… The platform is structured around five components: DataAI Command Graph for unified context and relationships DataAI Security for threat visibility and protection alignment DataAI Governance for policy enforcement DataAI Compliance and Privacy for regulatory alignment DataAI Resilience for backup a… …
Dell and Samsung Push AI Infrastructure Into Semiconductor Manufacturing by Harold Fritts on May 18, 2026 AI ◇ Enterprise At Dell Technologies World, Dell announced an expanded partnership with Samsung Electronics to support AI-driven semiconductor manufacturing, with Dell AI infrastructure deploye… …
Scality Introduces ADI Platform for AI-Driven, Sovereign Data Infrastructure by Harold Fritts on May 13, 2026 AI ◇ Enterprise Scality has announced Scality Autonomous Data Infrastructure ADI , a platform aimed at enterprises facing increasing pressure to support diverse AI workloads, strengthen cyb… …
… He said that many organizations are obsessed with the “penthouse” of AI productivity while building on a foundation of “legacy sand.” He feels that t he industry is shifting toward “Identity 2.0,” in which the definition of a user has expanded beyond humans to include autonomous AI agents . …
… The feature brings AI-driven ransomware detection closer to the storage layer itself, where Dell says it inspects data at the byte level and has been trained on thousands of ransomware variants. …
… Additionally, the Red Hat Lightspeed Agent for Google Cloud extends AI-assisted development and operational capabilities to improve productivity for engineering teams managing hybrid environments. …
… Cost concerns remain a primary driver, with 62% of IT leaders citing generative AI infrastructure costs as a major issue. Additionally, 36% report new requirements around data protection, privacy, and risk management driven by AI adoption. …
… The goal is to enhance the integration of AI capabilities into production-oriented computing environments, with an emphasis on practical, operational improvements. Additionally, the lab emphasizes the development of small, efficient language model architectures and new AI computing paradigms. …
… Separately, the next experiment queued behind this one shifts from inference to training: a sub-1B-parameter model trained from scratch on a dual-Spark cluster, configured to mirror the distributed pre-training conditions of much larger systems. …
… The performance profile fits that role, pairing high sequential read bandwidth with much lower write throughput, making the R6060 better suited to read-heavy datasets and capacity-driven storage tiers than to small-block transactional workloads. …