DataHour: LLMs and Foundational Models in Ads Personalization

Join us for a talk on the journey of scaling ads ranking at Pinterest using innovative machine learning algorithms and innovation in ML platform.

This presentation will showcase the transition from traditional logistic regressions to deep learning-based transformer models, LLM inspired sequential transformer based models, multi-task learning, transfer learning.

Throughout the process, we encountered various challenges and gained valuable lessons. Discover the hurdles we overcame and the insights we gained in this talk, as we share the transformation of ads ranking utilizing multiple innovations from the NLP domain at Pinterest and the lessons learned along the way.

Aayush Mudgal is a Senior Machine Learning Engineer at Pinterest, currently leading the efforts around Privacy Aware Conversion Modeling. He has a successful track record of starting and executing 0 to 1 projects, including conversion optimization, video ads ranking, landing page optimization, and evolving the ads ranking from GBDT to DNN stack. His expertise is in large-scale recommendation systems, personalization, and ads marketplaces. Before entering the industry, Aayush conducted research on intelligent tutoring systems, developing data-driven feedback to aid students in learning computer programming. He holds a Master’s in Computer Science from Columbia University and a Bachelor of Technology in Computer Science from Indian Institute of Technology Kanpur.