“These things are hard to tip over,” geologist Wilson Bonner assures me as the four-wheeled off-road vehicle he’s driving suddenly tips sideways, throwing me toward the churned-up mud beneath our wheels. On a chilly fall day, we drive up the side of a densely wooded hillside in rural Ontario, Canada, on our way to a place that, according to Bonner’s employer, startup KoBold Metals, represents the marriage of advanced artificial intelligence with one of the oldest industries.
Indeed, we complete the half-hour trek relatively unmuddy, eventually breaking through a ring of broken trees and mutilated undergrowth into a swath of flattened mud. A black pipe about as wide as my arm protrudes from the ground—the top end of a half-mile-deep hole punched into the ground by a truck-sized oil rig standing idly nearby. It’s not much to look at, but this gap could represent a step into the future of mining, an industry critical to the world’s transition to renewable energy.
As the world begins to shift uneasily from fossil fuels to greener alternatives, there is an increasing global scramble to find the vast amounts of cobalt, lithium and other metals needed to build all the electric car batteries, solar panels and wind turbines we need. need to build. But finding new mineral deposits has always been difficult and expensive, and it’s only getting worse. Most of the world’s easy-to-discover reserves are already being tapped. Those that remain are usually in remote locations and deep underground. Miners generally say that only 1 in 100 exploratory boreholes turn up anything.
KoBold Metals, a four-year-old startup, is one of the few companies trying to make the process faster, cheaper and more efficient by applying artificial intelligence. KoBold has built a massive database containing all the information it can find about the Earth’s crust – the equivalent of 30 million pages of geologic reports, soil samples, satellite images, academic research papers and centuries-old handwritten field reports. A team of data scientists is converting all this disparate information into something machine-readable, for example by scanning written reports with optical character reading software, or by standardizing geophysical information captured in various digital formats.
All of this is guided by machine-learning algorithms that identify patterns in the geology and other features of places where metals have been found in the past. The algorithms can then be unleashed on the entire database to find promising locations with similar patterns that have not yet been explored, spewing out a series of maps showing where the target metals are likely to be found.
Backed by investors including venture firm Andreessen Horowitz and Bill Gates’ Breakthrough Energy Ventures, KoBold’s first exploration teams got underway last summer, prospecting in areas of Zambia, Greenland and Canada, including the Ontario site at Crystal Lake.
KoBold is looking for copper, cobalt, nickel, lithium and rare earth metals – the key ingredients of batteries for electric cars and other renewable energy technologies. The International Energy Agency predicts that demand for all of these metals will quadruple by 2050 and that demand for some metals, such as cobalt and nickel, will increase by up to 40 times. All told, the agency estimates that the collective market for minerals needed for “clean energy technologies” — everything from renewables to batteries and power grids — will grow more than fivefold by 2050 to about $400 billion.