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Augment fraud transactions using synthetic data in Amazon SageMaker

AWS Machine Learning

Gartner predicts that by 2024, 60 percent of the data used for the development of ML and analytics solutions will be synthetically generated and that the use of synthetic data will continue to increase substantially. This blog post explores tabular synthetic data generation. Prerequisites: You must have an AWS account to run SageMaker.

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Philips accelerates development of AI-enabled healthcare solutions with an MLOps platform built on Amazon SageMaker

AWS Machine Learning

This is a joint blog with AWS and Philips. These capabilities are essential for demonstrating compliance with regulatory standards and ensuring transparency and accountability in AI/ML workflows. Users from several business units were trained and onboarded to the platform, and that number is expected to grow in 2024.

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Build private and secure enterprise generative AI apps with Amazon Q Business and AWS IAM Identity Center

AWS Machine Learning

As of April 30, 2024 Amazon Q Business is generally available. The sample use case in this post uses an IAM Identity Center account instance with its identity source configured as Okta, which is used as the IdP. There are two types of IAM Identity Center instances: an organization instance and an account instance.

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Your guide to generative AI and ML at AWS re:Invent 2023

AWS Machine Learning

Join Shaown Nandi, AWS Director of Technology for Industries and Strategic Accounts, and industry leaders to hear how generative AI is accelerating content creation and helping organizations reimagine customer experiences. You can also get behind the wheel yourself on November 30, when the track opens for the 2024 Open Racing.

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Enable data sharing through federated learning: A policy approach for chief digital officers

AWS Machine Learning

This is a guest blog post written by Nitin Kumar, a Lead Data Scientist at T and T Consulting Services, Inc. Furthermore, model hosting on Amazon SageMaker JumpStart can help by exposing the endpoint API without sharing model weights. In this post, we discuss the value and potential impact of federated learning in the healthcare field.

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Transform customer engagement with no-code LLM fine-tuning using Amazon SageMaker Canvas and SageMaker JumpStart

AWS Machine Learning

Prerequisites First-time users need an AWS account and AWS Identity and Access Management (IAM) role with SageMaker and Amazon Simple Storage Service (Amazon S3) access. Enrich your existing software as a service (SaaS), software platforms, web portals, or mobile apps with your fine-tuned LLM using the API or SDKs.

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Welcome to a New Era of Building in the Cloud with Generative AI on AWS

AWS Machine Learning

We expect our first Trainium2 instances to be available to customers in 2024. With Amazon Bedrock, customers are only ever one API call away from a new model. CRM or ERP applications), and write a few AWS Lambda functions to execute the APIs (e.g., Meta Llama 2 70B, and additions to the Amazon Titan family.

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