HPE and Kamiwaza rethink AI infrastructure for the inference era
As AI factories evolve into “data centers of the future,” the infrastructure stack must also transform into a mix of CPU and GPU platforms that can deliver a full set of AI computing solutions.
This runs the gamut from application hosting to intelligence generation and from static workflows to agentic orchestration systems. For key enterprise computing vendors, such as Hewlett Packard Enterprise Co., it means that organizations increasingly expect production-ready enterprise AI with the governance, security and scale required to move efficiently from pilot to production.
The challenge confronting many organizations today is to get beyond the noise surrounding the IT stack and use AI infrastructure to improve inference speed, according to Robin Braun (pictured, left), vice president of AI business development, hybrid cloud, at HPE.
“People are trying to find the signal in the noise; they’re trying to use their data to improve their efficiency … to improve their business,” Braun said. “That’s where inference comes in — just trying to use that to get at the underlying understanding of your data is so important. That’s where I see so many customers are now really locking in and focusing on how they are solving some of the more mundane, messy data type issues.”
