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High-performance computing on AWS

Xebia

How does High-Performance Computing on AWS differ from regular computing? For this HPC will bring massive parallel computing, cluster and workload managers and high-performance components to the table. Today’s server hardware is powerful enough to execute most compute tasks. Why HPC and cloud are a good fit? No ageing infrastructure.

AWS 147
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Techniques and approaches for monitoring large language models on AWS

AWS Machine Learning - AI

However, as these models continue to grow in size and complexity, monitoring their performance and behavior has become increasingly challenging. Monitoring the performance and behavior of LLMs is a critical task for ensuring their safety and effectiveness. The following diagram illustrates this architecture.

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Accenture creates a regulatory document authoring solution using AWS generative AI services

AWS Machine Learning - AI

The following diagram illustrates the solution architecture. The application uses the Amplify libraries for Amazon Simple Storage Service (Amazon S3) and uploads documents provided by users to Amazon S3. Amazon SQS enables a fault-tolerant decoupled architecture. It captures the message ID returned by Amazon SQS.

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Dynamic Data Processing Using Serverless Java With Quarkus on AWS Lambda (Part 1)

Dzone - DevOps

This was not only about rewriting applications, but the backend data stores were also redesigned in terms of dynamic scalability , high performance, and flexibility for event-driven architecture.

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Automate the process to change image backgrounds using Amazon Bedrock and AWS Step Functions

AWS Machine Learning - AI

The following diagram provides a simplified view of the solution architecture and highlights the key elements. The workflow consists of the following steps: A user uploads multiple images into an Amazon Simple Storage Service (Amazon S3) bucket via a Streamlit web application. Invokes the Amazon Bedrock InvokeModel API action.

AWS 112
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Learning Lambda — Part 9

Mike Roberts

Scaling and State This is Part 9 of Learning Lambda, a tutorial series about engineering using AWS Lambda. So far in this series we’ve only been talking about processing a small number of events with Lambda, one after the other. Lambda will horizontally scale precisely when we need it to a massive extent.

Lambda 52
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Fundamentals of Data Engineering

Xebia

The data engineer is also expected to create agile data architectures that evolve as new trends emerge. Building architectures that optimize performance and cost at a high level is no longer enough. The best data engineers view their responsibilities through business and technical lenses.