Breaking through AI’s memory wall with token warehousing

Source: VentureBeat

Memory Bottleneck in Agentic AI

As agentic AI moves from experiments to real production workloads, a quiet but serious infrastructure problem is coming into focus: memory. Not compute. Not models. Memory.

Under the hood, today’s GPUs simply don’t have enough space to hold the Key-Value (KV) caches that modern, long‑running AI agents require. This limitation creates a bottleneck that hampers scalability and performance, prompting researchers and engineers to explore new strategies for managing and extending memory capacity.