LLM Memory
Some thoughts on implementations
Summary
Redlining large language models (LLMs) refers to exceeding their reliable context window, which leads to degraded output quality before the advertised limit is reached.
Each LLM displays different performance boundaries, making some models better suited for certain tasks than others. Businesses using high-end LLMs can expect significantly increased productivity but must budget substantially more for token usage to leverage these models effectively.
