software-engineering.
30 writings found
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Facebook's Hybrid Search: When Keywords Meet Neural Embeddings
Meta rebuilt Facebook Groups search by merging traditional keyword matching with dense vector embeddings, then used Llama 3 to validate the results at scale.
Facebook's Hybrid Search: When Keyword Matching Isn't Enough Anymore
Meta's Groups search now blends lexical precision with semantic understanding. Here's why traditional keyword matching is dying and what comes next.
Facebook's Hybrid Search: When Keyword Matching Meets Neural Understanding
Meta rebuilt Facebook Groups search by blending traditional inverted indices with dense embeddings, then used Llama 3 to grade results at scale.
Meta's AI Agents Are Now Fixing Their Own Performance Problems
How Meta built a unified AI platform that automates finding and fixing performance issues, recovering hundreds of megawatts without scaling headcount.
How Meta Escaped the Open Source Forking Trap with WebRTC
Meta's multi-year journey to break free from a divergent WebRTC fork reveals hard lessons about managing open source dependencies at scale.
How Meta Escaped the WebRTC Forking Trap Without Breaking Everything
Meta's multi-year migration from a divergent WebRTC fork to upstream reveals hard-earned lessons about maintaining open source dependencies at scale.
When Machines Write Code, Humans Must Learn to Judge
As LLMs generate more code, teams face cognitive surrender and debt proliferation. The future isn't about writing code, it's about verification.
Meta's KernelEvolve: When AI Writes Its Own Performance Code
Meta's KernelEvolve system uses AI agents to automatically optimize low-level hardware kernels, achieving 60% performance gains in hours instead of weeks.
Meta's Adaptive Ranking Model: The Real Cost of Serving Trillion-Parameter Ads
Meta scaled ads recommendations to LLM complexity while keeping latency under a second. Here's why their inference trilemma solution matters beyond advertising.
Treating AI Instructions as Infrastructure, Not Documentation
How encoding team standards as versioned AI instructions solves the consistency problem that plagues AI-assisted development workflows.
Making Team Standards Executable: Infrastructure for AI-Assisted Development
AI coding tools produce wildly different results based on who's prompting. Treating team standards as versioned, executable instructions solves the consistency problem.
Meta's AI is Reshoring American Concrete, One Mix at a Time
How Bayesian optimization is helping U.S. concrete producers ditch imported cement and redesign mixes in days instead of months.
How Facebook Built Friend Bubbles: A Deep Dive into Social ML Architecture
Meta's friend bubbles system combines closeness prediction models, ranking optimization, and performance engineering to surface friend-driven content at scale.
Facebook's Friend Bubbles: When Social Graphs Meet Recommendation Systems
Meta's friend bubbles on Reels reveal how social signals and ML models can coexist in video recommendations without destroying performance.
Facebook's Friend Bubbles: A Masterclass in Social Graph ML
How Meta blends closeness prediction models, multi-task ranking, and prefetch optimization to surface friend-driven content at scale on Reels