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Expedite your Genesys Cloud Amazon Lex bot design with the Amazon Lex automated chatbot designer

AWS Machine Learning

Some examples include a customer calling to check on the status of an order and receiving an update from a bot, or a customer needing to submit a renewal for a license and the chatbot collecting the necessary information, which it hands over to an agent for processing. Save your configuration.

Chatbots 122
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How Formula 1® uses generative AI to accelerate race-day issue resolution

AWS Machine Learning

During these live events, F1 IT engineers must triage critical issues across its services, such as network degradation to one of its APIs. This impacts downstream services that consume data from the API, including products such as F1 TV, which offer live and on-demand coverage of every race as well as real-time telemetry.

APIs 69
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How Much Does it Cost to Make a Chatbot that Actually Works?

Creative Virtual

Ask any seller of a highly complex and customizable chatbot or virtual agent system about cost and you’re likely to get an evasive answer. Increasingly, in this ever-saturating market, it’s easy to find elements of chatbot pricing (i.e., The truth is, building a successful chatbot is not purely a question of technology.

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Building AI chatbots using Amazon Lex and Amazon Kendra for filtering query results based on user context

AWS Machine Learning

When the user signs in to an Amazon Lex chatbot, user context information can be derived from Amazon Cognito. The Amazon Lex chatbot can be integrated into Amazon Kendra using a direct integration or via an AWS Lambda function. The use of the AWS Lambda function will provide you with fine-grained control of the Amazon Kendra API calls.

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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. GPT-NeoXT-Chat-Base-20B is designed for use in chatbot applications and may not perform well for other use cases outside of its intended scope. In addition to the aforementioned fine-tuning, GPT-NeoXT-Chat-Base-20B-v0.16

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GenAI for Aerospace: Empowering the workforce with expert knowledge on Amazon Q and Amazon Bedrock

AWS Machine Learning

This post shows how aerospace customers can use AWS generative AI and ML-based services to address this document-based knowledge use case, using a Q&A chatbot to provide expert-level guidance to technical staff based on large libraries of technical documents. Finally, we need to create user access permissions to our chatbot.

APIs 109
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Elevating the generative AI experience: Introducing streaming support in Amazon SageMaker hosting

AWS Machine Learning

Now you can continuously stream inference responses back to the client when using SageMaker real-time inference to help you build interactive experiences for generative AI applications such as chatbots, virtual assistants, and music generators. We use Streamlit for the sample demo application UI.

APIs 116