Presentation: Adaptive Recommenders in the Real World: Inference, Evals, and System Design

Mallika Rao explains that the true complexity of adaptive recommendation systems lies outside model architecture. She discusses how real-time feedback loops, retrieval freshness, multi-stage orchestration, and end-to-end latency budgeting enable systems to continuously learn and evolve in production under real-world operational constraints like latency, cost, and observability. By Mallika Rao

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