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Improving air quality with generative AI

AWS Machine Learning Blog

The solution harnesses the capabilities of generative AI, specifically Large Language Models (LLMs), to address the challenges posed by diverse sensor data and automatically generate Python functions based on various data formats. This allows for data to be aggregated for further manufacturer-agnostic analysis.

AWS 130
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Boosting RAG-based intelligent document assistants using entity extraction, SQL querying, and agents with Amazon Bedrock

AWS Machine Learning Blog

Overview of RAG RAG solutions are inspired by representation learning and semantic search ideas that have been gradually adopted in ranking problems (for example, recommendation and search) and natural language processing (NLP) tasks since 2010. Load into the SQL database for later querying.

SQL 125
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A review of purpose-built accelerators for financial services

AWS Machine Learning Blog

This makes GPUs well suited for data-heavy, matrix math-based, ML training workloads, and real-time inference workloads needing synchronicity at scale. Both use cases require the ability to move data around the chip quickly and controllably. An important part of the data pipeline is the production of features, both online and offline.

AWS 112
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How SnapLogic built a text-to-pipeline application with Amazon Bedrock to translate business intent into action

Flipboard

The SnapLogic Intelligent Integration Platform (IIP) enables organizations to realize enterprise-wide automation by connecting their entire ecosystem of applications, databases, big data, machines and devices, APIs, and more with pre-built, intelligent connectors called Snaps.

Database 159
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Unlocking generative AI for enterprises: How SnapLogic powers their low-code Agent Creator using Amazon Bedrock

AWS Machine Learning Blog

Agent Creator is a versatile extension to the SnapLogic platform that is compatible with modern databases, APIs, and even legacy mainframe systems, fostering seamless integration across various data environments. The resulting vectors are stored in OpenSearch Service databases for efficient retrieval and querying.

AI 89
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Build generative AI applications quickly with Amazon Bedrock IDE in Amazon SageMaker Unified Studio

AWS Machine Learning Blog

Its sales analysts face a daily challenge: they need to make data-driven decisions but are overwhelmed by the volume of available information. They have structured data such as sales transactions and revenue metrics stored in databases, alongside unstructured data such as customer reviews and marketing reports collected from various channels.

AWS 105