According to the International Energy Forum, somewhere between 35 and 194 new mines will be needed by 2050. These new mines aren’t your typical small-town coal mines but instead major digs related to rare earth metals. In essence, that equates to between one to six new mines a year in order to keep pace with technology and energy demands. Understanding that few new mines have been opened in the U.S. over the decades, this is a major challenge. The science behind identifying geographic locations where these metals may be hiding has not kept pace with the times. But that looks to be changing with the innovative use of AI in mining exploration. An AI model for rare earth mining is currently being put to the test. And thus far, the results look to be quite promising.
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One new company, KoBold Metals, recently made a major breakthrough using AI in mining exploration. Using advanced scientific methods, the company located a massive copper deposit deep beneath the surface in Zambia. Given the need for copper and other rare earth metals, the discovery was met with profound excitement. But in reality, such finds need to be occurring several times a year to keep pace with rare earth metal needs. The hope is that this new AI model for rare earth mining paves the way for a boom in these resources. In this regard, AI could potentially represent both a supplier and demand consumer for these metals. With the billions of dollars pouring into these efforts, it’s clear that a solution is needed. And many believe AI will play a large part in that.
The AI Model for Rare Earth Mining
Unlike traditional mining exploration, KoBold has taken a much different approach. A key part of that approach involves a gadget that was developed by scientists trying to identify dark matter. When such efforts proved to be unfruitful, these same technologies were considered for other uses. And one of those uses involved identifying and locating rare earth metals. In essence, after routine research narrows down potential sites, a hole is drilled sometimes well below the earth’s surface. The technology is then used to identify tiny subatomic particles and related density readings that profile key metals. These metals include copper, lithium, cobalt, and nickel. And the use of AI in mining exploration projects like this plays a huge role.
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Interestingly enough, the science behind this AI model for rare earth mining has been used in some rather odd scenarios. For example, it has been used to locate ancient Egyptian burial chambers. It has also been used to reveal underground tunnels that might serve as a means to unauthorized border crossings. But its use with AI in mining exploration is new, and it’s proving to have significant potential. KoBold is leading the way in using this technology, and as such, it is receiving tremendous support financially. Not only is this support coming from venture capitalists from all over the world. But it’s also coming from governments including the U.S. If this AI model for rare earth mining can consistently provide results, it will definitely change mining forever.
KoBold’s Approach to AI-Enhanced Mining
For KoBold, the company began operations about 5 years prior. Notably, it recognized the potential for AI in mining exploration early. But that doesn’t mean other mining exploration practices were aborted. Instead, these were used to complement its AI model for rare earth mining. For instance, Cessna planes are still used to investigate potential metal deposits beneath the surface using radar and magnetic readings. Likewise, historical research and ground sampling are also routinely used. All of this information as well as AI drilling data is combined to create KoBold’s Terrashed. This is its 3D model that’s combined tens of millions of documents and datapoints to assist with metal discoveries. Naturally, AI has enabled Terrashed to advance dramatically.
In terms of operations, KoBold is also placing its money where its mouth is. In the recent Zambia discovery, it is estimated that over 300,000 tons of copper may exist down below. KoBold has about $2.3 billion invested into this mine already and controls a significant percentage of ownership. At the same time, KoBold has received tremendous funding from private equity in the U.S. and Europe. And government support for the company is also profound. The U.S. has committed to building a railway in Zambia to facilitate copper exporting for KoBold. And KoBold continues to negotiate with Zambia about percentage rights to the mine. Assuming KoBold’s AI model for rare earth mining continues to shine, the company will do very well. It already has about 60 mining projects in progress with AI in mining exploration fueling future ones as well.
Necessity as the Mother of Invention
One might say that KoBold’s AI model for rare earth mining just happened to come along at the right time. But it’s more like a chicken and egg dilemma. While AI in mining exploration is likely to be a tremendous advancement, it’s also part of the problem. The energy demands of AI are incredible, and rare earth metals are needed to assist with developing energy solutions. In addition to their essential role in consumer goods, rare earth metals are also part of power grid solutions. Massive battery storage facilities are needed the size of buildings to store wind and solar energies. And a large amount of rare earth metals will be required to achieve this. At the same time, advanced weaponries also require these resources in large quantities. Indeed, AI mining advances are proving to be timely, but they have indeed helped fuel the rising demand.
Assuming KoBold’s copper discovery in Zambia can be effectively mined, it will provide billions of dollars a year. These revenues will also persist for decades according to projections. But this is just a single mine for a single rare earth metal. Many more will be needed, and the use of AI in mining exploration can hopefully fill this void. Preliminary evidence from KoBold’s AI model for rare earth mining and its copper discovery supports this potential. And this breakthrough couldn’t come at a better time.
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