In-Prompt Information Subject Matter Expert Text-to-Text AI Prompt

An In-Prompt Information Subject Matter Expert Text-to-Text AI Prompt is a in-prompt text-to-text AI prompt that is a subject matter expert text-to-text AI prompt (combines the need for responses based on specific information provided within the prompt with the requirement for expert-level analysis).

• Context:
  • It can range from being a Simple In-Prompt Information Subject Matter Expert Text-to-Text AI Prompt to being a Complex In-Prompt Information-Based Subject Matter Expert Text-to-Text AI Prompt.
  • It can (typically) involve a detailed crafting of prompts that include domain-specific knowledge, jargon, and contextual information.
  • It can (often) leverage techniques such as Context Expansion, Content Summarization With Specific Focus, and Template Filling to enhance the AI's understanding and output relevance.
  • It can benefit from Prompt Reframing, Prompt Combination, and Chain-Of-Thought Prompting to produce nuanced and comprehensive responses.
  • It may include advanced techniques like Iterative Prompting, Interactive Storytelling and Role-Playing, and Implicit Information Injection for dynamic interaction and output generation.
  • It might also utilize Language Translation With Contextual Nuance and Automatic Prompt Engineering (APE) for cross-language applicability and automation of prompt generation processes.
  • ...
• Example(s):
  • “Given the recent market data, analyze the potential economic impact of a new trade policy.” - Requires expert economic analysis based on provided market data.
  • “Considering the details in the provided medical study, what are the implications for future cancer treatment?” - Requires medical expertise to interpret and analyze information from a medical study.
  • Asking a Generative AI model to provide expert-level advice on a medical topic by framing the prompt with specific medical terminology and context.
  • Using a structured prompt to generate a technical analysis report on cybersecurity threats, including industry-specific terms and frameworks.
  • ...
• Counter-Example(s):
  • General Text-to-Text AI Prompt without specific data or expert knowledge requirement.
  • Text-to-Code AI Prompt, Text-to-Image AI Prompt which focus on different AI model capabilities.
  • Generic prompts that lack domain specificity or technical depth.
  • Prompts designed for broad, non-specialized audiences without the inclusion of expert knowledge or terminology.
• See: In-Prompt Information-Based Text-to-Text AI Prompt, Subject Matter Expert Text-to-Text AI Prompt, AI-Generated Text, Data-Driven Communication, Expert System, AI in Legal Analysis, Prompt Engineering, Subject Matter Expertise in AI, Text-to-Text AI Communication.

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References

2024

• (Hostinger, 2024) ⇒ Hostinger. (2024). ["AI Prompt Engineering: What It Is and 15 Techniques for 2024". In: Hostinger.
  • QUOTE: With Artificial Intelligence (AI) tools becoming more common across industries to supplement human effort, prompt engineering has emerged as a pivotal skill.

    Prompt engineers are natural language experts responsible for communicating with large language models (LLMs) to achieve desired results.

    In this article, we’ll explain the essentials of prompt engineering and its key concepts. We’ll also explore multiple techniques for developing prompts in a precise, context-driven manner.

2023

• (McFarland, 2023) ⇒ Alex McFarland. (2024). "What is Prompt Engineering in AI & Why It Matters". In: Unite.AI, .
  • QUOTE: AI prompt engineering is an effective way to get the desired output with an AI tool. Prompts come in various forms, such as statements, blocks of code, and strings of words. This method of utilizing prompts was invented by people with the intention of eliciting responses from AI models. It serves as a starting point for teaching the model to develop outputs that are appropriate to a given task.

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