How Thomson Reuters Labs achieved AI/ML innovation at pace with AWS MLOps services

This article discusses how Thomson Reuters Labs achieved AI/ML innovation at pace using AWS MLOps services like Amazon SageMaker, SageMaker Experiments, SageMaker Model Registry, and SageMaker Pipelines.

Specifically, the article covers:

• The challenges faced by Thomson Reuters Labs due to lack of standardized MLOps process
• Overview of the MLTools and MLTools CLI developed by Thomson Reuters Labs to standardize MLOps workflow
• Integration of MLTools with SageMaker Experiments for tracking experiments and runs
• Integration of MLTools with SageMaker Pipelines for creating reproducible ML workflows
• Benefits achieved such as faster model development, efficient troubleshooting, and cost savings
• Plans for future improvements to the MLTools framework