Episode 534: Andy Dang on AI / ML Observability
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Episode 534: Andy Dang on AI / ML Observability
Andy Dang, Head of Engineering at WhyLabs discusses observability and data ops for AI/ML applications and how that differs from traditional observability. SE Radio host Akshay Manchale speaks with Andy about running an AI/ML model in production and how observability is an important tool in diagnosing and detecting various failures in the application. They explore concept drift and data drift as indicators in assessing a model’s quality and what corrective actions to take. Andy describes the challenges arising from high dimensionality and data volume, as well as from organizational structures that manage and operate various aspects of the data infrastructure and how observability can detect and solve problems in production. This episode also considers explainability from an observability perspective and how it helps stakeholders — include both builders and consumers of AI/ML applications — understand what they are seeing from AL/ML models.
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