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How Rocket Companies modernized their data science solution on AWS

AWS Machine Learning Blog

Deployment times stretched for months and required a team of three system engineers and four ML engineers to keep everything running smoothly. With just one part-time ML engineer for support, our average issue backlog with the vendor is practically non-existent.

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Establishing an AI/ML center of excellence

AWS Machine Learning Blog

The rapid advancements in artificial intelligence and machine learning (AI/ML) have made these technologies a transformative force across industries. According to a McKinsey study , across the financial services industry (FSI), generative AI is projected to deliver over $400 billion (5%) of industry revenue in productivity benefits.

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Meta SAM 2.1 is now available in Amazon SageMaker JumpStart

AWS Machine Learning Blog

Conclusion In this post, we explored how SageMaker JumpStart empowers data scientists and ML engineers to discover, access, and deploy a wide range of pre-trained FMs for inference, including Metas most advanced and capable models to date. On the endpoint details page, choose Delete. Choose Delete again to confirm. models today.

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How Axfood enables accelerated machine learning throughout the organization using Amazon SageMaker

AWS Machine Learning Blog

This functionality enables us to build generative AI applications in the future for increased understanding of how the model works. About the Authors Dr. Björn Blomqvist is the Head of AI Strategy at Axfood AB. Pavel Maslov is a Senior DevOps and ML engineer in the Analytic Platforms team.