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Real value, real time: Production AI with Amazon SageMaker and Tecton

AWS Machine Learning Blog

Businesses are under pressure to show return on investment (ROI) from AI use cases, whether predictive machine learning (ML) or generative AI. Only 54% of ML prototypes make it to production, and only 5% of generative AI use cases make it to production. Using SageMaker, you can build, train and deploy ML models.

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Accelerate pre-training of Mistral’s Mathstral model with highly resilient clusters on Amazon SageMaker HyperPod

AWS Machine Learning Blog

The compute clusters used in these scenarios are composed of more than thousands of AI accelerators such as GPUs or AWS Trainium and AWS Inferentia , custom machine learning (ML) chips designed by Amazon Web Services (AWS) to accelerate deep learning workloads in the cloud.

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Meeting customer needs with our ML platform redesign

Snorkel AI

In this article, we share our journey and hope that it helps you design better machine learning systems. Table of contents Why we needed to redesign our interactive ML system In this section, we’ll go over the market forces and technological shifts that compelled us to re-architect our ML system.

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Accelerate disaster response with computer vision for satellite imagery using Amazon SageMaker and Amazon Augmented AI

AWS Machine Learning Blog

AWS recently released Amazon SageMaker geospatial capabilities to provide you with satellite imagery and geospatial state-of-the-art machine learning (ML) models, reducing barriers for these types of use cases. For more information, refer to Preview: Use Amazon SageMaker to Build, Train, and Deploy ML Models Using Geospatial Data.

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Redesigning Snorkel’s interactive machine learning systems

Snorkel AI

In this article, we share our journey and hope that it helps you design better machine learning systems. Table of contents Why we needed to redesign our interactive ML system In this section, we’ll go over the market forces and technological shifts that compelled us to re-architect our ML system.

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Redesigning Snorkel’s interactive machine learning systems

Snorkel AI

In this article, we share our journey and hope that it helps you design better machine learning systems. Table of contents Why we needed to redesign our interactive ML system In this section, we’ll go over the market forces and technological shifts that compelled us to re-architect our ML system.

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Transforming financial analysis with CreditAI on Amazon Bedrock: Octus’s journey with AWS

AWS Machine Learning Blog

Solution overview The following figure illustrates our system architecture for CreditAI on AWS, with two key paths: the document ingestion and content extraction workflow, and the Q&A workflow for live user query response. He specializes in generative AI, machine learning, and system design.

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