AI for American-Produced Cement and Concrete

Meta's Engineering team developed the Adaptive Ranking Model to serve Large Language Model (LLM)-scale models in real-time ads recommendation environments. This innovation bends the inference scaling curve, balancing increasing model complexity with low latency and cost efficiency. By dynamically aligning model complexity with user context and intent, the Adaptive Ranking Model ensures a high-quality ad experience while maintaining strict, sub-second latency and improving advertiser value. The Adaptive Ranking Model achieves inference efficiency through three key innovations: Inference-Efficient Model Scaling, Model/System Co-Design, and Reimagined Serving Infrastructure. These innovations enable the system to serve LLM-scale models at sub-second latency, unlocking a deeper understanding of user interests and intent without compromising the experience. The system has delivered a +3% increase in ad conversions and +5% increase in ad click-through rate for targeted users since its launch on Instagram.