Meta's HawkEye Toolkit Dramatically Simplifies AI Debugging
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HawkEye is a debugging toolkit used internally at Meta for monitoring, observability, and debugging of ML models powering products. It has improved debugging time by orders of magnitude.
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HawkEye implements a decision tree to guide users in identifying root causes of issues with predictions, features, models, training data, etc.
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It performs real-time analysis to isolate problematic model snapshots, features, and data dependencies correlated with prediction degradation.
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HawkEye visualizes model graphs and training data statistics to diagnose model and data issues.
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It has simplified operational workflows, enabling non-experts to triage complex ML production issues with minimal coordination.