What is Machine Learning?

Machine Learning is a branch of artificial intelligence (AI) that enables systems to learn and improve automatically from experience without being explicitly programmed

At SGC, we believe in combining AI insights with specialised knowledge from geologists and geophysicists to ensure precise data interpretation and better identification of potential mineral deposits. Ensuring the accuracy and reliability of AI models is crucial and requires continuous refinement. AI complements, rather than replaces, traditional geological expertise, creating a synergy that enhances sustainable mineral exploration. Demystifying AI involves recognising its role as a tool that empowers professionals to collaborate more effectively, innovate, and responsibly utilise Earth’s resources.

Improve efficiency and accuracy in mineral exploration:

  • Data Analysis: AI algorithms excel at processing large amounts of data, including geological surveys, satellite imagery, and historical exploration data. Through machine learning models, AI can identify patterns, anomalies, and potential mineral deposits that might have been overlooked by traditional exploration methods.
  • Targeted Exploration: AI can identify areas with a higher likelihood of containing specific minerals. This targeted approach minimises exploration costs and reduces environmental impact by focusing efforts on high-potential sites.
  • Optimisation: AI-powered tools streamline workflows, accelerating the process of analysing geological data and reducing the time required for exploration. This efficiency saves costs and enables quicker decision-making in identifying viable mining sites.

Left: Geology Map Right: Geology Map using artificial intelligence (AI) image being edited


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In agriculture and the environment:

  • Identification of Suitable Locations: AI can analyse soil, climate, and topography data to identify the most suitable locations for cultivating different agricultural crops, optimising productivity and sustainability.

  • Predictive Analysis and Agricultural Planning: Using satellite, meteorological, and historical cultivation data, AI can forecast crop yields, identify potential pests and diseases, and suggest the best times and locations for planting. This helps farmers make informed decisions and plan their agricultural activities more efficiently.

  • Soil Monitoring and Management: By continuously analysing remote sensing and field data, AI can detect changes in soil composition and quality caused by agricultural practices, enabling more effective management and the implementation of corrective measures when necessary.

  • Environmental Sustainability: AI can help identify areas that need conservation and recovery, promoting agricultural practices that preserve natural resources and reduce environmental impact.

Contact SGC to find out more.