Category: HAQM SageMaker

Cloud costs can significantly impact your business operations. Gaining real-time visibility into infrastructure expenses, usage patterns, and cost drivers is essential. To allocate costs to cloud resources, a tagging strategy is essential. This post outlines steps you can take to implement a comprehensive tagging governance strategy across accounts, using AWS tools and services that provide visibility and control. By setting up automated policy enforcement and checks, you can achieve cost optimization across your machine learning (ML) environment.

We recently announced the general availability of cross-account sharing of HAQM SageMaker Model Registry using AWS Resource Access Manager (AWS RAM), making it easier to securely share and discover machine learning (ML) models across your AWS accounts. In this post, we will show you how to use this new cross-account model sharing feature to build your own centralized model governance capability, which is often needed for centralized model approval, deployment, auditing, and monitoring workflows.

In this post, we show you how to build a generative AI-powered trip-planning service that revolutionizes the way travelers discover and explore destinations. By using advanced AI technology and HAQM Location Service, the trip planner lets users translate inspiration into personalized travel itineraries. This innovative service goes beyond traditional trip planning methods, offering real-time interaction through a chat-based interface and maintaining scalability, reliability, and data security through AWS native services.

Stability AI’s newest launch of Stable Diffusion 3.5 Large (SD3.5L) on HAQM SageMaker JumpStart enhances image generation, human anatomy rendering, and typography by producing more diverse outputs and adhering closely to user prompts, making it a significant upgrade over its predecessor. In this post, we explore advanced prompt engineering techniques that can enhance the performance of these models and facilitate the creation of compelling imagery through text-to-image transformations.

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 HAQM 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 HAQM SageMaker Studio, and generating images using text-to-image prompts.

You can now register machine learning (ML) models in HAQM SageMaker Model Registry with HAQM SageMaker Model Cards, making it straightforward to manage governance information for specific model versions directly in SageMaker Model Registry in just a few clicks. In this post, we discuss a new feature that supports the integration of model cards with the model registry. We discuss the solution architecture and best practices for managing model cards with a registered model version, and walk through how to set up, operationalize, and govern your models using the integration in the model registry.

In this post, you will learn how to extract key objects from image queries using HAQM Rekognition and build a reverse image search engine using HAQM Titan Multimodal Embeddings from HAQM Bedrock in combination with HAQM OpenSearch Serverless Service.

In this post, we demonstrate how to fine-tune Meta’s latest Llama 3.2 text generation models, Llama 3.2 1B and 3B, using HAQM SageMaker JumpStart for domain-specific applications. By using the pre-built solutions available in SageMaker JumpStart and the customizable Meta Llama 3.2 models, you can unlock the models’ enhanced reasoning, code generation, and instruction-following capabilities to tailor them for your unique use cases.

This post is cowritten with Mones Raslan, Ravi Sharma and Adele Gouttes from Zalando. Zalando SE is one of Europe’s largest ecommerce fashion retailers with around 50 million active customers. Zalando faces the challenge of regular (weekly or daily) discount steering for more than 1 million products, also referred to as markdown pricing. Markdown pricing is […]

HAQM SageMaker Ground Truth enables the creation of high-quality, large-scale training datasets, essential for fine-tuning across a wide range of applications, including large language models (LLMs) and generative AI. By integrating human annotators with machine learning, SageMaker Ground Truth significantly reduces the cost and time required for data labeling. Whether it’s annotating images, videos, or […]