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Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning - AI

The solution integrates large language models (LLMs) with your organization’s data and provides an intelligent chat assistant that understands conversation context and provides relevant, interactive responses directly within the Google Chat interface. This request contains the user’s message and relevant metadata.

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Automate Amazon Bedrock batch inference: Building a scalable and efficient pipeline

AWS Machine Learning - AI

Batch inference in Amazon Bedrock efficiently processes large volumes of data using foundation models (FMs) when real-time results aren’t necessary. To address this consideration and enhance your use of batch inference, we’ve developed a scalable solution using AWS Lambda and Amazon DynamoDB.

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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

Each distinct task type will likely require a separate LLM, which might also be fine-tuned with custom data. The Pro tier, however, would require a highly customized LLM that has been trained on specific data and terminology, enabling it to assist with intricate tasks like drafting complex legal documents. 70B and 8B.

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Amazon Q Business simplifies integration of enterprise knowledge bases at scale

AWS Machine Learning - AI

Amazon Q Business , a new generative AI-powered assistant, can answer questions, provide summaries, generate content, and securely complete tasks based on data and information in an enterprises systems. Large-scale data ingestion is crucial for applications such as document analysis, summarization, research, and knowledge management.

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Build a video insights and summarization engine using generative AI with Amazon Bedrock

AWS Machine Learning - AI

All of this data is centralized and can be used to improve metrics in scenarios such as sales or call centers. These insights are stored in a central repository, unlocking the ability for analytics teams to have a single view of interactions and use the data to formulate better sales and support strategies.

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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning - AI

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. Here you also have the data sources, processing pipelines, vector stores, and data governance mechanisms that allow tenants to securely discover, access, andthe data they need for their specific use case.

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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

To achieve these goals, the AWS Well-Architected Framework provides comprehensive guidance for building and improving cloud architectures. The solution incorporates the following key features: Using a Retrieval Augmented Generation (RAG) architecture, the system generates a context-aware detailed assessment.