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
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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
