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Develop a comprehensive RAG solution utilizing Knowledge Databases for Amazon Bedrock and AWS CloudFormation.

Advanced (300), Amazon Bedrock, Amazon Machine Learning, Amazon Titan, AWS CloudFormation, Generative AI, Integration & Automation, Technical How-to, UncategorizedAugust 6, 202433Views0Likes0Comments
Retrieval Augmented Generation (RAG) is a cutting-edge method for constructing question answering systems, blending retrieval and foundation model capabilities. This unique approach first draws relevant data from a large body of text, using a foundation model to forge an answer from the collated information. Setting up an RAG system entails several elements such as a…

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Establish a connection between Amazon Q Business and Microsoft SharePoint Online using minimal privilege access controls.

Advanced (300), Amazon Q, Technical How-to, UncategorizedJuly 30, 202433Views0Likes0Comments
Amazon's Q Business application links with Microsoft's SharePoint Online, leveraging generative artificial intelligence to provide employees with company data and insights. This process involves the use of Amazon Q Business Connectors. In this post, least privilege access controls and best practices suggested by the Microsoft SharePoint Dev Support Team are utilized. The Sites.Selected application permission scope…

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Experimenting with Large-scale Machine Learning using Amazon SageMaker Pipelines and MLflow

Advanced (300), Amazon SageMaker, Amazon SageMaker Studio, Generative AI, Technical How-to, Thought Leadership, UncategorizedJuly 25, 202432Views0Likes0Comments
This post explains how large language models (LLMs) can be fine-tuned to better adapt to specific domains or tasks, using Amazon SageMaker and MLflow. When working with LLMs, customers may have varied requirements such as choosing a suitable pre-trained foundation model (FM) or customizing an existing model for a specific task. Using Amazon SageMaker with…

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Customizing models in Amazon Bedrock through automation using AWS Step Functions workflow.

Advanced (300), Amazon Bedrock, AWS Step Functions, Technical How-to, UncategorizedJuly 12, 202435Views0Likes0Comments
Amazon Web Services (AWS) recently introduced support for customizing models in Amazon Bedrock, a fully managed service for AI applications. The key role of Amazon Bedrock is to provide high-performing foundation language models from leading AI firms like Cohere and Meta. It aids businesses in using their proprietary data to pre-train their models according to…

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Create a digital helper for self-service using Amazon Lex and Knowledge Bases for Amazon Bedrock

Advanced (300), Amazon Bedrock, Amazon Lex, Generative AI, Technical How-to, UncategorizedJuly 2, 202431Views0Likes0Comments
Efficient automated customer service is a goal for many businesses, and AI-powered chatbots can provide human-like interactions without the need for live agents. This frees up the agents for more complex tasks. Among these AI-powered tools are Amazon Lex and Amazon Bedrock. Lex offers advanced conversational interfaces, utilizing voice and text channels to provide accurate…

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Create a discussion-oriented bot by incorporating various Language Learning Models (LLMs) within a single platform – Segment 1.

Advanced (300), Amazon Bedrock, Artificial Intelligence, Generative AI, UncategorizedJune 28, 202436Views0Likes0Comments
Generative AI and foundation models (FMs) are offering new possibilities for content generation, particularly in areas such as answering questions and summarizing documents. Companies such as Amazon, Anthropic, AI21 Labs, Cohere, and Meta supply these models. Amazon Bedrock, a fully managed service, streamlines the process of building and scaling generative AI applications. It provides access…

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