Social learning: Collaborative learning with large language models

Favorite Posted by Amirkeivan Mohtashami, Research Intern, and Florian Hartmann, Software Engineer, Google Research Large language models (LLMs) have significantly improved the state of the art for solving tasks specified using natural language, often reaching performance close to that of people. As these models increasingly enable assistive agents, it could

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Shared by Google AI Technology March 7, 2024

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