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How to Spot and Prevent Model Drift Before it Impacts Your Business

Despite the AI hype, many tech companies still rely heavily on machine learning to power critical applications, from personalized recommendations to fraud detection.  I’ve seen firsthand how undetected drifts can result in significant costs — missed fraud detection, lost revenue, and suboptimal business outcomes, just to name a few. So, it’s crucial to have robust…

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Optimizing Imitation Learning: How X‑IL is Shaping the Future of Robotics

Designing imitation learning (IL) policies involves many choices, such as selecting features, architecture, and policy representation. The field is advancing quickly, introducing many new techniques and increasing complexity, making it difficult to explore all possible designs and understand their impact. IL enables agents to learn through demonstrations rather than reward-based approaches. The increasing number of…

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