Lightning Talk: AIOps vs. MLOps: What's the Difference?
summary
Distinguishes AIOps as a multi-layer platform that automates IT with big data analytics and machine learning to predict performance issues, do root-cause analysis and surface anomalies, from MLOps as a discipline that standardizes processes and is DevOps for ML pipelines managing models as products across continuous lifecycles. Claims include a practical gap — only 13% of ML projects reach production — and the prescription that culture and cross-functional collaboration matter more than specific tools.
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