Matthew BermanThis podcast introduces a new prompting strategy called "chain of draft" for AI models, which aims to improve upon the traditional "chain of thought" method [00:00]. Chain of draft encourages LLMs to generate concise, dense information outputs at each step, reducing token usage and latency while maintaining or exceeding the accuracy of chain of thought [11:41]. Implementing chain of draft is simple, requiring only an update to the prompt [08:06].
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