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Large language models (LLMs) have witnessed an unprecedented surge in popularity, with customers increasingly using publicly available models such as Llama, Stable Diffusion, and Mistral. Across diverse industries—including healthcare, finance, and marketing—organizations are now engaged in pre-training and fine-tuning these increasingly larger LLMs, which often boast billions of parameters andContinue Reading

We recently announced the general availability of cross-account sharing of Amazon 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. Customers find it challenging to share and access ML models across AWS accounts becauseContinue Reading

You can now register machine learning (ML) models in Amazon SageMaker Model Registry with Amazon SageMaker Model Cards, making it straightforward to manage governance information for specific model versions directly in SageMaker Model Registry in just a few clicks. Model cards are an essential component for registered ML models, providingContinue Reading

This post is co-written with David Gildea and Tom Nijs from Druva. Druva enables cyber, data, and operational resilience for thousands of enterprises, and is trusted by 60 of the Fortune 500. Customers use Druva Data Resiliency Cloud to simplify data protection, streamline data governance, and gain data visibility andContinue Reading

Real-world applications vary in inference requirements for their artificial intelligence and machine learning (AI/ML) solutions to optimize performance and reduce costs. Examples include financial systems processing transaction data streams, recommendation engines processing user activity data, and computer vision models processing video frames. In these scenarios, customized model monitoring for nearContinue Reading

To stay competitive, businesses across industries use foundation models (FMs) to transform their applications. Although FMs offer impressive out-of-the-box capabilities, achieving a true competitive edge often requires deep model customization through pre-training or fine-tuning. However, these approaches demand advanced AI expertise, high performance compute, fast storage access and can beContinue Reading