AWS On Air ft. Amazon SageMaker Ground Truth Plus
summary
Amazon launches SageMaker Ground Truth Plus, a turnkey data‑labeling service that claims to remove up to 80% of the manual work customers report by combining automated pre-labeling (ML-drawn bounding boxes) with an expert human workforce. Customers upload data to S3, pick formats (images, video, 3D point clouds, documents, audio), and monitor batches in a project portal; labeled batches pass machine validation, allow accept/reject feedback, and return packaged, ML-ready datasets for training.
AI-written summary · about
chapters (10)
- 0:00Introduction to the show
- 0:48Introducing Ground Truth Plus
- 1:49What is data labeling
- 4:17Challenges in data labeling
- 6:44Ground Truth Plus for startups
- 8:09Demo overview
- 8:30Getting started in console
- 13:02Backend workflow explained
- 17:39Customer review process
- 20:24Summary and next steps
related talks
33mBuild, train, and deploy ML models using Amazon SageMaker
22mCreating high-quality training sets for machine learning models
32mBuild, Train, and Deploy Machine Learning Models on AWS
19mUsing Amazon SageMaker to develop and deploy ML models
30mBring AutoML to all users across your business
37mStreamlining Machine Learning Operations
31mBuild, train, and deploy ML models using Amazon SageMaker
48mAccelerate science, research, and innovation with AWS