Tag

YouTube

0 views collected around this technical thread.

IT Services Circle
IT Services Circle
Dec 15, 2023 · Frontend Development

How Chrome Manifest V3 Affects Ad Blockers and YouTube

The upcoming retirement of Chrome Manifest V2 forces extensions to adopt Manifest V3, which requires Chrome Web Store review for updates, dramatically slowing ad‑blocker rule changes and giving YouTube an advantage, while other browsers remain unaffected.

Ad BlockerBrowser CompatibilityChrome
0 likes · 3 min read
How Chrome Manifest V3 Affects Ad Blockers and YouTube
Code Ape Tech Column
Code Ape Tech Column
Feb 7, 2023 · Backend Development

YouTube Backend Architecture: Databases, Vitess, and Cloud‑Native Infrastructure

This article examines YouTube's massive backend infrastructure, detailing its use of MySQL with Vitess for horizontal scaling, caching with Memcache, coordination via Zookeeper, cloud‑native deployment on Kubernetes, CDN delivery, and the storage systems (GFS, BigTable) that enable billions of users to upload and stream petabytes of video data.

VitessYouTubebackend
0 likes · 15 min read
YouTube Backend Architecture: Databases, Vitess, and Cloud‑Native Infrastructure
Architecture Digest
Architecture Digest
Jan 4, 2023 · Databases

YouTube Backend Architecture: Databases, Scaling, and Vitess

This article examines YouTube’s massive backend infrastructure, detailing how the platform stores billions of videos using MySQL, Vitess for horizontal scaling, sharding, replication, disaster management, cloud‑native deployment on Kubernetes, and the supporting storage systems such as GFS and BigTable.

VitessYouTubebackend
0 likes · 13 min read
YouTube Backend Architecture: Databases, Scaling, and Vitess
NetEase LeiHuo UX Big Data Technology
NetEase LeiHuo UX Big Data Technology
Nov 22, 2022 · Artificial Intelligence

Sample Weighting in Machine Learning: From YouTube Playback Duration to Game Recommendation Optimization

This article explains why and how sample weighting is used in machine learning, illustrates YouTube's conversion of video watch time into sample weights to align with its commercial goals, and describes practical weighted‑logistic‑regression techniques applied to improve game recommendation systems.

AIGame RecommendationRecommendation systems
0 likes · 8 min read
Sample Weighting in Machine Learning: From YouTube Playback Duration to Game Recommendation Optimization
DataFunTalk
DataFunTalk
Feb 21, 2020 · Artificial Intelligence

Avoid Strategic Mistakes—How to Properly Set Optimization Goals for Recommendation Systems

The article explains why recommendation‑system optimization goals must align with business objectives, illustrates this with YouTube’s watch‑time target and Alibaba’s multi‑task CVR/CTR model, and stresses the strategic importance of defining clear goals to guide cross‑team collaboration.

AIAlibabaCVR
0 likes · 10 min read
Avoid Strategic Mistakes—How to Properly Set Optimization Goals for Recommendation Systems
DataFunTalk
DataFunTalk
Dec 8, 2018 · Artificial Intelligence

Analysis of YouTube’s Deep Neural Network–Based Recommendation System

The article examines YouTube’s large‑scale recommendation system, detailing its deep‑learning architecture, the challenges of scale, freshness and noise, and the design choices in candidate generation, ranking, data collection, and evaluation that together deliver over 70% of user watch time.

Artificial IntelligenceRankingYouTube
0 likes · 10 min read
Analysis of YouTube’s Deep Neural Network–Based Recommendation System
Architecture Digest
Architecture Digest
Feb 20, 2017 · Backend Development

YouTube Architecture Overview: High‑Concurrency, High‑Availability Design

This article examines YouTube's large‑scale architecture, detailing its platform components, web and video services, database evolution, data‑center strategy, and key lessons for building high‑concurrency, fault‑tolerant backend systems.

BigDataYouTubearchitecture
0 likes · 9 min read
YouTube Architecture Overview: High‑Concurrency, High‑Availability Design