Match Cutting: Finding Cuts with Smooth Visual Transitions
A match cut is a transition between a pair of shots that uses similar framing, composition, or action to...
Netflix: A Culture of Learning
February 3, 2022
A match cut is a transition between a pair of shots that uses similar framing, composition, or action to...
In this blog post, we introduce RecSysOps a set of best practices and lessons that we learned while...
This writeup is about using reinforcement learning to construct an optimal list of recommendations when the...
We present a technique to reduce the dynamic range of an HDRI lighting environment map in an efficient,...
While the LED panels used in virtual production systems can display vibrant imagery with a wide color...
In an instant search setting such as Netflix Search where results are returned in response to every...
Research at Netflix is aimed at improving various aspects of our business. Research applications span many areas including our personalization algorithms, content valuation, and streaming optimization. To maximize the impact of our research, we do not centralize research into a separate organization. Instead, we have many teams that pursue research in collaboration with business teams, engineering teams, and other researchers. This allows for close partnerships between researchers and the business or engineering teams in each area. In addition, research that applies to the same methodological area or business area is shared and highlighted in discussion and debate forums to strengthen the work and its impact. These forums also serve to identify and motivate future research directions.
Researchers at Netflix love working in a unique environment enabled by the Netflix Culture that values curiosity, courage with smart risks, innovation, science, rigor, and high impact. Across the company, we strive to run experiments to back our hypotheses up with evidence, which often uncover surprises that redirect or refine our research. We relish the freedom to try new ideas and the opportunity to debate their implications with colleagues spanning all parts and levels of the company, including our own CEO.
Learning how to entertain the world
Figuring out how to bring unique joy to each member
Letting members make the decisions
Driving insights from data
Accelerating and democratizing ML innovation
The best bang for your bytes