How Meta Used AI to Map Tribal Knowledge in Large-Scale Data Pipelines

Meta engineers introduce KernelEvolve, an agentic kernel authoring system that optimizes AI model performance on various hardware platforms, including NVIDIA GPUs, AMD GPUs, and Meta's custom MTIA silicon chips. KernelEvolve uses automated search to find optimized performance, reducing development time from weeks to hours and yielding improvements of up to 60% in inference throughput. By treating kernel optimization as a search problem, KernelEvolve explores hundreds of alternative kernel implementations, often matching or exceeding human expert performance in hours rather than weeks. This automation enables Meta's production environment to serve trillions of daily inference requests while reducing engineering effort required to integrate heterogeneous hardware for training and inference. KernelEvolve addresses the challenge of explosive kernel growth by autonomously generating and optimizing production-grade kernels for complex AI models and diverse hardware, adapting to model and hardware evolution, and enabling Meta to rapidly integrate new hardware into its AI infrastructure.

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.