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Microsoft’s new generative AI-powered, multimodal, content analysis service is a next-generation version of its existing Cognitive Services platform.
Heroku also announced that its Next Generation platform, which supports building and deploying Kubernetes and AI applications, is available in a pilot.
Cloud AI providers brag that their generative AI and large language models are open, and enterprises are falling for it.
Red Hat Ansible Automation Platform Service on AWS is a Red Hat managed service for automating the deployment and management of hybrid cloud infrastructure.
Other updates to the mostly free low code tool for building generative AI applications includes an app search and the ability to bake in simultaneous document processing inside applications.
From our editors: We look at how IT leaders are reworking their cloud implementations for better fit to their needs, as well as how they can control cloud costs and ensure cloud security.
Following the crowd can be an expensive mistake—just ask the developers trying to make Kubernetes or AI fit.
Growing cloud complexity, undisciplined planning, and a shrinking talent pool lead to more failures than successes. Here’s how to avoid becoming another cautionary tale.
Microsoft uses Ignite 2024 to set out its vision for agentic AI in business.
Finops uses cloud units to connect cloud costs with business value. But applying a simple and generic metric to complex and unique business uses leaves me with a lot of questions.
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