Spent a day talking artificial intelligence with the British Geological Survey in Nottingham this week. Fascinating to hear the projects already being undertaken and opportunities to apply new techniques.They hold over 15,000 cores from onshore boreholes, as well as core from just about every oil & gas well ever drilled offshore in the UK. An... Continue Reading →

Interesting article on AI ethics. Is it ethical for AI to be hosted to the international scientific community from a legal jurisdiction that will not allow questions or outputs that tarnish the image of that particular government or its policies? With the blessing and legitimacy of a prestigious international scientific body?Local laws must be respected.... Continue Reading →

Gave a talk today on Artificial Intelligence to the UK Government Department for Environment, Food and Rural Affairs (DEFRA). A focus on Natural Language Processing, Large Language Models and Machine Vision in the Geological Sciences.Areas I covered for these techniques included: geology, palaeontology, outreach and education, geotourism, hydrogeology, hydrology, environmental contamination and pollution, geohazards -... Continue Reading →

Delighted to be appointed Chair of the Artificial Intelligence Ethics Task Group of the International Union of Geological Sciences (IUGS) Commission on Geoethics. We will be working towards a white paper as a guiding document for the Union.

Using AI to describe fossils. I've been experimenting with GPT-4o to see how well it can describe fossils from smartphone photographs. At a high level it seems to perform reasonably well given most fossils found are not complete specimens.In my unscientific experiment using 10 commonly found fossils from the Jurassic Coast in England, it was... Continue Reading →

Free open-source tools: Automated petrographic image analysis by supervised and unsupervised machine learning methods. Interesting paper from Azzam, Blaise and Brigaud (2024).“We present two novel software tools: GrainSight, which utilizes a supervised deep learning model (FastSAM) for automated grain detection and morphological characterization; and PetroSeg, which employs an unsupervised segmentation approach to explore rock properties... Continue Reading →

I've been experimenting taking a large volume of text, building embeddings and using PCA for dimensionality reduction. These data can be an input for clustering e.g. k-means. In this example I've used thousands of minerals and lithologies. I've highlighted some of the associations to illustrate. Where there are associations (complex word association co-occurrence) that are... Continue Reading →

Some great work at Queen Mary University of London by Cedric John and Harriet Dawson using machine vision to automatically detect skeletal components in carbonates."The subsurface is a fantastic resource to store and extract freshwater, clean hydrogen fuel, store carbon emissions, or even extract heat from geothermal energy. But to do this requires a meticulous... Continue Reading →