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Inside Uber’s AI Revolution - Everything about how they use AI/ML

MLOps.community

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Evaluating Machine Learning Efficiency at Uber

This chapter explores the key metrics used to assess machine learning project efficiency at Uber, focusing on the 'time to production' as a primary measure. It discusses the challenges of measuring developer velocity and the complexities inherent in different use cases, as well as the significance of team feedback and proxy metrics. The chapter emphasizes the evolution of machine learning applications within Uber, highlighting the use of predictive ML and generative AI to enhance user experiences across services like ride booking and Uber Eats.

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