• Prompt engineering in guiding large language models (LLMs)

  • By: Anand V
  • Podcast

Prompt engineering in guiding large language models (LLMs)

By: Anand V
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  • Summary

  • 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
    Anand V
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Episodes
  • Prompt engineering in guiding large language models (LLMs)

    Prompt engineering in guiding large language models (LLMs)
    Oct 26 2024

    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 engineering, including few-shot learning prompts, interactive prompting, and explainable prompt design.

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    17 mins

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