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Create a multimodal chatbot tailored to your unique dataset with Amazon Bedrock FMs

AWS Machine Learning

With recent advances in large language models (LLMs), a wide array of businesses are building new chatbot applications, either to help their external customers or to support internal teams. This script can be acquired directly from Amazon S3 using aws s3 cp s3://aws-blogs-artifacts-public/artifacts/ML-16363/deploy.sh.

Chatbots 119
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Integrate dynamic web content in your generative AI application using a web search API and Amazon Bedrock Agents

AWS Machine Learning

Amazon Bedrock agents use LLMs to break down tasks, interact dynamically with users, run actions through API calls, and augment knowledge using Amazon Bedrock Knowledge Bases. 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.

APIs 102
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Build a contextual chatbot application using Knowledge Bases for Amazon Bedrock

AWS Machine Learning

Modern chatbots can serve as digital agents, providing a new avenue for delivering 24/7 customer service and support across many industries. Chatbots also offer valuable data-driven insights into customer behavior while scaling effortlessly as the user base grows; therefore, they present a cost-effective solution for engaging customers.

Chatbots 111
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Build a serverless voice-based contextual chatbot for people with disabilities using Amazon Bedrock

AWS Machine Learning

Specifically, we focus on chatbots. Chatbots are no longer a niche technology. Although AI chatbots have been around for years, recent advances of large language models (LLMs) like generative AI have enabled more natural conversations. We also provide a sample chatbot application. We discuss this later in the post.

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GPT-NeoXT-Chat-Base-20B foundation model for chatbot applications is now available on Amazon SageMaker

AWS Machine Learning

This demonstration provides an open-source foundation model chatbot for use within your application. As a JumpStart model hub customer, you get improved performance without having to maintain the model script outside of the SageMaker SDK. The inference script is prepacked with the model artifact.

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Chatbot: Complete Guide

JivoChat

Chatbots have become a success around the world, and nowadays are used by 58% of B2B companies and 42% of B2C companies. In 2022 at least 88% of users had one conversation with chatbots. There are many reasons for that, a chatbot is able to simulate human interaction and provide customer service 24h a day. What Is a Chatbot?

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Derive meaningful and actionable operational insights from AWS Using Amazon Q Business

AWS Machine Learning

In this post, we’re using the APIs for AWS Support , AWS Trusted Advisor , and AWS Health to programmatically access the support datasets and use the Amazon Q Business native Amazon Simple Storage Service (Amazon S3) connector to index support data and provide a prebuilt chatbot web experience. Test the solution through chat.

Scripts 112