AI brief
Exowatt used Amazon SageMaker AI serverless model customization to build a repeatable pipeline producing task-specific fine-tuned models for edge and cloud deployment, which achieved higher accuracy than frontier models.
Why it matters: It illustrates fine-tuning small task-specific models on SageMaker as an alternative to relying on frontier models for accuracy.
Written by AI from AWS Machine Learning Blog's published text.
Source
“In this post, we show how Exowatt used Amazon SageMaker AI serverless model customization to build a repeatable AI pipeline that produces task-specific fine-tuned models for two deployment targets, edge and cloud, achieving higher accuracy than frontier…”
Published by the organisation it describes; treat claims as first-party statements.
Read original story ↗