Is AI Hitting the Storage Wall? and why We Should Care

One of the driving factors of good AI models is data volume (and quality). From the inference perspective, we are more and more using very complex and large models (or several simpler still large specialized models, e.g. for multi-agent and multi-model systems) that are supposed to fit into memory to run efficiently. Model size and use is growing faster than memory size available, forcing the system to rely on milli-second-latency storage systems. Are we about to hit the storage-wall soon ?