Making AI Less “Thirsty”: Uncovering and Addressing the Secret Water Footprint of AI Modelsnullarxiv.org#arxiv.org#2023#APR#W17#W16#research·arxiv.org·Apr 18, 2023Making AI Less “Thirsty”: Uncovering and Addressing the Secret Water Footprint of AI Models
Generative AI; Relevance to Librarians | LucideaGenerative AI can be used in libraries in databases, in the chat systems librarians use, and in cataloging.In libraries, I think we will start seeing it in databases, in the chat systems we use, and in cataloging.arxiv.org#generativeAI#arxiv.org#2023#APR#W17#W16#research·lucidea.com·Apr 16, 2023Generative AI; Relevance to Librarians | Lucidea
Interpretability in Machine LearningWhy we need to understand how our models make predictionsarxiv.org#2023#APR#W17#W16#arxiv.org#research·towardsdatascience.com·Apr 18, 2023Interpretability in Machine Learning
Navigating the Sea of ExplainabilitySetting the right course and steering responsiblyarxiv.org#arxiv.org#2023#APR#W17#W16#research·towardsdatascience.com·Apr 18, 2023Navigating the Sea of Explainability
A Brief History of Machine Learning Models ExplainabilityIf software ate the world, models will run it. But are we ready to be controlled by blackbox intelligent softwares?arxiv.org#arxiv.org#2023#APR#W17#W16#research·zelros.medium.com·Apr 18, 2023A Brief History of Machine Learning Models Explainability