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The key to operational AI: Modern data architecture

CIO

Recent research shows that 67% of enterprises are using generative AI to create new content and data based on learned patterns; 50% are using predictive AI, which employs machine learning (ML) algorithms to forecast future events; and 45% are using deep learning, a subset of ML that powers both generative and predictive models.

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From legacy to lakehouse: Centralizing insurance data with Delta Lake

CIO

The time-travel functionality of the delta format enables AI systems to access historical data versions for training and testing purposes. Modern AI models, particularly large language models, frequently require real-time data processing capabilities.

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Comprehensive data management for AI: The next-gen data management engine that will drive AI to new heights

CIO

All industries and modern applications are undergoing rapid transformation powered by advances in accelerated computing, deep learning, and artificial intelligence. The next phase of this transformation requires an intelligent data infrastructure that can bring AI closer to enterprise data.

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Build an AI-powered document processing platform with open source NER model and LLM on Amazon SageMaker

AWS Machine Learning - AI

National Laboratory has implemented an AI-driven document processing platform that integrates named entity recognition (NER) and large language models (LLMs) on Amazon SageMaker AI. In this post, we discuss how you can build an AI-powered document processing platform with open source NER and LLMs on SageMaker.

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Using John Snow Labs’ Medical Large Language Models on Azure Fabric

John Snow Labs

John Snow Labs’ Medical Language Models library is an excellent choice for leveraging the power of large language models (LLM) and natural language processing (NLP) in Azure Fabric due to its seamless integration, scalability, and state-of-the-art accuracy on medical tasks.

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What is data architecture? A framework to manage data

CIO

In addition to using cloud for storage, many modern data architectures make use of cloud computing to analyze and manage data. Modern data architectures use APIs to make it easy to expose and share data. AI and machine learning models. Scalable data pipelines. Seamless data integration.

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Inferencing holds the clues to AI puzzles

CIO

Inferencing has emerged as among the most exciting aspects of generative AI large language models (LLMs). A quick explainer: In AI inferencing , organizations take a LLM that is pretrained to recognize relationships in large datasets and generate new content based on input, such as text or images.