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)

Gen AI at the Edge: Qualcomm AI Research at CVPR 2024 with Fatih Porikli - #688

Gen AI at the Edge: Qualcomm AI Research at CVPR 2024 with Fatih Porikli - #688

Today we’re joined by Fatih Porikli, senior director of technology at Qualcomm AI Research. In our conversation, we covered several of the Qualcomm team’s 16 accepted main track and workshop papers at...

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Energy Star Ratings for AI Models with Sasha Luccioni - #687

Energy Star Ratings for AI Models with Sasha Luccioni - #687

Today, we're joined by Sasha Luccioni, AI and Climate lead at Hugging Face, to discuss the environmental impact of AI models. We dig into her recent research into the relative energy consumption of ge...

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Language Understanding and LLMs with Christopher Manning - #686

Language Understanding and LLMs with Christopher Manning - #686

Today, we're joined by Christopher Manning, the Thomas M. Siebel professor in Machine Learning at Stanford University and a recent recipient of the 2024 IEEE John von Neumann medal. In our conversatio...

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Chronos: Learning the Language of Time Series with Abdul Fatir Ansari - #685

Chronos: Learning the Language of Time Series with Abdul Fatir Ansari - #685

Today we're joined by Abdul Fatir Ansari, a machine learning scientist at AWS AI Labs in Berlin, to discuss his paper, "Chronos: Learning the Language of Time Series." Fatir explains the challenges of...

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Powering AI with the World's Largest Computer Chip with Joel Hestness - #684

Powering AI with the World's Largest Computer Chip with Joel Hestness - #684

Today we're joined by Joel Hestness, principal research scientist and lead of the core machine learning team at Cerebras. We discuss Cerebras’ custom silicon for machine learning, Wafer Scale Engine 3...

13 Mai 202455min

AI for Power & Energy with Laurent Boinot - #683

AI for Power & Energy with Laurent Boinot - #683

Today we're joined by Laurent Boinot, power and utilities lead for the Americas at Microsoft, to discuss the intersection of AI and energy infrastructure. We discuss the many challenges faced by curre...

7 Mai 202449min

Controlling Fusion Reactor Instability with Deep Reinforcement Learning with Aza Jalalvand - #682

Controlling Fusion Reactor Instability with Deep Reinforcement Learning with Aza Jalalvand - #682

Today we're joined by Azarakhsh (Aza) Jalalvand, a research scholar at Princeton University, to discuss his work using deep reinforcement learning to control plasma instabilities in nuclear fusion rea...

29 Apr 202442min

GraphRAG: Knowledge Graphs for AI Applications with Kirk Marple - #681

GraphRAG: Knowledge Graphs for AI Applications with Kirk Marple - #681

Today we're joined by Kirk Marple, CEO and founder of Graphlit, to explore the emerging paradigm of "GraphRAG," or Graph Retrieval Augmented Generation. In our conversation, Kirk digs into the GraphRA...

22 Apr 202447min

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