Summary
Researchers have applied prompt optimization using VizPy to the challenging task of analog circuit placement, achieving 97% of expert quality. This method leverages an optimizer that learns from failure-success pairs to improve an LLM's layout reasoning across iterations, notably requiring zero domain-specific training data. This breakthrough could significantly automate and accelerate a notoriously difficult aspect of chip design.
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