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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 Blog

Prerequisites To implement the proposed solution, make sure that you have the following: An AWS account and a working knowledge of FMs, Amazon Bedrock , Amazon SageMaker , Amazon OpenSearch Service , Amazon S3 , and AWS Identity and Access Management (IAM). Amazon Titan Multimodal Embeddings model access in Amazon Bedrock.

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Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD

AWS Machine Learning Blog

We build a model to predict the severity (benign or malignant) of a mammographic mass lesion trained with the XGBoost algorithm using the publicly available UCI Mammography Mass dataset and deploy it using the MLOps framework. with administrative privileges installed on AWS Terraform version 1.5.5

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Manage Amazon SageMaker JumpStart foundation model access with private hubs

AWS Machine Learning Blog

Finally, admins can share access to private hubs across multiple AWS accounts, enabling collaborative model management while maintaining centralized control. SageMaker JumpStart uses AWS Resource Access Manager (AWS RAM) to securely share private hubs with other accounts in the same organization.

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Leveraging generative AI on AWS to transform life sciences

IBM Journey to AI blog

In this blog post, we will showcase how IBM Consulting is partnering with AWS and leveraging Large Language Models (LLMs), on IBM Consulting’s generative AI-Automation platform (ATOM), to create industry-aware, life sciences domain-trained foundation models to generate first drafts of the narrative documents, with an aim to assist human teams.

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A review of purpose-built accelerators for financial services

AWS Machine Learning Blog

Examples of other PBAs now available include AWS Inferentia and AWS Trainium , Google TPU, and Graphcore IPU. in 2012 is now widely referred to as ML’s “Cambrian Explosion.” The AWS P5 EC2 instance type range is based on the NVIDIA H100 chip, which uses the Hopper architecture. Work by Hinton et al.

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Machine learning with decentralized training data using federated learning on Amazon SageMaker

AWS Machine Learning Blog

Many ML algorithms train over large datasets, generalizing patterns it finds in the data and inferring results from those patterns as new unseen records are processed. Flower has an extensive implementation of FL averaging algorithms and a robust communication stack. Flower is open-sourced under Apache 2.0

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Build an image search engine with Amazon Kendra and Amazon Rekognition

AWS Machine Learning Blog

For example, searching for the terms “How to orchestrate ETL pipeline” returns results of architecture diagrams built with AWS Glue and AWS Step Functions. The solution applies Amazon Rekognition Custom Labels to detect AWS service logos on architecture diagrams to allow the architecture diagrams to be searchable with service names.

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