Invited Talks

Keynote Talk

Ed Chi

Distinguished Scientist, Research Lead at Google DeepMind

Title: The Convergence of Models and its Implication for Multi-Sided Markets 

Abstract: Our field has shifted from traditional machine learning techniques that are mostly based on pattern recognition to sequence-to-sequence models. While this has mostly played out in natural language and image processing, these techniques are starting to make their inroads in building recommendation and ads ranking systems. This has enabled an entirely different way of thinking about how to create these systems. In this talk, I will address the emerging trend of models converging into a single multitask multimodal model, and its implications for multi-sided markets. 

Invited Talk

Ding Tong

Senior Machine Learning Researcher at Netflix

Title: Beyond the Stream: Towards A Healthy Recommendation Ecosystem at Netflix

Abstract: In the era of digital streaming, the recommender system functions as a critical two-sided marketplace, connecting users with content through various products and services. While many existing recommender systems primarily emphasize the user side, long-term user satisfaction emerges from a healthy ecosystem integrating users, content creators, and system dynamics. This approach forms the foundation of us building a healthy recommendation ecosystem at Netflix. In this talk, we explore the multifaceted nature and unique challenges this ecosystem presents, and outline key characteristics and strategies to address the challenges.