ML and AI systems will make mistakes
summary
Message: AI systems—even top models with great data—will make mistakes, so organizations must quantify error, set tolerance and guardrails, and design human engagement and remediation paths. Uses the concrete example of 98% accuracy framed as million ±200,000 versus billion ±200,000,000 to show why context matters. Describes building a platform for end-to-end model deployment and monitoring, plus embedding computer vision and natural language processing, and integrating open‑source tools to operate models at scale.
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