Overview
FireworkTV's Infrastructure Overhaul: Enhancing Video Recommendation System with AWSProvectus |
Analytics & Modeling - Machine Learning Sensors - Camera / Video Systems | |
Cement Construction & Infrastructure | |
Quality Assurance | |
Construction Management Infrastructure Inspection | |
System Integration Training | |
Operational Impact
The new ML infrastructure built on AWS has provided FireworkTV with a robust foundation for its video recommender system. The migration to Amazon SageMaker has circumvented the limitations of Lambda, reducing admin overhead and infrastructure costs. It has also empowered the ML team with a more efficient process and better collaboration. With the 2x reduction in ML infrastructure costs and 10x acceleration in inference and training pipelines, FireworkTV is now poised to scale and grow its video recommender system. The company can make faster improvements to its system, deliver personalized video recommendations in real time due to reduced latency, and is set for future growth through faster and more accurate video recommendations that engage users, increase app usage, and drive ad revenue. | |
Quantitative Benefit
Reduced ML infrastructure costs by 2x | |
Sped up inferences by 10x | |
Built a new ML infrastructure on AWS in just four weeks | |