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Create a generative AI-based application builder assistant using Amazon Bedrock Agents

Create a generative AI-based application builder assistant using Amazon Bedrock Agents

In this post, we set up an agent using Amazon Bedrock Agents to act as a software application builder assistant. Agentic workflows are a fresh new perspective in building dynamic and complex business use- case based workflows with the help of large language models (LLM) as their reasoning engine or brain. These agentic workflows decompose …

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Transitioning from Amazon Rekognition people pathing: Exploring other alternatives

Transitioning from Amazon Rekognition people pathing: Exploring other alternatives

Amazon Rekognition people pathing is a machine learning (ML)–based capability of Amazon Rekognition Video that users can use to understand where, when, and how each person is moving in a video. This capability can be used for multiple use cases, such as for understanding: Retail analytics – Customer flow in the store and identifying high-traffic …

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Unlocking generative AI for enterprises: How SnapLogic powers their low-code Agent Creator using Amazon Bedrock

Unlocking generative AI for enterprises: How SnapLogic powers their low-code Agent Creator using Amazon Bedrock

This post is cowritten with Greg Benson, Aaron Kesler and David Dellsperger from SnapLogic. The landscape of enterprise application development is undergoing a seismic shift with the advent of generative AI. SnapLogic, a leader in generative integration and automation, has introduced the industry’s first low-code generative AI development platform, Agent Creator, designed to democratize AI …

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Next-generation learning experience using Amazon Bedrock and Anthropic’s Claude: Innovation from Classworks

Next-generation learning experience using Amazon Bedrock and Anthropic’s Claude: Innovation from Classworks

This post is co-written with Jerry Henley, Hans Buchheim and Roy Gunter from Classworks. Classworks is an online teacher and student platform that includes academic screening, progress monitoring, and specially designed instruction for reading and math for grades K–12. Classworks’s unique ability to ingest student assessment data from various sources, analyze it, and automatically deliver …

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Fine-tune a BGE embedding model using synthetic data from Amazon Bedrock

Fine-tune a BGE embedding model using synthetic data from Amazon Bedrock

Have you ever faced the challenge of obtaining high-quality data for fine-tuning your machine learning (ML) models? Generating synthetic data can provide a robust solution, especially when real-world data is scarce or sensitive. For instance, when developing a medical search engine, obtaining a large dataset of real user queries and relevant documents is often infeasible …

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Boost post-call analytics with Amazon Q in QuickSight

Boost post-call analytics with Amazon Q in QuickSight

In today’s customer-centric business world, providing exceptional customer service is crucial for success. Contact centers play a vital role in shaping customer experiences, and analyzing post-call interactions can provide valuable insights to improve agent performance, identify areas for improvement, and enhance overall customer satisfaction. Amazon Web Services (AWS) has AI and generative AI solutions that …

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Create a next generation chat assistant with Amazon Bedrock, Amazon Connect, Amazon Lex, LangChain, and WhatsApp

Create a next generation chat assistant with Amazon Bedrock, Amazon Connect, Amazon Lex, LangChain, and WhatsApp

This post is co-written with Harrison Chase, Erick Friis and Linda Ye from LangChain. Generative AI is set to revolutionize user experiences over the next few years. A crucial step in that journey involves bringing in AI assistants that intelligently use tools to help customers navigate the digital landscape. In this post, we demonstrate how …

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Generative AI foundation model training on Amazon SageMaker

Generative AI foundation model training on Amazon SageMaker

To stay competitive, businesses across industries use foundation models (FMs) to transform their applications. Although FMs offer impressive out-of-the-box capabilities, achieving a true competitive edge often requires deep model customization through pre-training or fine-tuning. However, these approaches demand advanced AI expertise, high performance compute, fast storage access and can be prohibitively expensive for many organizations. …

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