This week, Teradata Corp. unveiled new capabilities for VantageCloud Lake and ClearScape Analytics designed to speed the return on investment from generative AI use cases. The new Teradata AI offerings will enable customers to add their own large language models and take advantage of small or mid-size open AI solutions.
Meeta Vouk, vice president at Teradata, talks with theCUBE about Teradata’s AI offerings.
“If you’re a data scientist and you want to experience all of the capabilities that ClearScape Analytics offers, you can quickly spin up a node, you can experiment or … get some results out of AI, and then you can shut it down,” said Meeta Vouk (pictured), vice president of product management, AI and analytics, at Teradata. “We are saying, ‘Bring AI to the data rather than move the data to AI.'”
Vouk spoke with theCUBE Research’s Rob Strechay and co-host Savannah Peterson at Teradata Possible during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed a new partnership with Nvidia Corp. and growing use cases for AI. (* Disclosure below.)
Teradata AI offerings support hybrid AI
Tuesday’s announcement was accompanied by the news that Teradata will collaborate with Nvidia in an integration with the chipmaker’s AI full-stack accelerated computing platform. The collaboration will include Nvidia NIM, inference microservices that accelerate the deployment of foundation models in the cloud or data center.
“We are saying we will meet our customers where they are, whether they’re on-prem or in the cloud,” Vouk said. “We believe in hybrid AI, and if we need graphics processing units to solve for something, we will use GPUs. If you need central processing units, we’ll use CPUs. There are certain use cases which will always need GPUs, fine-tuning of models, [and creation of] vector embedding, so we really wanted to support our customers for those needs. That’s the idea behind it.”
Vouk discussed a number of use cases that have featured Teradata AI offerings in recent months as customers continue to implement AI solutions from prototype to production. She described the example of a large retailer with 160,000 products that sent a marketing email to four million customers. AI was able to personalize the campaign and achieve a 28% uplift in sales, according to Vouk.
“The use cases are getting so complex, and to solve for them in really meaningful ways, you’re going to need multiple models and multiple capabilities,” Vouk said. “It’s not really AI for AI’s sake or gen AI for gen AI’s sake. It’s really fit-for-purpose AI.”
Here’s the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage of Teradata Possible:
(* Disclosure: TheCUBE is a paid media partner for Teradata Possible. Neither Teradata Corp., the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)