Today we’re joined by Pat Woowong, principal engineer in the applied machine intelligence group at The Home Depot.
We discuss a project that Pat recently presented at the Google Cloud Next conference which used machine learning to predict shelf-out scenarios within stores. We dig into the motivation for this system and how the team went about building it, including what type of models ended up working best, how they collected their data, their use of kubernetes to support future growth in the platform, and much more.
For the complete show notes, visit twimlai.com/talk/175.
Causal Conceptions of Fairness and their Consequences with Sharad Goel - #586
Brain-Inspired Hardware and Algorithm Co-Design with Melika Payvand - #585
Equivariant Priors for Compressed Sensing with Arash Behboodi - #584
Managing Data Labeling Ops for Success with Audrey Smith - #583
Engineering an ML-Powered Developer-First Search Engine with Richard Socher - #582
On The Path Towards Robot Vision with Aljosa Osep - #581
More Language, Less Labeling with Kate Saenko - #580
Optical Flow Estimation, Panoptic Segmentation, and Vision Transformers with Fatih Porikli - #579
Data Governance for Data Science with Adam Wood - #578
Feature Platforms for Data-Centric AI with Mike Del Balso - #577
The Fallacy of "Ground Truth" with Shayan Mohanty - #576
Principle-centric AI with Adrien Gaidon - #575
Data Debt in Machine Learning with D. Sculley - #574
AI for Enterprise Decisioning at Scale with Rob Walker - #573
Data Rights, Quantification and Governance for Ethical AI with Margaret Mitchell - #572
Studying Machine Intelligence with Been Kim - #571
Advances in Neural Compression with Auke Wiggers - #570
Mixture-of-Experts and Trends in Large-Scale Language Modeling with Irwan Bello - #569
Daring to DAIR: Distributed AI Research with Timnit Gebru - #568
Hierarchical and Continual RL with Doina Precup - #567
Create your
podcast in
minutes
It is Free
20/20
The Dropout
Ten Percent Happier with Dan Harris
World News Tonight with David Muir
NEJM This Week