AI

Deploy Amazon SageMaker Projects with Terraform Cloud

Amazon SageMaker Projects empower data scientists to self-serve Amazon Web Services (AWS) tooling and infrastructure to organize all entities of the machine learning (ML) lifecycle, and further enable organizations to standardize and constrain the resources available to their data science teams in pre-packaged templates. For AWS customers using Terraform to define and manage their infrastructure-as-code (IaC),

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How ZURU improved the accuracy of floor plan generation by 109% using Amazon Bedrock and Amazon SageMaker

ZURU Tech is on a mission to change the way we build, from town houses and hospitals to office towers, schools, apartment blocks, and more. Dreamcatcher is a user-friendly platform developed by ZURU that allows users with any level of experience to collaborate in the building design and construction process. With the simple click of

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Going beyond AI assistants: Examples from Amazon.com reinventing industries with generative AI

Generative AI revolutionizes business operations through various applications, including conversational assistants such as Amazon’s Rufus and Amazon Seller Assistant. Additionally, some of the most impactful generative AI applications operate autonomously behind the scenes, an essential capability that empowers enterprises to transform their operations, data processing, and content creation at scale. These non-conversational implementations, often in

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Architect a mature generative AI foundation on AWS

Generative AI applications seem simple—invoke a foundation model (FM) with the right context to generate a response. In reality, it’s a much more complex system involving workflows that invoke FMs, tools, and APIs and that use domain-specific data to ground responses with patterns such as Retrieval Augmented Generation (RAG) and workflows involving agents. Safety controls

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Bridging the gap between development and production: Seamless model lifecycle management with Amazon Bedrock

In the landscape of generative AI, organizations are increasingly adopting a structured approach to deploy their AI applications, mirroring traditional software development practices. This approach typically involves separate development and production environments, each with its own AWS account, to create logical separation, enhance security, and streamline workflows. Amazon Bedrock is a fully managed service that

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Revolutionizing earth observation with geospatial foundation models on AWS

Emerging transformer-based vision models for geospatial data—also called geospatial foundation models (GeoFMs)—offer a new and powerful technology for mapping the earth’s surface at a continental scale, providing stakeholders with the tooling to detect and monitor surface-level ecosystem conditions such as forest degradation, natural disaster impact, crop yield, and many others. GeoFMs represent an emerging research

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