Why a Data Plane Architecture is Critical for Optimizing Next-Generation Workloads

For next generation workloads like AI and ML to power the next evolutionary leap in business transformation or research innovation, they need to be able to do more. AI can support enterprise scale requirements - if the data is there. But without a modern data infrastructure that can rapidly process massive volumes of data, it can't deliver on its full promise and potential.

Recent research has found that AI GPU accelerators can spend up to 70% of their time idle, waiting for data. They require a new kind of data infrastructure that is purpose-built to fuel massive quantities of data at low latencies. Speed is critically important to the AI-fueled enterprise - efficiently feeding the right data to the system is the difference between a project requiring months versus mere days.

In this workshop discussion, WEKA CTO Shimon Ben-David will explain why WEKA opted to architect a modern data plane to support next-generation workloads and discuss how the WEKA Data Platform is helping organizations to achieve first to market results with their AI and ML deployments.