Tag: artificial-intelligence

Webinar: The AuScope EarthBank ProjectBuilding Nationally Collaborative Geochemical Research Infrastructure to Enable Discovery.

Webinar: The AuScope EarthBank ProjectBuilding Nationally Collaborative Geochemical Research Infrastructure to Enable Discovery.Webinar 1st July 2025. Register link in the comments.AbstractProf Brent McInnes , AuScope EarthBank Project Director, John de Laeter Centre, Curtin University, Australia.“The AuScope EarthBank project (EarthBank project) is a $21 million national initiative to modernise Australia’s geochemistry data infrastructure and to advance... Continue Reading →

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Generating microscopic images of rocks using generative artificial intelligence

Interesting paper generating microscopic images of rocks using generative artificial intelligence (GenAI) published this week by Młynarczuk and Habrat (2025).“The generation of synthetic images can be an important element in supporting the augmentation and analysis of multimedia data. It has applications in many scientific fields. Also, in geological and mining sciences.This study presents generative artificial... Continue Reading →

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Open-access global geomagnetism

Upgrade to open-access global geomagnetism GIS portal operated by the British Geological Survey (BGS).“The World Data Centre (WDC) for Geomagnetism, based in Edinburgh, was established in 1966 and is operated by BGS. Its mission is to collate, store and distribute data (and associated metadata) from observations of the Earth’s magnetic field.As part of this mission,... Continue Reading →

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AI and Planetary Impact

AI and Planetary Impact: The Business of Saving the Planet. Insightful event today staged by John Hopkins University. How the rapid rise of AI technologies is influencing climate action, environmental sustainability, and wildlife conservation. Session included:Kate Brandt - Chief Sustainability Officer at GoogleDiego Saez Gil - CEO of PachamaMalaika Vaz - National Geographic ExplorerJerry Burgess - Director of the... Continue Reading →

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Automatic description of rock thin sections: A web application Open-source

Open-source: Automatic description of rock thin sections: A web application. Delighted to share Stalyn Paucar and colleagues work from Ecuador (Universidad Central del Ecuador) published this week.AbstractThe identification and characterization of rock types is a core activity in geology and related fields, including mining, petroleum, environmental science, industry, and construction. Traditionally, this task is performed... Continue Reading →

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Concerns remain over potential for censorship and lack of openness in Deep-time Digital Earth (DDE)’s GeoGPT which it promotes in the name of the International Union of Geological Sciences (IUGS)

Screenshot Serious concerns remain over potential for censorship, lack of openness and ethics with Deep-time Digital Earth’s GeoGPT. This Artificial Intelligence (AI) is promoted to the international community by Zhejiang Lab and DDE, in the name of the International Union of Geological Sciences (IUGS).Article published in the ‘Geoscientist’ in response to 'GeoGPT: An Update' by Ludden and... Continue Reading →

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Large Language Models: Due to the risks, NASA decides against fine tuning a generative earth science LLM.

Large Language Models: Due to the risks, NASA decides against fine tuning a generative earth science LLM.“Based on our initial assessment, the costs and risks associated with developing an exclusive NASA Science Mission Directorate (SMD) decoder (generative) model currently outweigh the benefits.”In a paper published yesterday in the American Geophysical Union (AGU) - Perspectives of... Continue Reading →

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AI Digital Assistant for Earth Observation

ESA Φ-lab have created an AI-powered digital assistant that allows users to access and explore complex Earth Observation data through a natural language interface.“In the long term, the aim is to integrate this tool into digital twins of Earth, supporting decision-making in areas such as climate monitoring, disaster management and urban planning.A digital twin of... Continue Reading →

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Text Embeddings for Rock Classifications

I tested if we might differentiate rock types and their associations based on the patterns of words that occur around them in large archives of geological reports. Using a text embeddings model generated through the unsupervised machine learning from thousands of geological survey reports, approximately 2,000 rock type names were compared to each other. The... Continue Reading →

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