Context window overflow: Breaking the barrier

This article discusses context window overflow (CWO) in large language models (LLMs) and its implications for generative AI systems.

Specifically, the article covers:

• Key concepts in generative AI such as LLMs, tokenization, context windows, retrieval augmented generation (RAG), and LLM hallucinations
• How CWO occurs when the total number of input and output tokens exceeds the model's predefined context window size, causing loss of context
• Examples demonstrating token complexity leading to overflow, and prompt injection using long prompts to retrieve sensitive information
• Recommendations to mitigate CWO, including token limits, input validation, streaming LLMs, and monitoring
• The importance of understanding CWO limitations to harness the potential of AI models effectively