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Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

AWS Machine Learning - AI

Knowledge Bases for Amazon Bedrock allows you to build performant and customized Retrieval Augmented Generation (RAG) applications on top of AWS and third-party vector stores using both AWS and third-party models. If you want more control, Knowledge Bases lets you control the chunking strategy through a set of preconfigured options.

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

AWS Machine Learning - AI

You can now use Agents for Amazon Bedrock and Knowledge Bases for Amazon Bedrock to configure specialized agents that seamlessly run actions based on natural language input and your organization’s data. The following diagram illustrates the solution architecture. The following are some example prompts: Create a new claim.

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Build a contextual chatbot for financial services using Amazon SageMaker JumpStart, Llama 2 and Amazon OpenSearch Serverless with Vector Engine

AWS Machine Learning - AI

The LLM generated text, and the IR system retrieves relevant information from a knowledge base. In this post, we explore building a contextual chatbot for financial services organizations using a RAG architecture with the Llama 2 foundation model and the Hugging Face GPTJ-6B-FP16 embeddings model, both available in SageMaker JumpStart.

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Advanced RAG patterns on Amazon SageMaker

AWS Machine Learning - AI

With the advancements being made with LLMs like the Mixtral-8x7B Instruct , derivative of architectures such as the mixture of experts (MoE) , customers are continuously looking for ways to improve the performance and accuracy of generative AI applications while allowing them to effectively use a wider range of closed and open source models.

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Top 13 GitHub Alternatives in 2020 [Free and Paid]

Codegiant

You can download either a GitHub Mac or Windows version. It’s worth noting that GitLab supports macOS, Linux, iOS, Android, except for its Windows clients. Based on the Acceptable Use Policy , Microsoft Windows operating systems are not permitted with GitLab. Knowledge bases and FAQs. Debug in production?—?Google

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Azure Migration Easy!

iTexico

Microsoft Azure puts a lot on the table for your consideration: enterprise-level cloud support, cloud-based windows servers, active directories, sharepoint and office, and plenty more you can look into. These services may include disaster recovery, the Internet of Things, serverless computing, and so on so forth.

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