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Croissant: a metadata format for ML-ready datasets

Favorite Posted by Omar Benjelloun, Software Engineer, Google Research, and Peter Mattson, Software Engineer, Google Core ML and President, MLCommons Association Machine learning (ML) practitioners looking to reuse existing datasets to train an ML model often spend a lot of time understanding the data, making sense of its organization, or

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Shared by Google AI Technology March 6, 2024

Google at APS 2024

Favorite Posted by Kate Weber and Shannon Leon, Google Research, Quantum AI Team Today the 2024 March Meeting of the American Physical Society (APS) kicks off in Minneapolis, MN. A premier conference on topics ranging across physics and related fields, APS 2024 brings together researchers, students, and industry professionals to

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Shared by Google AI Technology March 4, 2024

Expedite your Genesys Cloud Amazon Lex bot design with the Amazon Lex automated chatbot designer

Favorite The rise of artificial intelligence (AI) has created opportunities to improve the customer experience in the contact center space. Machine learning (ML) technologies continually improve and power the contact center customer experience by providing solutions for capabilities like self-service bots, live call analytics, and post-call analytics. Self-service bots integrated

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Shared by AWS Machine Learning March 1, 2024

Supercharge your AI team with Amazon SageMaker Studio: A comprehensive view of Deutsche Bahn’s AI platform transformation

Favorite AI’s growing influence in large organizations brings crucial challenges in managing AI platforms. These include developing a scalable and operationally efficient platform that adheres to organizational compliance and security standards. Amazon SageMaker Studio offers a comprehensive set of capabilities for machine learning (ML) practitioners and data scientists. These include

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Shared by AWS Machine Learning February 29, 2024

Accelerating large-scale neural network training on CPUs with ThirdAI and AWS Graviton

Favorite This guest post is written by Vihan Lakshman, Tharun Medini, and Anshumali Shrivastava from ThirdAI. Large-scale deep learning has recently produced revolutionary advances in a vast array of fields. Although this stunning progress in artificial intelligence remains remarkable, the financial costs and energy consumption required to train these models

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Shared by AWS Machine Learning February 29, 2024