In this tech blog, we report the current status of the SVT-AV1 project, as well as the characteristics and...

The paper gives a technical overview of AV1 - the first video codec standard from Aliance for Open Media (AOM).

We need an alternative to JPEG that a) is widely supported, b) has better compression efficiency and c) has a wider...

At Netflix, we regularly run experiments to improve the quality of our member’s streaming service. We rely on custom...

We are pleased to announce the open-source launch of Polynote: a new, polyglot notebook with first-class Scala...

A recap of the ML Platform meetup hosted at Netflix, Los Gatos on Sep 12, 2019 on the topic of Infrastructure for...

Another day, another custom script to analyze an A/B test. Maybe you’ve done this before and have an old script lying...

This blog post describes our approach to predictive CPU isolation for containers at Netflix -- enabling tasks to run...

Invited talk at the Adaptive and Multi-Task Learning (AMTL) workshop at ICML 2019 on 2019-06-15 in Long Beach, CA....

What's deeper than deep learning? A look at how recommender systems have grown from matrix factorization, to deep...

Both router buffer sizing and Active Queue Management (AQM) are concepts deeply embedded inside the computer...

Perfecting video adaptive bitrate algorithm (ABR) in a commercial setting is challenging, given the endless array of network environments, device capabilities, and content properties. To identify shortcomings effectively, a scalable methodology is needed to evaluate ABR algorithms under various scenarios. The state-of-the-art method is to evaluate a production ABR retrospectively with an optimal ABR algorithm. However,...

SVT-AV1 is a open-source AV1 framework born out of the collaboration between Intel and Netflix. In this tech blog, we...

Providing high-fidelity, near real-time data is important for multi-armed bandit and RL models to converge quickly....

We discuss salient challenges of building a search experience for a streaming media service such as Netflix. We provide an overview of the role of recommendations within the search context to aid content discovery and support searches for unavailable (out-of-catalog) entities. We also stress the importance of keystroke-level Instant Search experience, and the technical challenges associated with implementing it across...

Learn more about how Netflix uses data science and analytics to improve the reliability, security and efficiency of...

In order to produce software that improves a scientist's productivity we have come up with the following design...

From living rooms in Bogota, to morning commutes in Tokyo, to beaches in Los Angeles and dorms in Berlin, Netflix...