How should we go about understanding LLMs? Do these language models truly understand what they are saying? Or is it possible that what appears to be intelligence in LLMs may be a mirror that merely reflects the intelligence of the human observer?

In this episode, Terry Sejnowski explores the history and future of AI and its profound implications for understanding the human mind. He explains AI's evolution from early logic-based systems to cutting-edge advancements like deep learning and large language models, including ChatGPT, emphasizing the need for clear operational definitions and a strong mathematical foundation to advance AI research. Sejnowski also highlights the parallels between scientific discovery and engineering, discussing practical applications of AI in areas such as language translation and weather prediction.

Terry Sejnowski is the Francis Crick Chair at The Salk Institute for Biological Studies and a Distinguished Professor at the University of California, San Diego. He has published over 500 scientific papers and 12 books, including ChatGPT and The Future of AI: The Deep Language Revolution.