overfeed.news

Exowatt beats frontier models on accuracy with SageMaker serverless model customization

1d

Age

Published
Collected
Image: AWS Machine Learning Blog

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 models at up to 49x lower cost.

Excerpt from the source

Exowatt builds modular, dispatchable solar systems that deliver reliable power for energy-intensive applications such as AI data centers. Its flagship product, the Exowatt P3, captures solar energy through optical lenses, stores it as heat in a long-duration thermal battery, and dispatches electricity on demand through a heat engine. Unlike grid-tied photovoltaic solar systems, P3 powers data centers directly behind the meter, helping data centers come online without waiting in multi-year grid…

Read the full article at aws.amazon.com

overfeed.news indexes and links. We publish a short excerpt — the full article stays at AWS Machine Learning Blog.

Log in to follow this source
Exowatt beats frontier models on accuracy with SageMaker…