Metrics Driven Development (Practical AI #284)
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Evaluating LLM Applications vs. Models
This chapter explores the critical differences between evaluating large language models and their applications, highlighting the necessity for application-specific assessments. It emphasizes adapting traditional testing methods to suit the continuous and non-deterministic nature of AI applications, while also advocating for metrics-driven development to enhance debugging and performance evaluation.
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