Need smarter insights in your inbox? Join our weekly newsletters to get solely what issues to enterprise AI, knowledge, and safety leaders. Subscribe Now
As AI functions more and more permeate enterprise operations, from enhancing affected person care via superior medical imaging to powering advanced fraud detection fashions and even aiding wildlife conservation, a vital bottleneck typically emerges: knowledge storage.
Throughout VentureBeat’s Remodel 2025Greg Matson, head of merchandise and advertising and marketing, Solidigm and Roger Cummings, CEO of PEAK:AIO spoke with Michael Stewart, managing companion at M12 about how improvements in storage expertise allows enterprise AI use circumstances in healthcare.
The MONAI framework is a breakthrough in medical imaging, constructing it sooner, extra safely, and extra securely. Advances in storage expertise is what allows researchers to construct on high of this framework, iterate and innovate rapidly. PEAK:AIO partnered with Solidgm to combine power-efficient, performant, and high-capacity storage which enabled MONAI to retailer greater than two million full-body CT scans on a single node inside their IT setting.
“As enterprise AI infrastructure evolves quickly, storage {hardware} more and more must be tailor-made to particular use circumstances, relying on the place they’re within the AI knowledge pipeline,” Matson stated. “The kind of use case we talked about with MONAI, an edge-use case, in addition to the feeding of a coaching cluster, are properly served by very high-capacity solid-state storage options, however the precise inference and mannequin coaching want one thing completely different. That’s a really high-performance, very excessive I/O-per-second requirement from the SSD. For us, RAG is bifurcating the forms of merchandise that we make and the forms of integrations we now have to make with the software program.”
Bettering AI inference on the edge
For peak efficiency on the edge, it’s vital to scale storage right down to a single node, in an effort to deliver inference nearer to the info. And what’s secret’s eradicating reminiscence bottlenecks. That may be carried out by making reminiscence part of the AI infrastructure, in an effort to scale it together with knowledge and metadata. The proximity of knowledge to compute dramatically will increase the time to perception.
“You see all the large deployments, the massive inexperienced discipline knowledge facilities for AI, utilizing very particular {hardware} designs to have the ability to deliver the info as shut as doable to the GPUs,” Matson stated. “They’ve been constructing out their knowledge facilities with very high-capacity solid-state storage, to deliver petabyte-level storage, very accessible at very excessive speeds, to the GPUs. Now, that very same expertise is occurring in a microcosm on the edge and within the enterprise.”
It’s turning into vital to purchasers of AI programs to make sure you’re getting essentially the most efficiency out of your system by operating it on all stable state. That lets you deliver big quantities of knowledge, and allows unbelievable processing energy in a small system on the edge.
The way forward for AI {hardware}
“It’s crucial that we offer options which can be open, scalable, and at reminiscence velocity, utilizing among the newest and best expertise on the market to do this,” Cummings stated. “That’s our aim as an organization, to offer that openness, that velocity, and the dimensions that organizations want. I feel you’re going to see the economies match that as properly.”
For the general coaching and inference knowledge pipeline, and inside inference itself, {hardware} wants will maintain growing, whether or not it’s a really high-speed SSD or a really high-capacity answer that’s energy environment friendly.
“I might say it’s going to maneuver even additional towards very high-capacity, whether or not it’s a one-petabyte SSD out a few years from now that runs at very low energy and that may mainly exchange 4 instances as many arduous drives, or a really high-performance product that’s nearly close to reminiscence speeds,” Matson stated. “You’ll see that the massive GPU distributors are taking a look at learn how to outline the subsequent storage structure, in order that it might probably assist increase, very intently, the HBM within the system. What was a general-purpose SSD in cloud computing is now bifurcating into capability and efficiency. We’ll maintain doing that additional out in each instructions over the subsequent 5 or 10 years.”
Day by day insights on enterprise use circumstances with VB Day by day
If you wish to impress your boss, VB Day by day has you lined. We provide the inside scoop on what firms are doing with generative AI, from regulatory shifts to sensible deployments, so you’ll be able to share insights for max ROI.
Thanks for subscribing. Try extra VB newsletters right here.
An error occured.
