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Microsoft is laying the groundwork for a hardware-accelerated Azure cloud with its own custom AI silicon, Arm server processors, virtualization offload, and more.
Many enterprises are ‘rightsizing’ away from the cloud, but no one has documented the journey as well as 37signals. We can all learn from the company’s experience.
Cloud and AI are the most important technologies today, and both have outstripped open source licenses. It’s time for a new open source definition.
Just when you thought you knew all the ways hackers could access your data on a public cloud, a new threat has emerged. Luckily, the fixes are manageable.
Model quantization bridges the gap between the computational limitations of edge devices and the demands for highly accurate models and real-time intelligent applications.
A digital adoption platform overlays all of an organization’s applications, automating tedious tasks, guiding users through complex UIs, and measuring the use of all system features. Here’s how it works.
All the worry over technical debt and the risks of cloud vendor lock-in has spread to AI, only the stakes are now much higher.
InfoWorld recognizes the year’s best products in software development, cloud computing, data analytics, AI, and machine learning.
The mantra for computing is to use other people’s technology, so it's surprising that generative AI doesn’t seem to follow that pattern for many enterprises.
Hardware-backed confidential computing in Microsoft Azure now includes protected environments for VMs, containers, and GPUs, without the need to write specialized code.