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DataFunTalk
DataFunTalk
Jan 29, 2021 · Artificial Intelligence

Content Embedding Practices and Challenges at Hulu

This article presents Hulu's multi‑layered approach to content understanding and embedding, describing tag‑based graph embeddings, metadata‑BERT enhancements, multimodal video/audio feature aggregation, and various applications such as similarity search, ranking, cold‑start retrieval, and collection modeling, while also discussing current limitations and open research questions.

HuluRecommendation Systemscontent embedding
0 likes · 12 min read
Content Embedding Practices and Challenges at Hulu
Hulu Beijing
Hulu Beijing
Oct 26, 2020 · Artificial Intelligence

Hulu’s AI Innovations: Graph Neural Networks, Ad Targeting & Content Embeddings

The Hulu AI Class event showcased a series of technical talks covering large‑scale graph neural network optimizations, multi‑factor video ad placement algorithms, recommendation and search engine techniques, machine‑learning‑driven video codec improvements, and advanced content‑embedding methods, highlighting practical engineering experiences from Hulu’s Beijing office.

Graph Neural NetworksRecommendation Systemsad targeting
0 likes · 9 min read
Hulu’s AI Innovations: Graph Neural Networks, Ad Targeting & Content Embeddings
Hulu Beijing
Hulu Beijing
May 31, 2018 · Artificial Intelligence

How AI is Transforming Video Streaming: Today’s Practices and Future Trends

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.

AIRecommendation Systemscontent embedding
0 likes · 18 min read
How AI is Transforming Video Streaming: Today’s Practices and Future Trends