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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

Organizations are increasingly using multiple large language models (LLMs) when building generative AI applications. Although an individual LLM can be highly capable, it might not optimally address a wide range of use cases or meet diverse performance requirements.

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Build an AI-powered document processing platform with open source NER model and LLM on Amazon SageMaker

AWS Machine Learning - AI

National Laboratory has implemented an AI-driven document processing platform that integrates named entity recognition (NER) and large language models (LLMs) on Amazon SageMaker AI. In this post, we discuss how you can build an AI-powered document processing platform with open source NER and LLMs on SageMaker.

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Revolutionize trip planning with Amazon Bedrock and Amazon Location Service

AWS Machine Learning - AI

If an image is uploaded, it is stored in Amazon Simple Storage Service (Amazon S3) , and a custom AWS Lambda function will use a machine learning model deployed on Amazon SageMaker to analyze the image to extract a list of place names and the similarity score of each place name. Here is an example from LangChain.

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Build a video insights and summarization engine using generative AI with Amazon Bedrock

AWS Machine Learning - AI

This engine uses artificial intelligence (AI) and machine learning (ML) services and generative AI on AWS to extract transcripts, produce a summary, and provide a sentiment for the call. Organizations typically can’t predict their call patterns, so the solution relies on AWS serverless services to scale during busy times.

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Build a reverse image search engine with Amazon Titan Multimodal Embeddings in Amazon Bedrock and AWS managed services

AWS Machine Learning - AI

The Amazon Bedrock single API access, regardless of the models you choose, gives you the flexibility to use different FMs and upgrade to the latest model versions with minimal code changes. Amazon Titan FMs provide customers with a breadth of high-performing image, multimodal, and text model choices, through a fully managed API.

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Deploy DeepSeek-R1 Distilled Llama models in Amazon Bedrock

AWS Machine Learning - AI

Their DeepSeek-R1 models represent a family of large language models (LLMs) designed to handle a wide range of tasks, from code generation to general reasoning, while maintaining competitive performance and efficiency. For more information, see Create a service role for model import. for the month.

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FloQast builds an AI-powered accounting transformation solution with Anthropic’s Claude 3 on Amazon Bedrock

AWS Machine Learning - AI

With advancement in AI technology, the time is right to address such complexities with large language models (LLMs). Amazon Bedrock has helped democratize access to LLMs, which have been challenging to host and manage. The workflow starts with user authentication and authorization (steps 1-3).