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Navigating tomorrow: Role of AI and ML in information technology

Dataconomy

With the ability to analyze a vast amount of data in real-time, identify patterns, and detect anomalies, AI/ML-powered tools are enhancing the operational efficiency of businesses in the IT sector. Why does AI/ML deserve to be the future of the modern world? Let’s understand the crucial role of AI/ML in the tech industry.

ML 121
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Automate derivative confirms processing using AWS AI services for the capital markets industry

AWS Machine Learning Blog

Artificial intelligence and machine learning (AI/ML) technologies can assist capital market organizations overcome these challenges. Intelligent document processing (IDP) applies AI/ML techniques to automate data extraction from documents. These applications come with the drawback of being inflexible and high-maintenance.

AWS 104
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Reduce Amazon SageMaker inference cost with AWS Graviton

AWS Machine Learning Blog

Amazon SageMaker provides a broad selection of machine learning (ML) infrastructure and model deployment options to help meet your ML inference needs. New generations of CPUs offer a significant performance improvement in ML inference due to specialized built-in instructions. 4xlarge instances. 4xlarge instances.

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Reduce energy consumption of your machine learning workloads by up to 90% with AWS purpose-built accelerators

Flipboard

Machine learning (ML) engineers have traditionally focused on striking a balance between model training and deployment cost vs. performance. This is important because training ML models and then using the trained models to make predictions (inference) can be highly energy-intensive tasks.

AWS 94
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Accenture creates a Knowledge Assist solution using generative AI services on AWS

AWS Machine Learning Blog

To help tackle this challenge, Accenture collaborated with AWS to build an innovative generative AI solution called Knowledge Assist. By using AWS generative AI services, the team has developed a system that can ingest and comprehend massive amounts of unstructured enterprise content.

AWS 114
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Deploy pre-trained models on AWS Wavelength with 5G edge using Amazon SageMaker JumpStart

AWS Machine Learning Blog

As one of the most prominent use cases to date, machine learning (ML) at the edge has allowed enterprises to deploy ML models closer to their end-customers to reduce latency and increase responsiveness of their applications. Even ground and aerial robotics can use ML to unlock safer, more autonomous operations.

AWS 89
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Automatically generate impressions from findings in radiology reports using generative AI on AWS

AWS Machine Learning Blog

Generative AI is powered by machine learning (ML) models—very large models that are pre-trained on vast amounts of data and commonly referred to as foundation models (FMs). The proposed solution in this post uses fine-tuning of pre-trained large language models (LLMs) to help generate summarizations based on findings in radiology reports.

AWS 128