AWS Machine Learning Blog
Category: Artificial Intelligence
Deploy generative AI agents in your contact center for voice and chat using Amazon Connect, Amazon Lex, and Amazon Bedrock Knowledge Bases
In this post, we show you how DoorDash built a generative AI agent using Amazon Connect, Amazon Lex, and Amazon Bedrock Knowledge Bases to provide a low-latency, self-service experience for their delivery workers.
Migrating to Amazon SageMaker: Karini AI Cut Costs by 23%
In this post, we share how Karini AI’s migration of vector embedding models from Kubernetes to Amazon SageMaker endpoints improved concurrency by 30% and saved over 23% in infrastructure costs.
Harnessing the power of AI to drive equitable climate solutions: The AI for Equity Challenge
The International Research Centre on Artificial Intelligence (IRCAI), Zindi, and Amazon Web Services (AWS) are proud to announce the launch of the “AI for Equity Challenge: Climate Action, Gender, and Health”—a global virtual competition aimed at empowering organizations to use advanced AI and cloud technologies to drive real-world impact with a focus on benefitting vulnerable populations around the world.
Generate synthetic data for evaluating RAG systems using Amazon Bedrock
In this post, we explain how to use Anthropic Claude on Amazon Bedrock to generate synthetic data for evaluating your RAG system.
Making traffic lights more efficient with Amazon Rekognition
In this blog post, we show you how Amazon Rekognition can mitigate congestion at traffic intersections and reduce operations and maintenance costs.
Accelerate development of ML workflows with Amazon Q Developer in Amazon SageMaker Studio
In this post, we present a real-world use case analyzing the Diabetes 130-US hospitals dataset to develop an ML model that predicts the likelihood of readmission after discharge.
Govern generative AI in the enterprise with Amazon SageMaker Canvas
In this post, we analyze strategies for governing access to Amazon Bedrock and SageMaker JumpStart models from within SageMaker Canvas using AWS Identity and Access Management (IAM) policies. You’ll learn how to create granular permissions to control the invocation of ready-to-use Amazon Bedrock models and prevent the provisioning of SageMaker endpoints with specified SageMaker JumpStart models.
Transforming home ownership with Amazon Transcribe Call Analytics, Amazon Comprehend, and Amazon Bedrock: Rocket Mortgage’s journey with AWS
This post offers insights for businesses aiming to use artificial intelligence (AI) and cloud technologies to enhance customer service and streamline operations. We share how Rocket Mortgage’s use of AWS services set a new industry standard and demonstrate how to apply these principles to transform your client interactions and processes.
Integrate dynamic web content in your generative AI application using a web search API and Amazon Bedrock Agents
In this post, we demonstrate how to use Amazon Bedrock Agents with a web search API to integrate dynamic web content in your generative AI application.
Build a generative AI assistant to enhance employee experience using Amazon Q Business
In this blog post, we explore how you can use Amazon Q Business to build generative AI assistants that enhance employee experience and boost productivity. Amazon Q Business seamlessly integrates with internal data sources, knowledge bases, and productivity tools to equip your workforce with instant access to information, automated tasks, and personalized support.