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Amazon CloudWatch

The Weather Company improves MLOps through the use of Amazon SageMaker, AWS CloudFormation, and Amazon CloudWatch.

The Weather Company (TWCo) needed a robust Machine Learning Operations (MLOps) platform to support their growing data science team, and to create predictive, privacy-friendly machine learning (ML) models. The existing cloud environment lacked transparency for ML jobs and monitoring, making collaboration challenging. TWCo partnered with AWS Machine Learning Solutions Lab (MLSL) to enhance its MLOps…

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Determine inactive endpoints in Amazon SageMaker

Amazon's SageMaker is a machine learning (ML) platform offering a comprehensive toolkit for building, deploying, and managing ML models at scale. This platform optimizes the development and deployment process of ML solutions for developers and data scientists. AWS aids in this innovation by providing services that simplify infrastructure management tasks such as provisioning, scaling, and resource…

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Enhance insight into the use and functioning of Amazon Bedrock through Amazon CloudWatch.

Amazon Bedrock, a managed service that offers a selection of foundation models from leading AI companies, empowers users to build new, delightful experiences for their customers using generative AI. As a response to end users' curiosity for prescriptive ways to monitor generative AI applications' health and performance in an operational environment, Amazon Bedrock has introduced…

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Enhance insight into the use and efficiency of Amazon Bedrock through Amazon CloudWatch.

Amazon Bedrock, a generative artificial intelligence (AI) service, allows customers to build new and delightful user experiences using high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, and Meta. Users can use these models securely, privately, and responsibly through a single API, along with a broad set of capabilities for building…

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Observability of AWS Inferentia nodes in Amazon EKS clusters available through open source.

The growth and advancements in machine learning (ML) models have led to huge models that require a significant amount of computational resources for training and inferencing. Consequently, monitoring or observing these models and their performance is crucial for fine tuning and cost optimization. AWS has developed a solution to this using some of its tools…

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Strategies and methods for overseeing extensive language models on AWS.

Large Language Models (LLMs) have significantly impacted various functions in the field of Natural Language Processing (NLP), such as language translation, text summarization, and sentiment analysis. Despite these advantages, monitoring LLM's performance and behavior has become increasingly challenging due to their growing size and complexity. Therefore, it is necessary to implement an effective and scalable…

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