This post introduces online learning techniques to optimize LLM routing for cost efficiency, enabling dynamic model selection based on real-time cost and performance metrics. It details how Ramp accelerated machine learning development to simplify finance by building a system that dynamically routes requests to the most cost-effective and performant ML models. This builds upon the previous iteration by incorporating online learning for dynamic, real-time optimization.
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