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Amazon Q Business simplifies integration of enterprise knowledge bases at scale

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Enhancing AWS Support Engineering efficiency The AWS Support Engineering team faced the daunting task of manually sifting through numerous tools, internal sources, and AWS public documentation to find solutions for customer inquiries. Then we introduce the solution deployment using three AWS CloudFormation templates.

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

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Solution overview The NER & LLM Gen AI Application is a document processing solution built on AWS that combines NER and LLMs to automate document analysis at scale. Click here to open the AWS console and follow along. The endpoint lifecycle is orchestrated through dedicated AWS Lambda functions that handle creation and deletion.

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Llama 4 family of models from Meta are now available in SageMaker JumpStart

AWS Machine Learning Blog

Virginia) AWS Region. Prerequisites To try the Llama 4 models in SageMaker JumpStart, you need the following prerequisites: An AWS account that will contain all your AWS resources. An AWS Identity and Access Management (IAM) role to access SageMaker AI. b64encode(img).decode('utf-8') b64encode(response.content).decode('utf-8')

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Optimized PyTorch 2.0 inference with AWS Graviton processors

AWS Machine Learning Blog

AWS, Arm, Meta and others helped optimize the performance of PyTorch 2.0 As a result, we are delighted to announce that AWS Graviton-based instance inference performance for PyTorch 2.0 times the speed for BERT, making Graviton-based instances the fastest compute optimized instances on AWS for these models. is up to 3.5

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Llama 3.1: All You Need to Know About Meta’s Latest LLM

Data Science Dojo

Despite its large size, Meta has made this model open-source and accessible through various platforms, including Hugging Face, GitHub, and several cloud providers like AWS, Nvidia, Microsoft Azure, and Google Cloud. Like the 405B model, the 70B version is also open-source and available for download and use on various platforms.

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NeMo Retriever Llama 3.2 text embedding and reranking NVIDIA NIM microservices now available in Amazon SageMaker JumpStart

AWS Machine Learning Blog

With this launch, you can now deploy NVIDIAs optimized reranking and embedding models to build, experiment, and responsibly scale your generative AI ideas on AWS. As part of NVIDIA AI Enterprise available in AWS Marketplace , NIM is a set of user-friendly microservices designed to streamline and accelerate the deployment of generative AI.

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Deploy pre-trained models on AWS Wavelength with 5G edge using Amazon SageMaker JumpStart

AWS Machine Learning Blog

To reduce the barrier to entry of ML at the edge, we wanted to demonstrate an example of deploying a pre-trained model from Amazon SageMaker to AWS Wavelength , all in less than 100 lines of code. In this post, we demonstrate how to deploy a SageMaker model to AWS Wavelength to reduce model inference latency for 5G network-based applications.

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