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Why AI that works in the lab often fails in production — and what actually fixes it

Why AI that works in the lab often fails in production — and what actually fixes itVentureBeat

The article explores the gap between successful AI prototypes and reliable production systems, citing common pitfalls like data drift and lack of monitoring. Capital One's AI Foundations organization shares practical fixes including iterative deployment and cross-functional collaboration.

3 days ago
Why AI that works in the lab often fails in production — and what actually fixes it — AIBriefs