At Google Cloud Next, we are announcing innovations across every layer of our storage stacks — performance, intelligence, and management — to ensure your data is as fast and as useful as the AI models, apps and agents you are building. Why it matters: Storage is no longer just a place to keep data. When training AI models, storage is the engine that feeds data-hungry accelerators. During AI inference, it’s the access layer that makes it responsive, acting as the source for the context that AI agents need to be effective. When storage performance falls short, accelerators sit idle, agents respond slowly, and data remains invisible to AI models.  But storage performance is only half the battle; you also need storage that’s smart . With the help of Google’s AI models integrated directly into the storage layer, you’re no longer just storing bits, but data that has full context about its content.…