Prompting Insights

What is Prompting?

Prompting, in the context of AI and especially large language models (LLMs), refers to the process of providing input text (the "prompt") to guide the model's behavior and generate a desired output. The design and content of the prompt significantly influence the quality and relevance of the model's response. Effective prompting techniques are crucial for eliciting specific information, creative text formats, translations, code generation, and more from LLMs. This includes using techniques like few-shot learning, chain-of-thought prompting, and prompt engineering.

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What other technologies are related to Prompting?

Prompting Complementary Technologies

fine-tuning

Fine-tuning and prompting are often used together to adapt LLMs for specific tasks. Prompting provides initial guidance, while fine-tuning further optimizes the model's behavior based on a specific dataset and task objectives.

mentioned alongside Prompting in 8% (87) of relevant job posts

RAG

Retrieval-Augmented Generation is a complement to prompting strategies because it provides external context to improve the quality and relevance of the generated responses. Prompting defines how this retrieved information is utilized.

mentioned alongside Prompting in 1% (65) of relevant job posts

LLMs

Large Language Models are the foundation of prompting, as prompting is the mechanism used to interact with and guide the behavior of these models.

mentioned alongside Prompting in 0% (154) of relevant job posts