traditional approach to building chatbots using text classification and if statements, as well as the challenges and advantages of incorporating LLMs for improved context and reliability. The importance of injecting prompts and instructions, as well as the impact of chatGPT on the chatbot industry, is also highlighted. The podcast emphasizes the need to shift focus to data quality and feedback loops in machine learning systems and mentions the success of the Calm system in large enterprises. Overall, the episode provides insights into the past, present, and future of conversational AI.