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Flash performance key to AI and next-gen research

As imaging becomes ever-more important to healthcare, says one expert, AI-powered computing devices are increasingly used to rapidly analyze big data streams, as well as to help organizations mine more value from existing data sets.

Jeff Rowe | May 15, 2018 12:00 am

“Hard drives were great in the ‘90s and in the ‘00s, but now they’ve plateaued in terms of bit density and performance.”

So said Esteban Rubens, global enterprise imaging principal for Pure Storage, in a recent interview at Clinical-Innovation.  Perhaps more importantly, he continued, as the healthcare sector makes ever more inroads into the use of Artificial Intelligence (AI), flash is going to take on greater importance because the requirements of AI-driven healthcare IT are totally different than “traditional” applications.

“In a healthcare AI world in which we’re having to store so much data to train models like image and genomics data,” he explained, “you have to be smart about how you consume your storage.

Progressive health systems want the flexibility to be able to deploy infrastructure today knowing that it will still be useful with the new world of AI.”

Simplicity matters, as well, Rubens said, because “IT management doesn’t want to dedicate full-time employees to tuning storage like they’ve done in the past.”  Storage devices need to be optimizing themselves, thus enabling IT teams to “take care of the important things, such as making sure that critical applications are running and clinicians can get the data they need at the time they need it.”

Echoing Rubens, tech writer Garry Kranz recently pointed out that vendors are starting to integrate AI-based analytics engines directly into the storage layer, providing insight on sizing, potential bottlenecks and looming performance issues.

As he explained, “AI combines parallel processing and intelligent algorithms for analyzing data in context. Serverless computing, containerized application microservices and proliferating internet of things devices have all contributed to AI's growing popularity.”

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