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Uber's Michelangelo: Strategic AI Overhaul and Impact // #239
Jun 7, 2024
Demetrios Brinkmann, AI strategist at Uber, discusses the evolution of Michelangelo platform at Uber, from basic ML predictions to deep learning and generative AI. Covering challenges faced in early versions and improvements in Michelangelo 2.0 and 3.0 like Pytorch support, enhanced model training, and integration of technologies like Nvidia’s Triton and Kubernetes. The platform now includes features like a Genai gateway, compliance guardrails, and model performance monitoring to streamline AI operations.
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Quick takeaways
- Uber's Michelangelo platform evolved from basic ML to deep learning and generative AI, enhancing AI operations at Uber.
- Michelangelo 2.0 and 3.0 introduced support for PyTorch, model training enhancements, and integration of technologies like Nvidia's Triton and Kubernetes.
Deep dives
Evolution of Michelangelo Platform at Uber
Uber's Michelangelo platform evolved through three distinct phases, starting from foundational predictive ML and tabular data, progressing to deep learning, and eventually venturing into generative AI. The platform supported various use cases like Riot ETA, fraud detection, search, and driver matching, enhancing the real-time Uber product experience.
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