This chapter explores the blurring distinction between AI security and performance in the AI era compared to traditional software. It discusses the challenges of benchmarking, the limitations of generic benchmarks, and introduces an open-source product called Arthur Bench for testing language models. The importance of considering qualitative metrics, evaluating AI models, and measuring their performance is emphasized.

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