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At GTC, Solidigm's Scott Shadley and Dell Technologies' Rob Hunsaker discuss how Dell is tackling the challenges of AI data infrastructure with cutting-edge solutions: https://hubs.ly/Q03cZBrH0 With 90% of enterprises still gearing up for AI adoption, having the right data platform is essential. In the video below, Rob shares how Dell’s Project Lightning and AI Data Lakehouse are designed to meet extreme performance needs, making AI storage more scalable, flexible, and efficient than ever. #AI #GTC #Dell #DataInfrastructure #AIStorage #MachineLearning

AI is transforming cloud infrastructure, and OVHcloud is stepping up to the opportunity with a fully integrated approach. At CloudFest 2025, they shared how their custom-built servers, global network, and optimized storage are driving efficiency and performance at scale. With AI demands rising, controlling the full value chain—from hardware to data centers—is a game-changer. See how OVHcloud is unlocking new possibilities for AI and cloud in the video below. #CloudFest2025 #AI #CloudComputing #Infrastructure #OVHcloud #Solidigm

At this year’s MWC, TechArena’s Allyson Klein joined AMD's Salil Raje onstage for a Fireside Chat discussing the company's vision for the next era of AI, where intelligence moves from the cloud to the edge. From federated learning to AI-driven exoskeletons, Salil shared how AMD’s adaptive and embedded computing team is enabling real-time decision-making in sectors like healthcare, automotive, and industrial automation. With innovations like the Versal AI Gen 2, AMD is pushing the boundaries of AI hardware, optimizing performance at the edge while reducing power and cost constraints. As industries shift toward AI-enabled, always-on intelligence, the question isn’t if AI at the edge will take off—but how fast. Discover highlights from our Fireside Chat in our recap blog here: https://hubs.ly/Q03cshtR0 #AMD #AI #EdgeComputing #FederatedLearning

At NVIDIA GTC 2025, we sat down with VAST Data's John Mao and NVIDIA's Tony Paikeday for a Fireside Chat on the just-announced integration between the VAST Insight Engine and NVIDIA’s DGX compute platform. From fine-tuning enterprise AI to scaling inference workloads, John and Tony unpack how VAST and NVIDIA’s deep collaboration will help organizations simplify deployment, optimize performance, and accelerate AI adoption. With the rise of real-time AI factories, getting infrastructure right is critical—learn how this major GTC announcement will impact the AI transformation: https://hubs.ly/Q03cpSjB0 #AI #GTC2025 #EnterpriseAI #NVIDIA #VASTData

Cloud repatriation is redefining IT strategy, expanding workloads from the cloud to the edge to optimize costs, performance, and AI capabilities. With a recent Barclay's survey indicating that 83% of IT leaders considering repatriation, it's clear that enterprises are expanding their view of where their compute belongs. The reason? AI is accelerating, and real-time workloads demand ultra-low latency and localized processing. From predictive maintenance in factories to real-time analytics in retail, edge computing is unlocking new levels of efficiency—but edge expansions require the right infrastructure. In their latest report, OnLogic explores why IT leaders are expanding edge deployments, and how organizations can navigate the shift: https://hubs.ly/Q03clQbl0 #EdgeComputing #CloudRepatriation #AI #ITInfrastructure #HybridCloud

AI is revolutionizing industries—but without fast, scalable storage, its potential is limited. In a recent Data Insights podcast, sponsored by Solidigm, Mark Klarzynski of PEAK:AIO shared how high-performance AI storage is transforming industries. From healthcare to wildlife conservation, PEAK:AIO is solving critical data challenges by eliminating bottlenecks and accelerating real-time insights. AI is only as powerful as the storage supporting it. PEAK:AIO is ensuring AI can think faster, process more, and drive real-world impact. Check out our recap blog to hear more key insights from our conversation: https://hubs.ly/Q03ck2z90 #AI #GPUs #DataStorage #AIStorage #PEAKAIO

As we step into the room where it happens at NVIDIA GTC (cue Hamilton ??), all eyes are on NVIDIA and the next wave of AI innovation. While the spotlight will be on mega-factories and LLM expansion, we’ll explore the deeper currents shaping AI adoption: - DeepSeek’s impact: Will NVIDIA embrace more efficient Chinese models? Can optimization fuel broader market growth? - Enterprise AI uptick: Beyond theory—where are real-world AI applications scaling? 2025 is forecasted as the hockey stick growth year for GenAI in business. - Agentic computing: The buzzword of the moment—how are vendors setting guardrails to make AI agents enterprise-ready? We’re live from San Jose to bring you real-time insights. Stay tuned for updates, interviews, and key takeaways from the AI event of the year: https://hubs.ly/Q03cbQ3Z0 #GTC2025 #AI #LLMs #EnterpriseAI #AgenticComputing

Generative AI is transforming the enterprise landscape, shifting AI workloads from training-heavy to inference-heavy at an unprecedented scale. In our latest Tech Arena Data Insights webinar, WEKA's CTO, Shimon Ben David, and Solidigm's AI Data Center Lead, Ace Stryker, explored how businesses can future-proof their AI infrastructure. As inferencing demands grow, high-performance storage, seamless GPU integration, and multi-cloud strategies are becoming essential for efficiency and scalability. Want to stay ahead in the AI revolution? Learn how the right infrastructure choices can unlock new levels of AI performance: https://hubs.ly/Q03c94vd0 #GenerativeAI #AI #Inferencing #CloudComputing #TechInnovation

In safety-critical systems, every component matters—but not every component needs the highest safety rating. Through smart engineering techniques like redundancy, decomposition, and fault detection, systems can achieve stringent safety certifications even when individual parts don’t meet the highest standards. In Robert Bielby’s latest blog, he explains how system-level design compensates for component limitations, ensuring reliability without unnecessary overhead. These approaches are widely used in automotive, aerospace, and industrial applications, where cost, complexity, and practicality prevent every component from being built to the highest level of safety. So how does this work in practice? And what does it mean for the future of functional safety in complex automotive systems? Robert’s post explores the key mechanisms that make it possible: https://hubs.ly/Q03c5sRR0 #FunctionalSafety #FuSa #Automotive #SafetyStandards

AI is everywhere—but are we talking about generative AI (Gen AI) or machine learning (ML)? The hype around Gen AI is undeniable, but ML has been the backbone of AI innovation for years. Do you know the difference? In her latest blog, Gina Rosenthal breaks down the fundamental differences between machine learning and generative AI, how they work together, and why understanding both is crucial for real-world AI adoption: https://hubs.ly/Q03bVLjt0 #AI #MachineLearning #GenerativeAI