In data, we trust – navigating through the age of AI in the mining industry

The Australasian Institute of Mining and Metallurgy
R Ch ramhan M Pyle G Lane
Organization:
The Australasian Institute of Mining and Metallurgy
Pages:
6
File Size:
1066 KB
Publication Date:
Sep 1, 2024

Abstract

Data is the most valuable commodity in the information age. The use of data enables productivity, opportunity, and safety in various sectors and industries. In the late 1950s, Alan Turing coined the term artificial intelligence (AI) to describe the ability of computing machines to think and behave like humans through simplified reasoning and logic (Turing, 1950). This concept of mimicking human behaviour is the building block of machine learning algorithms used in most AI software. The ‘learning’ aspect in machine learning requires data, that is, information on the environment or the objective, to be modelled or predicted using AI. An AI-enabled system aims to predict the unknown faster and intuitively. Intuition in software algorithms can be described as probabilistic, learned through the data that the AI system is trained on; indeed, the AI software cannot predict the future, but it can provide the likelihood of an event/action occurring, thereby enabling decisions or responses to prevent it or take action. Just as various industries have adopted AI as the tool of choice to seek new opportunities (examples: medical research, self-driving cars, financial modelling), the mining industry, too, has been receptive to embracing AI for problem-solving and maximising the value of its business.
Citation

APA: R Ch ramhan M Pyle G Lane  (2024)  In data, we trust – navigating through the age of AI in the mining industry

MLA: R Ch ramhan M Pyle G Lane In data, we trust – navigating through the age of AI in the mining industry. The Australasian Institute of Mining and Metallurgy, 2024.

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