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Generative AI is causing excitement but not success for most enterprises. This needs to change quickly, but it will take some work that enterprises may not be willing to do.
Workloads in the cloud and workloads on premises are both reasonable choices. Enterprises are about evenly split between the two.
Cloud computing has become the ideal way to deliver enterprise applications—and the preferred solution for companies extending their infrastructure or launching new innovations.
Unsustainable demands for AI are on the horizon. People will soon have to stop fake-caring about cloud sustainability and give a damn for real.
By using Google’s search results to ground generative AI applications, developers can provide users with more accurate, relevant, and trustworthy information, the company said.
Microsoft is building Azure’s secure virtual infrastructure in public, a step toward expanding trusted execution.
Moving forward, we need to fully understand the security challenges inherent in a sophisticated cloud environment—for effective protection of digital assets. It’s time for a comprehensive solution that can seamlessly protect against on-pr
IT management’s call for strategic alignment and cost efficiency is leading to a new era of choices that will drive cloud innovation and collaboration.
New capabilities for building safe models include watermarking, prompt refining, and prompt debugging and work with any large language models.
The difference in pricing suggests cost savings for enterprises, at least for usage of open models.