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Combine keyword and semantic search for text and images using Amazon Bedrock and Amazon OpenSearch Service

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OpenSearch Service is the AWS recommended vector database for Amazon Bedrock. OpenSearch is a distributed open-source search and analytics engine composed of a search engine and vector database. To learn more, see Improve search results for AI using Amazon OpenSearch Service as a vector database with Amazon Bedrock.

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Integrate generative AI capabilities into Microsoft Office using Amazon Bedrock

AWS Machine Learning Blog

AWS (Amazon Web Services) is a comprehensive cloud computing platform offering a wide range of services like computing power, database storage, content delivery, and more.n2. Make sure that we have Powertools for AWS Lambda (Python) available in our runtime, for example, by attaching a Lambda layer to our function.

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Transforming financial analysis with CreditAI on Amazon Bedrock: Octus’s journey with AWS

AWS Machine Learning Blog

It was built using a combination of in-house and external cloud services on Microsoft Azure for large language models (LLMs), Pinecone for vectorized databases, and Amazon Elastic Compute Cloud (Amazon EC2) for embeddings. Opportunities for innovation CreditAI by Octus version 1.x

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Configure cross-account access of Amazon Redshift clusters in Amazon SageMaker Studio using VPC peering

AWS Machine Learning Blog

With cloud computing, as compute power and data became more available, machine learning (ML) is now making an impact across every industry and is a core part of every business and industry. The SourceIdentity attribute is used to tie the identity of the original SageMaker Studio user to the Amazon Redshift database user.

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Access control for vector stores using metadata filtering with Knowledge Bases for Amazon Bedrock

AWS Machine Learning Blog

After the doctor has successfully signed in, the application retrieves the list of patients associated with the doctor’s ID from the Amazon DynamoDB database. Before querying the knowledge base, the Lambda function retrieves data from the DynamoDB database, which stores doctor-patient associations.

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Securing MLflow in AWS: Fine-grained access control with AWS native services

AWS Machine Learning Blog

Deploys an Amazon Aurora Serverless database for the data store and Amazon Simple Storage Service (Amazon S3) for the artifact store. Irshad works with large AWS Global ISV and SI partners and helps them build their cloud strategy and broad adoption of Amazon’s cloud computing platform.

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