Running AI models is turning into a memory game

AI companies are facing a major challenge managing memory (the high-speed storage that holds data a computer needs right now) as they scale up their systems, with DRAM chip prices jumping 7x in the past year. Companies are adopting strategies like prompt caching (temporarily storing input data to reuse it cheaply) to reduce costs, but optimizing memory usage involves complex tradeoffs, such as deciding how long to keep data cached and managing what gets removed when new data arrives. The companies that master memory orchestration (coordinating how data moves through different storage systems) will be able to run queries more efficiently and gain a competitive advantage.