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As synthetic intelligence drives unprecedented demand for knowledge processing, Mountain View startup Voltron Data is providing an answer to considered one of AI’s least mentioned however most important challenges: shifting and reworking large datasets shortly sufficient to maintain up.
Voltron Knowledge, which introduced a strategic partnership with Accenture right this moment, has developed a GPU-accelerated analytics engine that might assist enterprises overcome the information preparation bottleneck hampering AI initiatives. The corporate’s core product, Theseus, allows organizations to course of petabyte-scale knowledge utilizing graphics processing models (GPUs) as an alternative of conventional pc processors (CPUs).
“Everybody’s targeted on the flashy new stuff which you could contact and really feel, however it’s that dataset basis beneath that’s going to be key,” mentioned Michael Abbott, who leads Accenture’s banking and capital markets observe, in an unique interview with VentureBeat. “To make AI work, you’ve acquired to maneuver knowledge round at a velocity and tempo you simply by no means needed to earlier than.”
Constructing for the AI tsunami: Why conventional knowledge processing gained’t lower it
The partnership comes as firms dashing to undertake generative AI are discovering their current data infrastructure isn’t outfitted to deal with the quantity and velocity of knowledge required. This problem is predicted to accentuate as AI brokers grow to be extra prevalent in enterprise operations.
“Brokers will most likely write extra SQL queries than people did in a really quick time horizon,” mentioned Rodrigo Aramburu, Voltron Knowledge’s Discipline CTO and cofounder. “If CIOs and CTOs are already saying they spend means an excessive amount of on knowledge analytics and cloud infrastructure, and the demand is about to step perform greater, then we’d like a step perform down in the price of working these queries.”
Not like conventional database distributors which have retrofitted GPU help onto current methods, Voltron Knowledge constructed its engine from the bottom up for GPU acceleration. “What most firms have finished once they’ve tried to do GPU acceleration is that they’ll shoehorn GPUs onto an current system,” Aramburu advised VentureBeat. “By constructing from the bottom up…we’re capable of get 10x, 20x, 100x relying on the efficiency profile of a selected workload.”
From 1,400 servers to 14: Early adopters see dramatic outcomes
The corporate positions Theseus as complementary to established platforms like Snowflake and Databricks, leveraging the Apache Arrow framework for environment friendly knowledge motion. “It’s actually an accelerator to all these databases, slightly than competitors,” Abbott mentioned. “It’s nonetheless utilizing the identical SQL that was written to get the identical reply, however get there quite a bit sooner and faster in a parallel style.”
Early adoption has targeted on data-intensive industries like monetary providers, the place use circumstances embody fraud detection, threat modeling and regulatory compliance. One massive retailer decreased its server depend from 1,400 CPU machines to only 14 GPU servers after implementing Theseus, in accordance with Aramburu.
Since launching at Nvidia’s GTC convention final March, Voltron Knowledge has secured about 14 enterprise clients, together with two massive authorities companies. The corporate plans to launch a “take a look at drive” model that may permit potential clients to experiment with GPU-accelerated queries on terabyte-scale datasets.
Turning the GPU scarcity into a chance
The present GPU shortage sparked by AI demand has been each difficult and helpful for Voltron Knowledge. Whereas new deployments face {hardware} constraints, many enterprises possess underutilized GPU infrastructure initially bought for AI workloads, property that could possibly be repurposed for knowledge processing throughout idle durations.
“We truly noticed it as a boon in that there’s simply so many GPUs out out there that beforehand weren’t there,” Aramburu famous, including that Theseus can run successfully on older GPU generations which may in any other case be deprecated.
The know-how could possibly be significantly useful for banks coping with what Abbott calls “trapped knowledge” — info locked in codecs like PDFs and paperwork that could possibly be useful for AI coaching however is tough to entry and course of at scale. “You’ve seen a few of the knowledge that Voltron would present you is probably 90% simpler and environment friendly to maneuver knowledge utilizing this know-how than commonplace CPUs,” Abbott mentioned. “That’s the ability.”
As enterprises grapple with the information calls for of AI, options that may speed up knowledge processing and cut back infrastructure prices are prone to grow to be more and more vital. The partnership with Accenture may assist Voltron Knowledge attain extra organizations going through these challenges, whereas giving Accenture’s shoppers entry to know-how that might considerably enhance their AI initiatives’ efficiency and effectivity.
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