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Optimize for Performance, Adapt to Complexity
Designing optimizers that are agnostic to non-differentiable components enhances adaptability in programming. Current optimizers focus on refining prompts for language model calls to maximize program performance. This approach is extendable, indicating it can handle diverse functions alongside conventional language models. Establishing benchmarks, like the Ling Probe initiative, will facilitate the evaluation of optimizer efficiency on various language model programs. Future developments in tool use will further enrich this exploration, presenting both opportunities and challenges to enhance program optimization.