At Netflix we’re focused on running our service as efficiently as possible to serve our more than 150 million members around the world. We are always looking for ways to highlight and fix performance-related efficiency problems. This talk will provide an overview of several problems we have found and fixed using tools we developed in-house. We’ll discuss tools and techniques for narrowing larger problems down to a small set of instances for deeper analysis. The talk should provide a good overview of how certain parts of the service work, along with information on some of the tools that we have made open source for the larger community.
Presented by
Ed Hunter
Engineering Leader, Netflix
Los Gatos, California USA
Benchmarking AI models from an ethical angle involves ensuring that the evaluation processes promote fairness,...
Find out moreIn his talk on "Fake News: easier to detect with sentiment analysis," Sanjaikanth E. Vadakkethil...
Find out more