With Amazon Comprehend, you can extract insights from text without being a machine learning expert. Using its built-in models, Comprehend can analyze the syntax of your input documents and find entities, events, key phrases, personally identifiable information (PII), and the overall sentiment or sentiments associated with specific entities (such as brands or products). Today, we are adding the capability to detect toxic content. This new capability helps you build safer environments for your end users. For example, you can use toxicity detection to improve the safety of applications open to external contributions such as comments. When using generative AI, toxicity detection can be used to check the input prompts and the output responses from large language models (LLMs). You can…
Category: AWS
Reposts from Amazon Web Services (AWS).
New – Manage Planned Lifecycle Events on AWS Health
We are announcing new features in AWS Health to help you manage planned lifecycle events for your AWS resources and dynamically track the completion of actions that your team takes at the resource-level to ensure continued smooth operations of your applications. Some examples of planned lifecycle events are an Amazon Elastic Kubernetes Service (Amazon EKS) Kubernetes version end of standard support, Amazon Relational Database Service (Amazon RDS) certificate rotations, and end of support for other open source software, to name a few. These features include: The ability to dynamically track the completion of actions at the resource level where possible, to minimize disruption to applications. Timely visibility into upcoming planned lifecycle events, using notifications at least 90 days in advance…
Amazon Aurora MySQL zero-ETL integration with Amazon Redshift is now generally available
“Data is at the center of every application, process, and business decision,” wrote Swami Sivasubramanian, VP of Database, Analytics, and Machine Learning at AWS, and I couldn’t agree more. A common pattern customers use today is to build data pipelines to move data from Amazon Aurora to Amazon Redshift. These solutions help them gain insights to grow sales, reduce costs, and optimize their businesses. To help you focus on creating value from data instead of preparing data for analysis, we announced Amazon Aurora zero-ETL integration with Amazon Redshift at AWS re:Invent 2022 and in public preview for Amazon Aurora MySQL-Compatible Edition in June 2023. Now generally available: Amazon Aurora MySQL zero-ETL integration with Amazon Redshift Today, we announced the general…
New – Create application-consistent snapshots using Amazon Data Lifecycle Manager and custom scripts
Amazon Data Lifecycle Manager now supports the use of pre-snapshot and post-snapshot scripts embedded in AWS Systems Manager documents. You can use these scripts to ensure that Amazon Elastic Block Store (Amazon EBS) snapshots created by Data Lifecycle Manager are application-consistent. Scripts can pause and resume I/O operations, flush buffered data to EBS volumes, and so forth. As part of this launch we are also publishing a set of detailed blog posts that show you how to use this feature with self-managed relational databases and Windows Volume Shadow Copy Service (VSS). Data Lifecycle Manager (DLM) Recap As a quick recap, Data Lifecycle Manager helps you to automate the creation, retention, and deletion of Amazon EBS volume snapshots. Once you have…