ChatGPT and other chatbots are impressive in their ability to provide answers, but they can also produce unrealistic or nonsensical responses. These machine learning systems are fundamentally black boxes, and no one knows exactly how they arrive at their answers. Despite this mystery, computer scientist Yejin Choi discusses the capabilities and limitations of chatbots and large language models (LLMs) in a conversation with host Steven Strogatz. They ponder whether these systems truly understand the world and the questions they answer. Choi shares that large language models can mimic human intelligence to a striking extent, but they lack common sense and can make humorous mistakes.

They also explore the challenges of training these models and the interdisciplinary nature of studying AI. Choi emphasizes the importance of transparency in data and techniques, and discusses the potential dangers of AI, such as misinformation and the overreliance on AI-generated content. They conclude by considering the need for AI literacy and greater involvement of governments and communities in shaping AI policies. Overall, the conversation delves into the exciting advancements and potential risks associated with chatbots and large language models.