// MODEL OPTIMIZATION AND PROMPT SYNTAX TERM
Prompt
The input text or instruction given to an AI model to guide its response or generation.
TECHNICAL DEFINITION
A prompt is a sequence of tokens, natural language instructions, or examples provided to a generative AI model, particularly Large Language Models (LLMs), to elicit a desired output, guiding the model's generation process and contextual understanding.
BACKGROUND
Prompt engineering is the process of structuring natural language inputs to produce specified outputs from a generative artificial intelligence (GenAI) model. Context engineering is the related area of software engineering that focuses on the management of non-prompt contexts supplied to the GenAI model, such as metadata, API tools, and tokens.
READ MORE ON WIKIPEDIASYNONYMS & ALIASES
- Input
- Query
- Instruction
- Command
- Context
USAGE NOTE
Crafting effective prompts is fundamental to interacting with and controlling AI models.
DEVELOPERS
Organizations developing technology related to Prompt.
Develops advanced AI models like GPT-4 and provides APIs where prompt engineering is crucial for effective interaction and desired output generation.
Creator of the Claude family of LLMs, Anthropic focuses on safe and helpful AI, where thoughtful prompt design and 'constitutional AI' principles guide model behavior.
Provides a platform and tools for building, training, and deploying machine learning models, with extensive resources and libraries (like Transformers) that support prompt engineering for various tasks.
Develops foundational AI models (e.g., Gemini) and offers cloud-based AI services where prompt engineering is a critical skill for users to leverage their language models effectively.
Offers a suite of AI services and tools through Azure AI, closely collaborating with OpenAI, where prompt engineering is fundamental to integrating and utilizing large language models in applications.
An open-source framework designed to simplify the development of applications powered by large language models, providing tools for prompt management, chaining, and optimization.
Provides a data framework for LLM applications, helping developers connect LLMs with external data sources and optimize prompts for information retrieval and synthesis.
Offers MLOps tools for tracking, visualizing, and optimizing machine learning experiments, including features specifically designed for managing and evaluating prompt variations in LLM development.
A platform focused on enabling developers to build LLM-powered applications faster, offering tools for prompt engineering, testing, deployment, and monitoring.