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

AWS Machine Learning - AI

As AI technology continues to evolve, the capabilities of generative AI agents are expected to expand, offering even more opportunities for customers to gain a competitive edge. These managed agents play conductor, orchestrating interactions between FMs, API integrations, user conversations, and knowledge sources loaded with your data.

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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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The importance of software documentation tools

Apiumhub

Technical documentation helps the new team members adapt faster to the working habits of the company. Good technical documentation using the right tools will make information easily accessible, provide a limited number of user entry points, help new developers learn quickly, simplify the product and help cut support costs.

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Simplify data prep for generative AI with Amazon SageMaker Data Wrangler

AWS Machine Learning - AI

Data from social media, reviews, or any user generated contents can also contain toxic and biased contents, and you may need to filter them out using some pre-processing steps. Read and write access to an Amazon Simple Storage Service (Amazon S3) bucket. The choice of vector database is an important architectural decision.

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Metadata Management: Process, Tools, Use Cases, and Best Practices

Altexsoft

Metadata management is a set of activities, technologies, and policies that target metadata collection, storage, and organizing. Plus, a data fabric architecture design approach is also based on metadata as one of the main building blocks. Metadata storage usually implies developing a specialized repository.

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Generate customized, compliant application IaC scripts for AWS Landing Zone using Amazon Bedrock

AWS Machine Learning - AI

With Amazon Bedrock, teams can input high-level architectural descriptions and use generative AI to generate a baseline configuration of Terraform scripts. AWS Landing Zone architecture in the context of cloud migration AWS Landing Zone can help you set up a secure, multi-account AWS environment based on AWS best practices.

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