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

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Manage episode 492587117 series 3241972
Content provided by Demetrios. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Demetrios or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

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

  continue reading

449 episodes

Artwork
iconShare
 
Manage episode 492587117 series 3241972
Content provided by Demetrios. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Demetrios or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

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

  continue reading

449 episodes

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