Amazon SageMaker AI

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How Salesforce achieves high-performance model deployment with Amazon SageMaker AI

Amazon SageMaker, Amazon SageMaker AI, Artificial Intelligence, Best Practices, Customer Solutions, Experience-Based Acceleration /

This post is a joint collaboration between Salesforce and AWS and is being cross-published on both the Salesforce Engineering Blog and the AWS Machine Learning Blog. The Salesforce AI Model Serving team is working to push the boundaries of natural language processing and AI capabilities for enterprise applications. Their key focus areas include optimizing large […]

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Reduce ML training costs with Amazon SageMaker HyperPod

Amazon Machine Learning, Amazon SageMaker, Amazon SageMaker AI, Artificial Intelligence, Foundation models, Generative AI /

Training a frontier model is highly compute-intensive, requiring a distributed system of hundreds, or thousands, of accelerated instances running for several weeks or months to complete a single job. For example, pre-training the Llama 3 70B model with 15 trillion training tokens took 6.5 million H100 GPU hours. On 256 Amazon EC2 P5 instances (p5.48xlarge,

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