Causal Models in Practice at Lyft with Sean Taylor - #486

Causal Models in Practice at Lyft with Sean Taylor - #486

Today we’re joined by Sean Taylor, Staff Data Scientist at Lyft Rideshare Labs. We cover a lot of ground with Sean, starting with his recent decision to step away from his previous role as the lab director to take a more hands-on role, and what inspired that change. We also discuss his research at Rideshare Labs, where they take a more “moonshot” approach to solving the typical problems like forecasting and planning, marketplace experimentation, and decision making, and how his statistical approach manifests itself in his work. Finally, we spend quite a bit of time exploring the role of causality in the work at rideshare labs, including how systems like the aforementioned forecasting system are designed around causal models, if driving model development is more effective using business metrics, challenges associated with hierarchical modeling, and much much more. The complete show notes for this episode can be found at twimlai.com/go/486.

Episoder(778)

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Deploying Edge and Embedded AI Systems with Heather Gorr - #655

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Mental Models for Advanced ChatGPT Prompting with Riley Goodside - #652

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Multilingual LLMs and the Values Divide in AI with Sara Hooker - #651

Multilingual LLMs and the Values Divide in AI with Sara Hooker - #651

Today we’re joined by Sara Hooker, director at Cohere and head of Cohere For AI, Cohere’s research lab. In our conversation with Sara, we explore some of the challenges with multilingual models like p...

16 Okt 20231h 18min

Scaling Multi-Modal Generative AI with Luke Zettlemoyer - #650

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Pushing Back on AI Hype with Alex Hanna - #649

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