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Automate the insurance claim lifecycle using Agents and Knowledge Bases for Amazon Bedrock

AWS Machine Learning - AI

Generative AI agents are a versatile and powerful tool for large enterprises. These agents excel at automating a wide range of routine and repetitive tasks, such as data entry, customer support inquiries, and content generation. System integration – Agents make API calls to integrated company systems to run specific actions.

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Build a contextual chatbot application using Knowledge Bases for Amazon Bedrock

AWS Machine Learning - AI

One way to enable more contextual conversations is by linking the chatbot to internal knowledge bases and information systems. Integrating proprietary enterprise data from internal knowledge bases enables chatbots to contextualize their responses to each user’s individual needs and interests.

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Incorporate offline and online human – machine workflows into your generative AI applications on AWS

AWS Machine Learning - AI

Recent advances in artificial intelligence have led to the emergence of generative AI that can produce human-like novel content such as images, text, and audio. An important aspect of developing effective generative AI application is Reinforcement Learning from Human Feedback (RLHF).

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Build knowledge-powered conversational applications using LlamaIndex and Llama 2-Chat

AWS Machine Learning - AI

One popular approach is using Retrieval Augmented Generation (RAG) to create Q&A systems that comprehend complex information and provide natural responses to queries. RAG allows models to tap into vast knowledge bases and deliver human-like dialogue for applications like chatbots and enterprise search assistants.