Announcing new ways to customize models with SageMaker AI, without managing GPUs

AWS Machine Learningen

AWS Machine Learning

AI Global Wire

Amazon SageMaker AI serverless model customization now includes training sessions, generally available today. You write and coordinate your own post-training loop (custom loss functions, reward signals, or multi-turn reinforcement learning) while SageMaker AI handles GPU allocation, distributed execution, fault recovery, and checkpoint storage.

This is a short summary published by AI Global Wire. The full article is owned and hosted by AWS Machine Learning — open it there to read it in full.

Read the full story at AWS Machine Learning

    Related AI news