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Perhaps one of the most anticipated applications of AI in cybersecurity is in the realm of behavioralanalytics and predictive analysis. By leveraging machinelearning algorithms, AI can analyze user behavior and network traffic patterns, identifying anomalies that might indicate insider threats or other malicious activities.
2) MLOps became the expected norm in machinelearning and data science projects. 3) Concept drift by COVID – as mentioned above, concept drift is being addressed in machinelearning and data science projects by MLOps, but concept drift so much bigger than MLOps. will look like).
From AI and data analytics, to customer and employee experience, here’s a look at strategic areas and initiatives IT leaders expect to spend more time on this year, according to the State of the CIO. 1 priority among its respondents as well. And CIOs said the need for security improvements is the top driver of IT budget increases.
Vendors, by making indistinguishable claims about digitaltransformation and process automation, suggest similar outcomes. Digitaltransformation cannot be achieved through purely tech-enabled, service-led approaches, with the promise to build autonomous enterprises with low code, flexible applications, etc.
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