100K token Context Window memory in Claude

Context Window: In the context of the language model, the "context window" refers to the specific text or document that is loaded into the model for processing, analysis, and generating responses. It represents the fixed and non-volatile memory of the text, typically up to a maximum token limit (e.g., 100K tokens), that the model can access and refer to during a session or conversation. The context window provides the model with a comprehensive understanding of the given text, enabling it to generate accurate and contextually relevant responses.

ChatGPT, after many corrections:

	Session Memory	Context Window
Definition	Focuses on maintaining contextual information within a single conversation or session.	Represents the specific text or document that is loaded into the language model for processing and analysis.
Purpose	Helps maintain coherence and continuity within a conversation by keeping track of topics, questions, and responses.	Enables the language model to have a comprehensive understanding of the loaded text to generate accurate and contextually relevant responses.
Scope	Limited to a single conversation or session.	Can encompass a broader range of information, including but not limited to the current conversation or session.
Usage	Revisits open points, summarizes covered ground, and maintains context within a specific conversation.	Allows the model to refer to and analyze the loaded text, even if it spans hundreds of pages or contains extensive information.
Persistence	Typically resets or clears when the conversation or session ends.	Persists across conversations and sessions, providing a consistent understanding of the loaded text.
Text Example	Keeps track of the discussion context, questions, and responses within the transcribed podcast.	Represents the entire transcribed text of the podcast loaded into the model as the context window.

about the release: Introducing 100K Context Windows

100K translates into roughly 6 hours of audio - AssemblyAI put out a great demonstration of this where they transcribed a long podcast into 58K words and then used Claude for summarization and Q&A. You can watch the full demo here. With 100K context windows, you can:

•     Digest, summarize, and explain dense documents like financial statements or research papers
•     Analyze strategic risks and opportunities for a company based on its annual reports
•     Assess the pros and cons of a piece of legislation
•     Identify risks, themes, and different forms of argument across legal documents.
•     Read through hundreds of pages of developer documentation and surface answers to technical questions
•     Rapidly prototype by dropping an entire codebase into the context and intelligently build on or modify it