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Evaluating AI Benchmarks in Dynamic Environments
This chapter examines the structure and limitations of AI benchmarks within simulated web contexts, advocating for a focus on generality. It discusses the challenges AI agents face in adapting to evolving tasks and external shifts, stressing the need for effective performance assessments. The chapter also highlights the potential discrepancies in AI task completion rates and the considerations needed for deploying reliable AI systems in real-world applications.