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Streamline generative AI development in Amazon Bedrock with Prompt Management and Prompt Flows (preview)

AWS Machine Learning - AI

As the adoption of generative AI continues to grow, many organizations face challenges in efficiently developing and managing prompts. Before introducing the details of the new capabilities, let’s review how prompts are typically developed, managed, and used in a generative AI application.

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

AWS Machine Learning - AI

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. The ReAct approach enables agents to generate reasoning traces and actions while seamlessly integrating with company systems through action groups.

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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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AWS empowers sales teams using generative AI solution built on Amazon Bedrock

AWS Machine Learning - AI

Prospecting, opportunity progression, and customer engagement present exciting opportunities to utilize generative AI, using historical data, to drive efficiency and effectiveness. Use case overview Using generative AI, we built Account Summaries by seamlessly integrating both structured and unstructured data from diverse sources.

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Unlock AWS Cost and Usage insights with generative AI powered by Amazon Bedrock

AWS Machine Learning - AI

We aim to target and simplify them using generative AI with Amazon Bedrock. The application generates SQL queries based on the user’s input, runs them against an Athena database containing CUR data, and presents the results in a user-friendly format. CUR data stored in an S3 bucket.