Advancements in the use of machine learning for IT management are leading to growing adoption of Artificial Intelligence for IT Operations (AIOps). This is not about “anything you can do, AI can do better” – it’s about augmenting operators, not replacing them, using operational intelligence, predictive analytics and automation. A reactive approach that uses siloed data, static rule-based thresholds and human brute force can no longer keep up with the complexity and operational data generated by modern hybrid IT systems that often span mainframe to multi-cloud infrastructures. AIOps uses advanced algorithms to automatically normalize, correlate and analyze this vast amount of data—removing the noise and making it easier to solve hard problems. Discover how you can begin your journey to self-driven intelligent ops and let the machine to do the mundane and tedious, so you can focus on the strategic and fun.
We will explore the Responsible Artificial Intelligence (AI) concept while emphasizing the need for AI...
Find out moreBenchmarking AI models from an ethical angle involves ensuring that the evaluation processes promote fairness,...
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