Category: News

In this post, we explore how to deploy AI models from SageMaker JumpStart and use them with Amazon Bedrock’s powerful features. Users can combine SageMaker JumpStart’s model hosting with Bedrock’s security and monitoring tools. We demonstrate this using the Gemma 2 9B Instruct model as an example, showing how to deploy it and use Bedrock’s advanced capabilities.

This post introduces the workflow of Amazon Bedrock Model Distillation. We first introduce the general concept of model distillation in Amazon Bedrock, and then focus on the important steps in model distillation, including setting up permissions, selecting the models, providing input dataset, commencing the model distillation jobs, and conducting evaluation and deployment of the student models after model distillation.

Today, we are excited to announce that John Snow Labs’ Medical LLM – Small and Medical LLM – Medium large language models (LLMs) are now available on Amazon SageMaker Jumpstart. For medical doctors, this tool provides a rapid understanding of a patient’s medical journey, aiding in timely and informed decision-making from extensive documentation. This summarization capability not only boosts efficiency but also makes sure that no critical details are overlooked, thereby supporting optimal patient care and enhancing healthcare outcomes.

Today, we are happy to announce the availability of Binary Embeddings for Amazon Titan Text Embeddings V2 in Amazon Bedrock Knowledge Bases and Amazon OpenSearch Serverless. This post summarizes the benefits of this new binary vector support and gives you information on how you can get started.

We are excited to announce the availability of Stability AI’s latest and most advanced text-to-image model, Stable Diffusion 3.5 Large, in Amazon SageMaker JumpStart. In this post, we provide an implementation guide for subscribing to Stable Diffusion 3.5 Large in SageMaker JumpStart, deploying the model in Amazon SageMaker Studio, and generating images using text-to-image prompts.

Amazon Bedrock has launched a capability that organizations can use to tag on-demand models and monitor associated costs. Organizations can now label all Amazon Bedrock models with AWS cost allocation tags, aligning usage to specific organizational taxonomies such as cost centers, business units, and applications.

Today, we are excited to announce that the Snowflake Arctic Instruct model is available through Amazon SageMaker JumpStart to deploy and run inference. In this post, we walk through how to discover and deploy the Snowflake Arctic Instruct model using SageMaker JumpStart, and provide example use cases with specific prompts.

The Cohere Rerank 3 Nimble foundation model (FM) is now generally available in Amazon SageMaker JumpStart. This model is the newest FM in Cohere’s Rerank model series, built to enhance enterprise search and Retrieval Augmented Generation (RAG) systems. In this post, we discuss the benefits and capabilities of this new model with some examples. Overview […]

GraphStorm is a low-code enterprise graph machine learning (GML) framework to build, train, and deploy graph ML solutions on complex enterprise-scale graphs in days instead of months. With GraphStorm, you can build solutions that directly take into account the structure of relationships or interactions between billions of entities, which are inherently embedded in most real-world […]

Unlock ML governance with SageMaker-DataZone integration: streamline infrastructure, collaborate, and govern data/ML assets.