The conversation dives into the complexities of real-time detection in machine learning systems, emphasizing the limitations of traditional metrics like accuracy. Shreya highlights the difficulties posed by the lack of real-time labels and the impact of feedback loops on model performance. She argues for the importance of focusing on product metrics rather than forcing machine learning metrics to align with business outcomes, especially in the context of LLMs where the AI often becomes the product itself.
