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Deploy DeepSeek-R1 Distilled Llama models in Amazon Bedrock

AWS Machine Learning - AI

Amazon Bedrock Custom Model Import enables the import and use of your customized models alongside existing FMs through a single serverless, unified API. This serverless approach eliminates the need for infrastructure management while providing enterprise-grade security and scalability.

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Build RAG-based generative AI applications in AWS using Amazon FSx for NetApp ONTAP with Amazon Bedrock

AWS Machine Learning - AI

Our solution uses an FSx for ONTAP file system as the source of unstructured data and continuously populates an Amazon OpenSearch Serverless vector database with the user’s existing files and folders and associated metadata. We use this data and ACLs to test permissions-based access to the embeddings in a RAG scenario with Amazon Bedrock.

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Revolutionize trip planning with Amazon Bedrock and Amazon Location Service

AWS Machine Learning - AI

This innovative service goes beyond traditional trip planning methods, offering real-time interaction through a chat-based interface and maintaining scalability, reliability, and data security through AWS native services. Architecture The following figure shows the architecture of the solution.

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Deploy DeepSeek-R1 distilled Llama models with Amazon Bedrock Custom Model Import

AWS Machine Learning - AI

Amazon Bedrock Custom Model Import enables the import and use of your customized models alongside existing FMs through a single serverless, unified API. This serverless approach eliminates the need for infrastructure management while providing enterprise-grade security and scalability.

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PHP vs. Python: How to Choose the Right Programming Language

Mobilunity

Each language’s web framework defines its versatility and scalability. They empower scalable, secure, and data-driven applications, highlighting Python as a pillar for complex and multi-functional web projects. Python frameworks are a perfect fit for businesses seeking scalable, robust, and data-intensive API solutions.

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