Three insights you may have missed from theCUBE’s coverage of RAISE Summit
Agentic inference is reshaping the center of gravity in AI infrastructure. What began as a race to scale training has shifted into a phase defined by expanding context windows, memory‑augmented reasoning and the need to keep graphics processing units continuously fed with data.
As enterprises push deeper into agentic systems, storage has moved into the critical path of AI performance. Agentic inference is exposing new bottlenecks, accelerating the adoption of design patterns and pushing organizations to rethink how intelligence is staged, retrieved and delivered to GPUs, according to Greg Matson (pictured), senior vice president and head of marketing and products at Solidigm, a trademark of SK Hynix NAND Product Solutions Corp.
“It started a couple of years ago with training, where the need for high-capacity, high-performance storage very adjacent to the GPUs was all of a sudden center stage,” Matson told theCUBE. “But now, as we go from last year to this year, inference phase into agentic inference, it’s exploding even more. Storage is actually a whole new storage tier that’s being created to extend the memory for the system.”
