AI Daily — August 6, 2026
2026-08-06
engineering.fb.com
From User Sequences to Scaling Laws: A Multi-Stage Architecture for Meta's Ads Ranking
Meta Engineering details their evolved ads ranking system, which builds on 2024's sequence learning work by applying scaling laws to a multi-stage recommendation architecture. The system models temporal user interaction signals across products, ads, and content rather than relying on static sparse features, enabling better capture of individual preference and intent at billions-of-interactions scale. The post covers how scaling laws were applied to guide architectural decisions across retrieval and ranking stages.