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In this interview from the AI Data Pipeline Forum 2026, Vaughn Stewart, vice president of systems engineering at VAST Data, joins theCUBE's John Furrier to discuss why fragmented, best-in-breed AI pipelines are giving way to unified data platforms built for both training and inference. Stewart explains how VAST's Disaggregated Shared-Everything Architecture (DASE) conflates the roles of high-performance storage and data processing systems, eliminating trade-offs that once forced operators to choose between scale, economics and speed. He points to data freshness, access control and vector embedding synchronization as critical failure points in piecemeal architectures, noting that stale or improperly governed data undermines the quality of inference at scale. The conversation also explores VAST Data's new DataEnclave offering, a confidential computing environment built with NVIDIA, AMD and Intel alongside model providers such as Cohere, CrowdStrike and TwelveLabs, enabling secure execution of frontier models on sensitive, regulated data that previously couldn't leave corporate data centers. Stewart details how remote cryptographic attestation and tamper-proof audit logging protect data and model weights across the entire GPU cluster, closing the gap between regulated industries and public AI tools. He also unpacks how VAST is optimizing for power draw and density to meet the scarcest resource constraints facing neoclouds, while sustaining year-over-year growth above 100%. From battling legacy vendor lock-in to building win-win-win ecosystems with semiconductor makers and model builders alike, Stewart lays out why cohesive, full-stack infrastructure is now the deciding factor in the AI infrastructure race. Find more SiliconANGLE news and analysis https://siliconangle.com/ Follow theCUBE's wall-to-wall event coverage https://siliconangle.com/events/ Learn about the latest theCUBE events https://www.thecube.net/ 00:00 - VAST Data Infrastructure for Training and Inference 02:43 - Unified Storage and Scalable AI Infrastructure 08:57 - Energy-Efficient AI Infrastructure: Memory and Compute 11:16 - Why Fragmented AI Pipelines Fall Short 14:23 - Scaling Architecture for Fresh Data and Secure Inference 17:59 - VAST DataEnclave Enables Confidential AI Computing 22:09 - Building Mutually Beneficial AI Ecosystem Partnerships #theCUBE #AIDataPipelineForum #theCUBEresearch #VASTData #AI #ConfidentialComputing #NVIDIA

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