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Retrieval-Augmented Generation with LangChain, Amazon SageMaker JumpStart, and MongoDB Atlas semantic search

AWS Machine Learning

Generative AI models have the potential to revolutionize enterprise operations, but businesses must carefully consider how to harness their power while overcoming challenges such as safeguarding data and ensuring the quality of AI-generated content. As a Data Engineer he was involved in applying AI/ML to fraud detection and office automation.

APIs 127
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Generating value from enterprise data: Best practices for Text2SQL and generative AI

AWS Machine Learning

We are seeing numerous uses, including text generation, code generation, summarization, translation, chatbots, and more. One such area that is evolving is using natural language processing (NLP) to unlock new opportunities for accessing data through intuitive SQL queries. What percentage of customers are from each region?”

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Identify objections in customer conversations using Amazon Comprehend to enhance customer experience without ML expertise

AWS Machine Learning

Since conversational AI has improved in recent years, many businesses have adopted cutting-edge technologies like AI-powered chatbots and AI-powered agent support to improve customer service while increasing productivity and lowering costs. API Gateway bypasses the request to Lambda. Lambda checks the format and stores it in DynamoDB.

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Build a custom UI for Amazon Q Business

AWS Machine Learning

The workflow includes the following steps: The user accesses the chatbot application, which is hosted behind an Application Load Balancer. Amazon Q uses the chat_sync API to carry out the conversation. He helps organizations in achieving specific business outcomes by using data and AI, and accelerating their AWS Cloud adoption journey.

APIs 136
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Design secure generative AI application workflows with Amazon Verified Permissions and Amazon Bedrock Agents

AWS Machine Learning

Agents automatically call the necessary APIs to interact with the company systems and processes to fulfill the request. The App calls the Claims API Gateway API to run the claims proxy passing user requests and tokens. Claims API Gateway runs the Custom Authorizer to validate the access token. User – The user.

APIs 95
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Improve visibility into Amazon Bedrock usage and performance with Amazon CloudWatch

AWS Machine Learning

Figure: 4 In the CloudWatch console you have the option to create custom dashboards Under Custom Dashboards , you should see a dashboard called Contextual-Chatbot-Dashboard. With over 35 patents granted across various technology domains, she has a passion for continuous innovation and using data to drive business outcomes.

Metrics 119
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How Twilio generated SQL using Looker Modeling Language data with Amazon Bedrock

AWS Machine Learning

Every use case has different requirements for context length, token size, and the ability to handle various tasks like summarization, task completion, chatbot applications, and so on. Johnny Chivers is a Senior Solutions Architect working within the Strategic Accounts team at AWS.