AWS Machine Learning Blog
Category: Artificial Intelligence
Amazon Bedrock Custom Model Import now generally available
We’re pleased to announce the general availability (GA) of Amazon Bedrock Custom Model Import. This feature empowers customers to import and use their customized models alongside existing foundation models (FMs) through a single, unified API.
Deploy a serverless web application to edit images using Amazon Bedrock
In this post, we explore a sample solution that you can use to deploy an image editing application by using AWS serverless services and generative AI services. We use Amazon Bedrock and an Amazon Titan FM that allow you to edit images by using prompts.
Brilliant words, brilliant writing: Using AWS AI chips to quickly deploy Meta LLama 3-powered applications
In this post, we will introduce how to use an Amazon EC2 Inf2 instance to cost-effectively deploy multiple industry-leading LLMs on AWS Inferentia2, a purpose-built AWS AI chip, helping customers to quickly test and open up an API interface to facilitate performance benchmarking and downstream application calls at the same time.
Best practices for building robust generative AI applications with Amazon Bedrock Agents – Part 2
In this post, we dive into the architectural considerations and development lifecycle practices that can help you build robust, scalable, and secure intelligent agents.
Train, optimize, and deploy models on edge devices using Amazon SageMaker and Qualcomm AI Hub
In this post we introduce an innovative solution for end-to-end model customization and deployment at the edge using Amazon SageMaker and Qualcomm AI Hub.
Using Amazon Q Business with AWS HealthScribe to gain insights from patient consultations
In this post, we discuss how you can use AWS HealthScribe with Amazon Q Business to create a chatbot to quickly gain insights into patient clinician conversations.
Use Amazon SageMaker Studio with a custom file system in Amazon EFS
In this post, we explore three scenarios demonstrating the versatility of integrating Amazon EFS with SageMaker Studio. These scenarios highlight how Amazon EFS can provide a scalable, secure, and collaborative data storage solution for data science teams.
Summarize call transcriptions securely with Amazon Transcribe and Amazon Bedrock Guardrails
In this post, we show you how to use Amazon Transcribe to get near real-time transcriptions of calls sent to Amazon Bedrock for summarization and sensitive data redaction. We’ll walk through an architecture that uses AWS Step Functions to orchestrate the process, providing seamless integration and efficient processing
How DPG Media uses Amazon Bedrock and Amazon Transcribe to enhance video metadata with AI-powered pipelines
In this post, we share how DPG Media is introducing AI-powered processes using Amazon Bedrock into its video publication pipelines. This solution is helping accelerate audio metadata extraction, create a more engaging user experience, and save time.
How SailPoint uses Anthropic’s Claude on Amazon Bedrock to automatically generate TypeScript code for SaaS connectors
In this post, we highlight how the AWS Generative AI Innovation Center collaborated with SailPoint Technologies to build a generative AI-based coding assistant that uses Anthropic’s Claude Sonnet on Amazon Bedrock to help accelerate the development of software as a service (SaaS) connectors.