An employee of KGK Diamonds Botswana inspects a diamond in Gaborone, Botswana, Jan. 18, 2023. (Photo by Tshekiso Tebalo/Xinhua)
Botswana Stock Exchange (BSE) listed miner Botswana Diamonds (BOD) has adopted the use of artificial intelligence (AI) in search of new diamond discoveries.
GABORONE, April 10 (Xinhua) -- Botswana Stock Exchange (BSE) listed miner Botswana Diamonds (BOD) has adopted the use of artificial intelligence (AI) in search of new diamond discoveries.
The company's latest stakeholders update issued Tuesday said incorporating AI will assist in a "comprehensive search" for new diamond deposits and potentially other minerals.
"Our mineral database in Botswana is simply vast, too big for timely analysis by humans," said BOD Chairman John Teeling, saying that the company's database consists of 95,000 sq km of data, 375,000 km airborne geophysical data, 606 ground geophysical surveys, 228,000 soil sample results, 32,000 drill hole logs, totaling 380 gigabytes of data and 260,000 files.
He said the massive databases are suited to be analyzed by computer-based large data models and artificial intelligence techniques which can analyze substantial amounts of data in a short time. "We feed in the data and create the models from our existing knowledge both theoretical and factual," he said.
Trucks line up to be loaded with rocks at the Jwaneng Mine open pit, which is about 160 km southwest of Gaborone, Botswana, May 11, 2023. (Photo by Tshekiso Tebalo/Xinhua)
BOD will utilize Planetary AI Ltd Xplore mineral prospectivity technology which was developed in collaboration with International Geoscience Services Limited, a system that uses a unique combination of semantic technology with machine learning.
Semantic technology is a branch of artificial intelligence focused on understanding and representing the meaning of data, information, and knowledge in a machine-readable format.
Teeling said the system acts much like a geologist but can function quicker and more efficiently. Vast datasets are processed through AI that finds logical gaps in the data and learns to correct them.
"This exercise is expected to yield fresh insights that will offer drillable targets previously unseen," said Teeling. ■
