GPU-as-a-Service is democratizing access to high‑performance computing. It puts cutting-edge GPUs in the hands of any team—on demand—so you can train AI models, run simulations, render media, and accelerate analytics without owning the hardware.   In brief On-demand GPUs remove CapEx barriers and speed up time-to-value for AI, HPC, and data-intensive workloads. Elastic capacity and right-sizing help align compute to actual demand across training, inference, and simulations. A

Cybersecurity and AI: when LPUs become the brain of proactive defense. This article explains how Language Processing Units (LPUs) enable real-time detection, response and resilience—so security teams can shift from reactive alert fatigue to predictive, automated defense.   At a glance LPUs deliver ultra‑low‑latency AI inference, ideal for inline detection, triage, and autonomous response at scale. Proactive defense hinges on fast, explainable decisions across logs, network tr

L’infrastructure du futur éthique efficiente et prête pour l’intelligence artificielle. In 2025, that means building foundations that are secure, low‑carbon, resilient, and capable of powering real AI outcomes—without compromising ethics or budgets. At Score Group, we bridge energy systems, digital infrastructure and new technologies to help organizations design, deploy and operate this next-generation stack. Through our Noor Energy, Noor ITS and Noor Technology divisions, we

L’architecture hyperconvergée face aux exigences du calcul intensif: can hyperconverged infrastructure really satisfy HPC workloads in 2025? If you’re weighing hyperconverged infrastructure (HCI) for high‑performance computing (HPC), the short answer is: yes, in specific patterns—and no, for the most latency‑sensitive, tightly coupled jobs. This article clarifies where HCI fits, where it struggles, and how hybrid designs can align HPC needs with the operational simplicity of

GPU/TPU/LPU: understand the differences and use cases. This no‑nonsense guide clarifies what each accelerator does best, when to choose one over the others, and how to align your AI stack with performance, latency, and sustainability goals.   In brief GPUs are general‑purpose accelerators with the richest ecosystem—great for training and versatile inference. TPUs specialize in tensor math for deep learning—excellent for large‑scale training and batched inference on Google Clo

IT durable : green IT & efficacité énergétique — your 2025 playbook for cutting digital carbon, slashing energy costs, and...

Hyperconvergence & data center modernization, made practical for 2025. This guide explains what hyperconverged infrastructure (HCI) is,...

Hybrid cloud & digital sovereignty: a 2025 blueprint to keep sensitive data compliant, available, and under your control. Enterprises are...