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Amit Paka

Cofounder, Fiddler Ai

Search every verified Amit Paka interview, podcast appearance, and on-the-record quote β€” each transcript cross-checked by AI and human review to confirm speaker identity. Amit Paka, cofounder of Fiddler AI, discussed model performance monitoring and the proposed EU artificial intelligence regulation during a June 2021 appearance on the MLOps Coffee Sessions podcast. Paka stated that before founding Fiddler, while leading the product team on shopping apps at Samsung, he observed challenges that data teams faced in operationalizing models, including difficulty running A/B tests. He said the lack of transparency in model decisioning "played a key role and it came up again and again," and that the Fiddler team aligned on a mission of "helping teams build trust with AI." Paka described the proposed EU regulation as aiming to help teams build "human-centric and trustful AI," classifying applications into categories including banned "unacceptable" uses and "high-risk" applications such as self-driving cars or credit scoring that would face new oversight. He argued that for high-risk applications, the law would require sufficient transparency for users to understand and control how models work, and that monitoring, record-keeping, and fairness validation are what the regulation is pushing toward. Paka also introduced the concept of "Model Performance Management" (MPM), which he described as a centralized framework powered by explainable AI that involves measuring, validating, monitoring, and analyzing model behavior across the lifecycle, with the ability to feed new data representations back into training.

Selected quotes

Recent appearances

  • Model Performance Monitoring and Why You Need it Yesterday // Amit Paka // MLOps Coffee Sessions #42

    Coffee Sessions #42 with Amit Paka of Fiddler AI, Model Performance Monitoring. //Abstract Machine Learning accelerates business growth but is prone to performance degradation due to its high reliance on data. Moreover, MLOps is often fragmented in many organizations, causing frictions to debug models in production. With new rules from the EU that focus on trust and transparency, it’s becoming more important to keep track of model performance. But how? We propose a new framework, a centralized ML Model Performance Management powered by Explainable AI. Learn more about how you can stay complia…

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