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In this interview, Hulu senior engineer Cheng Mo shares how the company transitioned from jQuery and Backbone to React, discusses the challenges of server‑side rendering, offers practical advice on framework selection, learning curves, React's future, and tips for front‑end developers preparing for interviews.
The article reviews Hulu’s 2018 iQIYI keynote on AI video applications, detailing how AI drives personalized recommendations, content analysis through computer vision and NLP, ad targeting across visual, linguistic, and semantic layers, and outlines the platform’s machine‑learning architecture and future directions.
In this talk, Hulu’s Zhuge Yue explains how massive user data, diverse content, and advanced AI and machine learning techniques power personalized recommendations, content embedding, explainable AI, and innovative ad integration, outlining current implementations and future architectural directions for video streaming platforms.
This article explores the evolution of human‑computer interaction from its early interface concepts through multimodal and intelligent interaction stages, highlighting historical milestones, the rise of AI‑driven smart devices, emerging challenges such as bias, transparency, and the quest for universal interaction methods.
This article explains the core ideas and step-by-step procedures of widely used sampling methods—including inverse transform, rejection, importance, and Markov Chain Monte Carlo techniques such as Metropolis‑Hastings and Gibbs—highlighting their mathematical foundations, practical implementations, and when each method is appropriate.
This article explains the shortcomings of traditional GANs, introduces the Wasserstein GAN (WGAN) as a remedy using the Earth‑Mover distance, describes the theoretical motivations, outlines the algorithmic steps and constraints, and provides illustrative diagrams and references for deeper study.
This article introduces probabilistic graphical models, explains the differences between Bayesian and Markov networks, derives their joint probability distributions, and details the principles and graphical representations of naive Bayes and maximum entropy models with illustrative equations and diagrams.
This article introduces Hulu's in‑house OLAP engine Nesto, detailing its near‑real‑time data ingestion, nested data model, TB‑level storage using HBase and Parquet, MPP query execution, custom predicate library, and the overall architecture that enables sub‑second ad‑hoc queries for user analytics.
This article examines the evolution, strengths, and drawbacks of major video codecs—H.264, HEVC, VP9, and AV1—while offering practical criteria for selecting the most suitable standard and encoder for modern streaming services.
This article explains the principles, biological inspiration, network structure, training process, design parameters, and practical differences of Self‑Organizing Maps (SOM), an unsupervised neural network used for clustering, visualization, and feature extraction, and compares it with methods like K‑means.
