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With the pace of gen AI adoption accelerating across all business sectors and functions, required skills are increasingly in demand — but the people out there able to meet needs are in short supply.
Having established its bona fides as a key methodology for cost control and workload optimization of public cloud services, FinOps is expanding into optimizing outcomes for private cloud, SaaS, licensing, AI, and even traditional data centers.
Benchmarks can be used to put large language models to the test. Read on for some tips on how to do it right.
Intuitive user interfaces are no longer enough. CIOs need to shift application design toward deeper process analysis to deliver on-target features for business value. Here are four ideas that can help.
AI ethics seem to consist of a volatile maze of laws, tech and public whims. Build agility to control the uncontrollable, or risk losing everything.
If you want to take advantage of the possibilities offered by automation and AIOps, you first need to get your IT infrastructure in shape. However, modernization involves a great deal of homework.
The EuroStack initiative aims to reduce Europe’s technological dependency through European solutions — but is the budget sufficient?
The numbers are starting to come in, and many companies report that some gen AI investments are starting to pay off — but not all.
The barriers to entry for AI developers just got much lower, and that’s good news for businesses deploying AI.
If you’re searching for a playbook for successful gen AI adoption, look back at what works for citizen developers.
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