On Negative Sampling for Audio-Visual Contrastive Learning from Movies
The abundance and ease of utilizing sound, along with the fact that auditory clues reveal a plethora of...
Netflix: A Culture of Learning
February 3, 2022
The abundance and ease of utilizing sound, along with the fact that auditory clues reveal a plethora of...
At Netflix, we aim to provide recommendations that match our members’ interests. To achieve this, we rely...
Deep learning has profoundly impacted many areas of machine learning. However, it took a while for its...
Understanding the value of acquiring or retaining subscribers is crucial for subscription-based businesses....
This is the fifth post in a multi-part series on how Netflix uses A/B tests to inform decisions and...
Here we describe the role of Experimentation and A/B testing within the larger Data Science and Engineering...
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