AI trained on reams of geological data can indicate where to dig in search of metals crucial to electric cars and other green technology.
“We’re looking to expand and diversify the supply of these metals all over the world, but we're taking a totally different approach” from conventional mining companies, KoBold founder Kurt House tells me via Zoom from his home in Northern California. “Two-thirds of our team are software engineers or data scientists who have never worked a day of exploration in their life. The other third are experienced explorers.
While most AI exploration companies sell their services to mining outfits, KoBold aims to take part in the actual extraction operations. It currently holds the exploration rights to thousands of square miles of land around the world, and it has struck deals with some of the world’s largest mining companies, including BHP and Rio Tinto.
“KoBold is doing the riskiest thing,” says Sam Cantor, head of product at Minerva Intelligence, another AI-driven mining exploration startup. Even with help from AI, placing bets on potential mineral deposits is far from a foolproof process; metals often turn up in places with wildly different conditions and geologic histories. “When you’re training an algorithm to recognize a face, you can assume there’s a mouth and it’s below the nose and eyes,” Cantor says.
Copper and nickel were previously found at the Crystal Lake site KoBold is now exploring back in the 1970s, but not in high enough concentrations to make mining profitable. The startup’s algorithms, however, suggested there may be more there. So the company sent in a team of geologists and technicians, headed by Bonner, to gather more data.
Once again, KoBold turned to algorithms. Finding out exactly what’s underground requires drilling, but that is time-consuming and expensive, and it requires tearing up land, all of which KoBold would like to keep to a minimum.
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