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Hulu Beijing

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Latest from Hulu Beijing

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Hulu Beijing
Hulu Beijing
Mar 16, 2023 · Artificial Intelligence

Inside Hulu’s Distributed Training Platform: Architecture, Challenges, and Solutions

This article explores Hulu’s five‑year‑old machine‑learning training platform, detailing its three‑layer architecture, the shift from single‑node to distributed training, and the technical solutions—including parameter servers, Ring AllReduce, Kubernetes, Volcano, and Horovod—that enable scalable AI workloads across GPU, CPU, and storage resources.

AI infrastructureDistributed TrainingHulu
0 likes · 13 min read
Inside Hulu’s Distributed Training Platform: Architecture, Challenges, and Solutions
Hulu Beijing
Hulu Beijing
Feb 14, 2023 · Operations

How Hulu Scaled Its Live Streaming for the Super Bowl: Inside the War Room

This article details how Hulu's Beijing engineering teams prepared, scaled, and operated the live streaming infrastructure for the 2024 Super Bowl, handling a 20% traffic surge with advanced load‑testing, auto‑scaling, and coordinated on‑call support to ensure a flawless broadcast.

HuluSuper Bowlcloud
0 likes · 3 min read
How Hulu Scaled Its Live Streaming for the Super Bowl: Inside the War Room
Hulu Beijing
Hulu Beijing
Dec 2, 2022 · Artificial Intelligence

How Disney+ Designs a Multi‑Task Video Search Ranking Model

This article explains the architecture of a video search ranking system that combines a deep encoding network, multi‑task expert networks, and a bias‑correction module to jointly optimize relevance, click‑through rate, and watch time for streaming platforms.

Bias CorrectionMulti-Task Learningdeep learning
0 likes · 15 min read
How Disney+ Designs a Multi‑Task Video Search Ranking Model
Hulu Beijing
Hulu Beijing
Nov 18, 2022 · Artificial Intelligence

How Video Search Engines Rank Results: From Click Models to Multi‑Goal Optimization

This article explains the architecture of video search engine ranking, covering optimization objectives such as relevance, click‑through rate and watch time, and detailing pointwise, pairwise and listwise learning approaches, model training pipelines, and online serving strategies.

click-through ratemachine learningmulti-objective optimization
0 likes · 17 min read
How Video Search Engines Rank Results: From Click Models to Multi‑Goal Optimization
Hulu Beijing
Hulu Beijing
Nov 4, 2022 · Fundamentals

How HLS Powers Adaptive Streaming on Hulu & Disney+: A Deep Dive

This article explains the fundamentals of Apple's HTTP Live Streaming (HLS) protocol, covering how adaptive bitrate video is encoded into multiple renditions, organized via media and multivariant playlists, and how clients and servers coordinate playback in both on‑demand and live streaming scenarios.

Protocoladaptive streaminghls
0 likes · 21 min read
How HLS Powers Adaptive Streaming on Hulu & Disney+: A Deep Dive
Hulu Beijing
Hulu Beijing
Oct 21, 2022 · Big Data

How Hulu Scales Spark on Kubernetes: Cloud‑Native Big Data at Disney‑Scale

Hulu’s data platform team describes how they migrated large‑scale Spark workloads from Yarn to native Spark on Kubernetes, leveraging AWS services such as EKS, S3, and custom operators to achieve dynamic scaling, unified monitoring, cost‑effective resource management, and improved stability for search, recommendation, and advertising pipelines.

AWSKubernetesSpark
0 likes · 18 min read
How Hulu Scales Spark on Kubernetes: Cloud‑Native Big Data at Disney‑Scale
Hulu Beijing
Hulu Beijing
Sep 2, 2022 · Artificial Intelligence

How Hulu Eliminated Feature Drift with Server‑Side Feature Logging

This article explains Hulu's server‑side feature logging system that aligns online and offline recommendation features, measures and mitigates feature drift caused by data source, timing, and code differences, and improves model performance while reducing resource consumption.

Hulufeature driftfeature logging
0 likes · 17 min read
How Hulu Eliminated Feature Drift with Server‑Side Feature Logging
Hulu Beijing
Hulu Beijing
Aug 31, 2022 · Fundamentals

Algorithm Trio: Pattern Search, Tree Leaf Count, and Bounded Stock Trading

This article presents three algorithmic challenges: counting pattern occurrences on an M×N canvas, determining the number of leaf nodes in a binary tree represented by an array, and maximizing stock trade profit under constraints on negative returns and total gain, each with input specifications, sample cases, and solution outlines.

ConstraintsPattern Matchingalgorithm
0 likes · 8 min read
Algorithm Trio: Pattern Search, Tree Leaf Count, and Bounded Stock Trading