Category: Security, Identity, & Compliance

This post takes you through the most common challenges that customers face when searching internal documents, and gives you concrete guidance on how AWS services can be used to create a generative AI conversational bot that makes internal information more useful. Unstructured data accounts for 80% of all the data found within organizations, consisting of […]

This is joint post co-written by Leidos and AWS. Leidos is a FORTUNE 500 science and technology solutions leader working to address some of the world’s toughest challenges in the defense, intelligence, homeland security, civil, and healthcare markets. Leidos has partnered with AWS to develop an approach to privacy-preserving, confidential machine learning (ML) modeling where […]

May 2023: This blog post has been updated to include a workflow that does not require building a custom container. Amazon SageMaker is a fully managed machine learning (ML) service. With SageMaker, data scientists and developers can quickly and easily build and train ML models, and then directly deploy them into a production-ready hosted environment. […]

Amazon Kendra is an intelligent search service powered by machine learning (ML). It indexes the documents stored in a wide range of repositories and finds the most relevant document based on the keywords or natural language questions the user has searched for. In some scenarios, you need the search results to be filtered based on […]

Enterprises need to translate business-critical content such as marketing materials, instruction manuals, and product catalogs across multiple languages to communicate with a global audience of customers, partners, and stakeholders. Identifying the source language in each document before calling a translate job creates complexities and adds another step to your workflow. For example, an international product […]

This is a guest blog post cowritten with athenahealth. athenahealth a leading provider of network-enabled software and services for medical groups and health systems nationwide. Its electronic health records, revenue cycle management, and patient engagement tools allow anytime, anywhere access, driving better financial outcomes for its customers and enabling its provider customers to deliver better quality […]

Amazon SageMaker Studio is a web-based integrated development environment (IDE) for machine learning (ML) that lets you build, train, debug, deploy, and monitor your ML models. Each onboarded user in Studio has their own dedicated set of resources, such as compute instances, a home directory on an Amazon Elastic File System (Amazon EFS) volume, and […]

You can access Amazon SageMaker Studio notebooks from the Amazon SageMaker console via AWS Identity and Access Management (IAM) authenticated federation from your identity provider (IdP), such as Okta. When a Studio user opens the notebook link, Studio validates the federated user’s IAM policy to authorize access, and generates and resolves the presigned URL for […]

April 2024: This post was reviewed and updated for accuracy. IT has evolved in recent years: thanks to low-code and no-code (LCNC) technologies, an increasing number of people with varying backgrounds require access to tools and platforms that were previously a prerogative to more tech-savvy individuals in the company, such as engineers or developers. Out […]

For customers looking to implement a GxP-compliant environment on AWS for artificial intelligence (AI) and machine learning (ML) systems, we have released a new whitepaper: Machine Learning Best Practices in Healthcare and Life Sciences. This whitepaper provides an overview of security and good ML compliance practices and guidance on building GxP-regulated AI/ML systems using AWS […]