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The explosive growth of generative AI drives the multicloud model. But be prepared because it’s going to cost more money.
Overspending on AI infrastructure by cloud providers has some forecasting an AI bust, but there are signs that enterprises are starting to put AI to work.
Project IDX shines with a VS Code look and feel, GitHub integration, workspace sharing, and AI-powered coding assistance.
Kubernetes started as one of many tools for container orchestration. Ten years later it’s the leading platform for cloud-native applications.
It's old news that no one in IT can find enough talent to build and run modern IT solutions. AI won’t save you, so start looking at other options.
GPT-in-a-Box is a full-stack platform for running generative AI workloads that integrates Nvidia NIMs and the Hugging Face LLM library.
Balancing performance, energy efficiency, and cost-effectiveness, CPUs adeptly handle the less-intensive inference tasks that make up the lion’s share of AI workloads.
Microsoft is not simply making a big bet on AI in Windows, but betting that natural language and semantic computing are the future of Windows.
Using edge systems to run elements of generative AI could be game-changing. It requires planning and skill, but this hybrid approach may be the future.