// MODEL OPTIMIZATION AND PROMPT SYNTAX TERM
Long Context
Refers to AI models that can process and understand very long pieces of text, like entire documents or conversations, as a single input.
TECHNICAL DEFINITION
Long context refers to the capability of large language models (LLMs) to process and maintain coherence over significantly extended input sequences, typically thousands or tens of thousands of tokens, enabling deeper understanding of lengthy documents or conversations.
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
- Extended context window
- Large input capacity
- Long sequence processing
USAGE NOTE
Long context models are valuable for tasks like summarizing entire books or analyzing lengthy legal documents.
DEVELOPERS
Organizations developing technology related to Long Context.
A pioneer in developing large language models with exceptionally long context windows, enabling processing and reasoning over vast amounts of text, prominently featured in their Claude models.
A leading AI research and deployment company known for its GPT series of models, which continually push the boundaries of context window capabilities in large language models.
A prominent AI research lab and developer of advanced AI systems, including the Gemini family of models designed with enhanced capabilities for processing and understanding long contexts.
Provides large language models and RAG solutions tailored for enterprise applications, featuring models like Command-R with substantial context windows for complex business tasks.
Engages in cutting-edge research in large language models and integrates long-context processing capabilities into its Azure AI services, enabling enterprise-scale applications.
The AI research division of Meta, actively involved in developing and open-sourcing large language models and contributing significant research to efficient and effective long-context processing.
Offers a cloud platform for building and running AI models, including many open-source large language models optimized for extended context windows, and actively supports research in this area.