Why Vision AI Models Fail
This white paper delves into the reasons behind the failure of vision AI models, highlighting common failure modes such as poor data quality, underrepresented edge cases, and model bias. Real-world case studies from companies like Tesla, Walmart, and TSMC illustrate how these failures can lead to significant business losses. The document emphasizes the importance of data curation, model evaluation, and analysis in preventing these failures before they impact production. Strategies for detecting, analyzing, and preventing model failures, as well as approaches for production monitoring to track data drift and model confidence over time, are also discussed.
IEEE Spectrum•