This post discusses an innovative approach to compressing key-value (KV) caches used in large language models (LLMs) like Llama 2. The focus is on achieving memory efficiency for longer contexts without the need for additional parameters. The technique aims to enhance the performance of LLMs by allowing them to manage longer contexts while minimizing memory overhead. The comments reflect skepticism about the choice of Llama 2 7B as the basis for this research, questioning its relevance in 2023. This reflects a broader sentiment in the community regarding the speed of advancements in the field of LLMs.