How Meta Used AI to Map Tribal Knowledge in Large-Scale Data Pipelines
AI coding assistants were ineffective at making useful edits in large-scale data pipelines because they lacked sufficient understanding of complex, multi-repository codebases spanning multiple languages and thousands of files.
AI for American-Produced Cement and Concrete
Designing high-quality, sustainable concrete mixes that are produced in the United States while optimizing for performance characteristics.
KernelEvolve: How Meta’s Ranking Engineer Agent Optimizes AI Infrastructure
Meta needed to automatically optimize low-level infrastructure and kernel-level parameters for AI ranking models to improve performance without manual tuning.
Meta Adaptive Ranking Model: Bending the Inference Scaling Curve to Serve LLM-Scale Models for Ads
Meta needed to scale their ads ranking models to LLM-scale complexity and size while maintaining inference latency requirements for real-time ad serving.