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

Page: https://stenobird.com/podcast/mlops-community/inside-uber-s-ai-revolution-everything-about-how-they-use-ai-ml
Text version: https://stenobird.com/podcast/mlops-community/inside-uber-s-ai-revolution-everything-about-how-they-use-ai-ml.md
Podcast: [MLOps.community](https://stenobird.com/podcast/mlops-community)
Published: 2025-07-04T16:42:26+00:00
Episode link: https://podcasters.spotify.com/pod/show/mlops/episodes/Inside-Ubers-AI-Revolution---Everything-about-how-they-use-AIML-e353lvh
Audio file: https://anchor.fm/s/174cb1b8/podcast/play/105026993/https%3A%2F%2Fd3ctxlq1ktw2nl.cloudfront.net%2Fstaging%2F2025-6-4%2F403306804-44100-2-1858046985138.mp3
Processing state: processed
JSON: https://stenobird.com/v1/public/podcasts/mlops-community/episodes/inside-uber-s-ai-revolution-everything-about-how-they-use-ai-ml
Duration seconds: 2723

## Resource

Kai Wang joins the MLOps Community podcast LIVE to share how Uber built and scaled its ML platform, Michelangelo. From mission-critical models to tools for both beginners and experts, he walks us through Uber’s AI playbook—and teases plans to open-source parts of it. // Bio Kai Wang is the product lead of the AI platform team at Uber, overseeing Uber's internal end-to-end ML platform called Michelangelo that powers 100% Uber's business-critical ML use cases. // Related Links Uber GenAI: https://www.uber.com/blog/from-predictive-to-generative-ai/ #uber #podcast #ai #machinelearning ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~ Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExplore MLOps Swag/Merch: [ https://shop.mlops.community/ ] Connect with Demetrios on LinkedIn: /dpbrinkm Connect with Kai on LinkedIn: /kai-wang-67457318/ Timestamps: [00:00] Rethinking AI Beyond ChatGPT [04:01] How Devs Pick Their Tools [08:25] Measuring Dev Speed Smartly [10:14] Predictive Models at Uber [13:11] When ML Strategy Shifts [15:56] Smarter Uber Eats with AI [19:29] Summarizing Feedback with ML [23:27] GenAI That Users Notice [27:19] Inference at Scale: Michelangelo [32:26] Building Uber’s AI Studio [33:50] Faster AI Agents, Less Pain [39:21] Evaluating Models at Uber [42:22] Why Uber Open-Sourced Machanjo [44:32] What Fuels Uber’s AI Team

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