VMware Cloud Foundation vs. Red Hat OpenShift AI: Which Platform is Right for Your AI Workloads?

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InfrastructureTechnology

As AI workloads become increasingly central to business innovation, organizations are turning to modern infrastructure platforms that can scale AI training and inference reliably, securely, and efficiently. Two leading options in this space—VMware Cloud Foundation and Red Hat OpenShift AI—offer enterprise-grade solutions, but with very different philosophies and strengths. In this blog, we’ll explore the […]

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How Easy Is It to Deploy AI Tools? NVIDIA vs Intel Compared

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InfrastructureTechnology

One of the most frequent questions I’m asked by customers embarking on AI projects—whether it’s training deep learning models, running inference workloads at the edge, or scaling machine learning in a hybrid environment—is: “How easy is it to deploy the tools?” The answer often surprises them. While NVIDIA has been the dominant player in AI […]

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Are We Heading into Another Energy Crisis — This Time for AI?

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InfrastructureSocietyTechnology

In recent years, the crypto “energy crisis” sparked global alarm. Bitcoin mining alone consumed roughly 0.4% of global electricity, and crypto‑mining + data centers already made up about 2% of world demand in 2022 [1]. But now, AI workloads—particularly generative and large‑language‑model (LLM) operations—are poised to make an even bigger dent in our energy systems […]

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The Most Popular LLMs, VLLMs, and SLMs in Enterprise AI Today

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FutureGeneralHealthcareHuman ResourcesInformationalInfrastructureRecruitmentSecuritySocietyTechnology

As enterprises rapidly adopt AI to improve efficiency, customer experience, and innovation, the choice of model architecture has become a critical factor. Whether it’s deploying a massive Large Language Model (LLM), an efficient Very Large Language Model (VLLM), or a compute-friendly Small Language Model (SLM), organisations are increasingly strategic about balancing performance, cost, and accuracy. […]

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