Arcfra has introduced a new platform called Neutree, aimed at helping large companies manage AI models more effectively. It’s designed to make deploying and operating AI models simpler, more reliable, and scalable across different environments. This move aims to bridge the gap between developing AI models and running them smoothly in real-world business settings. Streamlining
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All posts tagged in GPU Computing
Gcore, a global provider of cloud, AI, and security solutions, has integrated NVIDIA Dynamo into its AI inference offerings. This new feature makes deploying powerful AI models easier and more efficient across different environments. Customers can now activate Dynamo with just one click, simplifying what used to be complex setup processes. What is NVIDIA Dynamo
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AI development is pushing the limits of hardware and data pipelines. To help solve the ongoing problem of GPU idle time, SCAILIUM has teamed up with TD SYNNEX. This partnership aims to make AI workloads run smoother and more efficiently across the globe. Addressing the GPU Bottleneck Many companies investing heavily in GPU infrastructure face
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Neoclouds are cloud platforms built specifically for artificial intelligence tasks. They are designed to handle the intense computational needs of AI, which is experiencing rapid growth. These clouds emerged a few years ago and now have several providers leading the way, such as CoreWeave, Crusoe, Llambda, Nebius, and Vultr. Unlike traditional cloud giants, neoclouds focus
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Whenever a big tech leader shares a vision of the future, people listen with mixed feelings. Some are excited by the idea, while others feel skeptical. Recently, Jeff Bezos suggested that someday, owning a personal computer might become a thing of the past. Instead, he said, we’ll rent processing power from large data centers. He
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Global IT spending is set to keep growing at a rapid pace, reaching over $6 trillion by 2026. According to Gartner, this represents a 10.8% increase from current levels. The biggest driver of this boom is investments in AI infrastructure, which is fueling a surge in hardware and software spending across industries. AI Infrastructure Leads
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Intel is ramping up its efforts in the GPU space, focusing on data center workloads. The company aims to challenge Nvidia’s dominance as AI-driven demand reshapes the infrastructure landscape. With new leadership and strategic shifts, Intel is seeking to carve out a stronger presence in the rapidly evolving market. New Approach to GPU Development Intel’s
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Google has announced a major upgrade to its LiteRT framework, a modern on-device inference engine that evolved from TensorFlow Lite. The new version introduces sophisticated hardware acceleration capabilities, making it faster and more versatile for a wide range of devices. This move aims to improve performance for apps that rely on AI models running locally
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Two leading tech providers have teamed up to make deploying AI workloads faster and easier. PacketFabric, a top Network-as-a-Service (NaaS) provider, and Massed Compute, which offers high-performance managed GPU infrastructure, announced a new, integrated platform. This platform combines GPU-as-a-Service (GPUaaS) with on-demand networking, creating a ready-to-use solution for enterprises working with AI. Streamlining AI Deployment
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In 2025, the worldwide sales of semiconductors reached a total of $793 billion, marking a 21 percent increase from the previous year. This surge reflects the growing demand for advanced chips, especially those used in artificial intelligence and graphics processing. The rise is also driven by the expansion of data centers across the globe, fueling
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