META: Evolution of Recommender Model

Since we began writing our reports, we've covered extensive ground on Ad Tech. However, we haven't systematically explained recommender algorithms and why AI and GPUs are fundamentally transforming them.

We've invested significant time understanding how META and other advertising companies evolve their recommender algorithms, frequently highlighting these contributions in our META Preview reports.

Before joining the hedge fund, I served as the recommender algorithm product manager for a short-video platform, witnessing the industry's complete transformation over the past decade. When I worked as a recommender algorithm PM, the short-video industry's content moderation and tagging systems were still nascent—I even participated in building some of the earliest moderation and tagging frameworks.

With earnings season now behind us, I'm dedicating two weeks to reviewing the technical evolution of recommender algorithms and explaining why LLMs and Agents are experiencing similar technological progressions.

This report will introduce recommender algorithm analysis approaches you've likely never encountered. I'll explain why AI and GPUs transformed the recommender algorithm industry without relying on technical jargon, and how AI has further revolutionized recommender algorithms in the past three months.

If 2023-2024 marked Generative Recommender Model 1.0, then the past three months have unlocked Generative Recommender Model 2.0.