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Unleashing the Power of Machine Learning: Efficient Detection of Tunneling Defects in Glass Models

Researchers leverage machine learning techniques to predict and detect structural defects, known as tunneling TLS, in glass models. This approach significantly enhances the identification process, leading to a deeper understanding of amorphous solids and their unique properties.

18 Jul 2023

Demystifying AI: A Comprehensive Overview of eXplainable AI (XAI) for Trustworthy Decision-Making

Demystifying AI: A comprehensive overview of eXplainable AI (XAI) provides a thorough analysis of current trends, research, and concerns in the field, shedding light on the inner workings of AI models for trustworthy decision-making. The review covers various aspects of XAI, including data explainability, model explainability, post-hoc explainability, assessment of explanations, and available XAI research software tools. It highlights the importance of understanding and validating AI systems to ensure transparency, fairness, and accountability in their deployment

9 Jul 2023

Planting the Future: Generating Key Questions in Plant Science with ChatGPT

The study explores the use of large language models (LLMs), specifically ChatGPT, to generate important questions in plant science. ChatGPT successfully generated relevant questions, highlighting the importance of sustainable products, plant-environment interactions, plant mechanisms, and enhanced plant traits. While ChatGPT overlooked certain aspects emphasized by researchers, it demonstrated its potential as a supportive tool in plant science research.

6 Jul 2023

Supervised Learning News and Research

Unleashing the Power of Machine Learning: Efficient Detection of Tunneling Defects in Glass Models

Demystifying AI: A Comprehensive Overview of eXplainable AI (XAI) for Trustworthy Decision-Making

Planting the Future: Generating Key Questions in Plant Science with ChatGPT

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