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AWS bets on S3 Vectors as AI agents reshape the demands of storage
Agents powered by artificial intelligence are evolving into systems that depend on richer context and scalable data access, driving demand for technologies such as S3 Vectors, a native vector search capability.
It may still be early in the agent era, but this is the first year that real, productive work has started to happen, according to Andy Warfield (pictured), vice president and distinguished engineer at Amazon Web Services Inc. This shift is bringing people back into hands-on development, fitting naturally into busy workflows and allowing deeper focus on finer details of development work.
“I think that what the storage teams are really seeing is [that] on the generative AI side, we’ve got models that can write code, we’ve got models that can write docs,” Warfield said. “At the end of the day, the big bridge that is on us to solve is the bridge between all of that kind of capability and the data that people have.”
Warfield spoke with John Furrier at AWS re:Invent, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed the industry’s shift toward powerful AI agents and the rapid evolution of storage needed to support emerging AI workloads.
S3 Vectors now generally available
On Tuesday, AWS announced that Amazon S3 Vectors is now generally available with increased scale and performance. By allowing customers to store and query vector embeddings directly in Amazon S3, the service can improve the relevance, latency and cost-efficiency of AI and retrieval-augmented applications. The launch is a major milestone that has generated significant enthusiasm across the organization, according to Warfield.
“With so many mature customers building on top of S3, and so many emerging customers just starting with objects and then building out tables for structured data and vectors for search … [Amazon S3 Vectors] is letting them build apps that are soup-to-nuts S3-based, which is super cool to see,” Warfield said.
The S3 preview quickly became the most popular one to date, according to Warfield. Use cases remain varied, especially in data-intensive fields like the life sciences.
“We’re seeing people use S3 Vectors to do drug development — like radiology applications,” he noted. “It’s actually wild to see the kinds of things that people are using vectors for.”
Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of AWS re:Invent:
Photo: SiliconANGLE
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