Google's new TurboQuant algorithm speeds up AI memory 8x, cutting costs by 50% or more

As Large Language Models (LLMs) expand their context windows to process massive documents and intricate conversations, they encounter a brutal hardware reality known as the "Key-Value (KV) cache bottleneck."Every word a model processes must be stored as a high-dimensional vector in high-speed memory. For long-form tasks, this "digital cheat sheet" swells rapidly, devouring the graphics processing unit (GPU) video ra…