Effective Prompt Engineering
Structuring prompts with clear sections and tags can significantly enhance the quality of responses from language models. By breaking down problems into manageable steps, users can improve the effectiveness of LLMs, although the execution of these steps may still pose challenges. A novel approach called program aided prompting encourages users to request pseudocode, further bridging the gap between planning and execution.In this clip
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Data Skeptic
Graphs for HPC and LLMs
Related Questions
What is the best insight on prompt engineering and engaging large language models (LLMs)?
What is the best insight on prompt engineering and engaging large language models (LLMs) from the episode LLMs in Social Science and the clip Prompt Engineering Advice?
How are prompts used in AI models as discussed in the episode Treating Prompt Engineering More Like Code // Maxime Beauchemain // MLOps Podcast #167 and the clip The Future of LLMs?