The conversation delves into the nuances of prompting in machine learning, likening it to tea leaf reading due to its unpredictable nature. Sara emphasizes the challenge of understanding high dimensional spaces and the potential for general prompts across different architectures. Tim counters with the idea that prompts hold intrinsic value, suggesting they may evolve but will always retain a degree of unpredictability.
