Creating an end-to-end streaming video pipeline for VoD and Live is a challenge but it has been well understood and solved. Since video takes lot of resources in terms of bandwidth, compute and memory, there is still a challenge to scale the streaming video pipeline for billions of people. For example, how to handle the video infrastructure for new-year eve, when everyone is sharing their live videos with their near and dear ones, or when it is a goal in soccer world-cup final. In this talk, I will focus on these challenges of video infra structure at scale and how industry is addressing them by using approaches from heterogeneous domains including Machine Learning, Single Processing and Statistical Analysis.
18. Machine learning@ Scale
• What problems to solve
• Classification
• Ranking
• Video encoding decisions
• Content understanding
• Making decisions
• Training speed
• Training frequency
