Prompt engineering in guiding large language models (LLMs) podcast artwork
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Prompt engineering in guiding large language models (LLMs)

by Anand V

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Latest episodes

  • Prompt engineering in guiding large language models (LLMs)

    October 26, 2024 · 17 min

    explains the role of prompt engineering in guiding large language models (LLMs) to solve problems and perform tasks. The document focuses on three prompting techniques: Chain of Thought (CoT), Tree of Thought (ToT), and Self-Reflection…

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About the show

Explains the role of prompt engineering in guiding large language models (LLMs) to solve problems and perform tasks. The document focuses on three prompting techniques: Chain of Thought (CoT), Tree of Thought (ToT), and Self-Reflection, describing how each technique allows LLMs to reason through problems, consider multiple solutions, and analyze their own reasoning process. It then explores the use of prompt engineering in various applications such as multi-modal models, dynamic prompting, and autonomous decision-making. The document concludes with a discussion on the future of prompt engineer