Researchers demonstrate a memory layer that extends AI language models to handle 50-million-token contexts by storing and retrieving key-value states from encrypted disk storage, achieving 2.8-4.3x faster loading and 8.8-12.3x lower GPU energy use compared to recomputation. Testing on Gemma models shows accurate retrieval of facts from millions of tokens earlier with no hallucinations.