Scaling AI: A Data Challenge, Not Just a Model Problem

A promotional announcement from The Register highlights a crucial issue in the implementation of artificial intelligence: AI projects fail at scale not so much because of ineffective models or insufficient GPU performance, but because of the inability of data to keep pace.

The publication invites GTC (GPU Technology Conference) attendees to an exclusive dinner to delve into this topic, suggesting that the real challenge in bringing AI from the lab to production lies in managing and organizing the data needed to power these systems.

For those evaluating on-premise deployments, there are significant trade-offs between data control and infrastructural complexity. AI-RADAR offers analytical frameworks on /llm-onpremise to evaluate these aspects.