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Inside X's (Twitter) Algorithm: Insane Software Engineering Behind It Analytics Table

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About Inside X's (Twitter) Algorithm: Insane Software Engineering Behind It

Explore Inside X's (Twitter) Algorithm: Insane Software Engineering Behind It with 3,404 views, 77 likes, and 5 comments. Experience the impact of this video content that has captured audience attention.

When X open-sourced its For You recommendation repository (xai-org/x-algorithm), rumors claimed one report cancels out 468 likes. What does the Rust source code actually say, and how do X's 13 Phoenix prediction heads score your feed? šŸ”” Subscribe: https://www.youtube.com/channel/UC0DZj1PNa_Fp0MU6uPSKv5w?sub_confirmation=1 šŸ’™ Become a Member: https://www.youtube.com/channel/UC0DZj1PNa_Fp0MU6uPSKv5w/join 🐦 Twitter/X: https://x.com/cloud_codes šŸ’¬ Discord: https://discord.gg/4kJqEBMMf In this deep dive, Cloud Codes breaks down the system design, Rust source code, and mathematical scoring pipeline behind X's open-source algorithm repository. We examine why ranking_scorer.rs multiplies predicted probabilities rather than raw action counts (debunking the 468-like report myth), review the exact published weight table (where copying a link carries 20.0 weight—40x a like—and muting at -58.8 hurts more than blocking at -31.2), and dissect Nikita Bier's bidirectional-follow boost diff that multiplies mutual reply weights by 20x. Furthermore, we analyze candidate retrieval across Thunder, Phoenix vectors, and SimClusters, explore the 17 pre-scoring filters, audit the 26 out-of-network visibility rules that enforce recommendation suppression, inspect the Under the Hood account diagnostic export tool, examine the 665 hardcoded Brazilian election filter IDs, and evaluate the critical caveat of why no trained model weights were shipped in the repository. If this helped you understand backend architecture, system design, and how to build faster software, subscribe to Cloud Codes for a new infrastructure breakdown every single week! Build, solve, deploy. šŸ”— Repositories & Sources Mentioned: • X Recommendation Algorithm Repository: https://github.com/xai-org/x-algorithm • Aug 14 Rebuttal Commit Diff (c65aa17): https://github.com/xai-org/x-algorithm/commit/c65aa179db7bdd61e2c2821eac87f208a105c053 • @XOpenSource Official Announcement: https://x.com/XOpenSource • X Under the Hood Transparency Tool: https://x.com/i/under_the_hood • TechCrunch X Algorithm Coverage: https://techcrunch.com/ ā±ļø Video Chapters: 0:00 - The -234.0 Number That Broke the Internet 1:21 - How Phoenix Predicts Your Behavior (13 Heads) 2:11 - The Math Fix: Why 1 Report Does NOT Equal 468 Likes 4:17 - The Exact Weight Table: Likes, Reposts, Replies & Copy Link 5:50 - Negative Weights: Why Muting Hurts More Than Blocking 6:48 - The Bidirectional Mutual Boost (Nikita Bier Diff) 8:29 - Retrieval Pipeline: Thunder, Phoenix & SimClusters 9:02 - Out-of-Network Penalties & The Cold-Start Escalator 11:43 - Visibility Filtering: 28 Home Rules vs 26 Shadowban Rules 13:30 - Under the Hood Tool & The 665 Hardcoded Brazilian Election IDs 15:45 - The Missing Piece: Why No Model Weights Were Shipped 17:50 - Final Verdict: Is X's Algorithm Really Transparent? #x #twitter #algorithm #rust #systemdesign #cloudcodes #softwareengineering #machinelearning #open-source #devops User Queries: x algorithm open source repository xai org x algorithm x algorithm report weight 234 vs favorite weight 0 5 math ranking scorer rs x algorithm weight table values nikita bier bidirectional follow boost diff x algorithm x algorithm phoenix 13 prediction heads under the hood x com under the hood account diagnostic brazil 2026 election filter rs 665 user ids x algorithm simclusters thunder phoenix retrieval pipeline x algorithm why x algorithm repo has no trained model weights cloud codes x algorithm breakdown

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