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Revolutionizing customer service: MaestroQA’s integration with Amazon Bedrock for actionable insight

AWS Machine Learning - AI

We discuss the unique challenges MaestroQA overcame and how they use AWS to build new features, drive customer insights, and improve operational inefficiencies. This expansion is achieved without introducing additional complexities, thereby maintaining operational efficiency while adhering to Regional data regulations.

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Use LangChain with PySpark to process documents at massive scale with Amazon SageMaker Studio and Amazon EMR Serverless

AWS Machine Learning - AI

That’s where the new Amazon EMR Serverless application integration in Amazon SageMaker Studio can help. In this post, we demonstrate how to leverage the new EMR Serverless integration with SageMaker Studio to streamline your data processing and machine learning workflows.

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Integrating Key Vault Secrets with Azure Synapse Analytics

Apiumhub

Key Components of Azure Synapse Analytics Data Warehousing with Dedicated SQL Pools At its core, Azure Synapse provides dedicated SQL pools (formerly known as Azure SQL Data Warehouse), which function as a traditional MPP (massively parallel processing) data warehouse. on-premises, AWS, Google Cloud).

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eSentire delivers private and secure generative AI interactions to customers with Amazon SageMaker

AWS Machine Learning - AI

To accomplish this, eSentire built AI Investigator, a natural language query tool for their customers to access security platform data by using AWS generative artificial intelligence (AI) capabilities. eSentire has over 2 TB of signal data stored in their Amazon Simple Storage Service (Amazon S3) data lake.

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Improving air quality with generative AI

AWS Machine Learning - AI

On December 6 th -8 th 2023, the non-profit organization, Tech to the Rescue , in collaboration with AWS, organized the world’s largest Air Quality Hackathon – aimed at tackling one of the world’s most pressing health and environmental challenges, air pollution. Having a human-in-the-loop to validate each data transformation step is optional.

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How Mixbook used generative AI to offer personalized photo book experiences

AWS Machine Learning - AI

Years ago, Mixbook undertook a strategic initiative to transition their operational workloads to Amazon Web Services (AWS) , a move that has continually yielded significant advantages. The data intake process involves three macro components: Amazon Aurora MySQL-Compatible Edition , Amazon S3, and AWS Fargate for Amazon ECS.

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Technology Trends for 2025

O'Reilly Media - Ideas

Building applications with RAG requires a portfolio of data (company financials, customer data, data purchased from other sources) that can be used to build queries, and data scientists know how to work with data at scale. Data engineers build the infrastructure to collect, store, and analyze data.

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