Cobalt Metals is applying modern data science to the traditional field of mineral exploration. By aggregating vast, disparate datasets (both structured and unstructured) and using proprietary AI/ML models, they aim to increase the probability of discovering high-quality ore deposits.
The global shift towards electrification, batteries, and AI is creating unprecedented demand for specific minerals. The speaker highlights that the next 25 years will require more copper than has ever been mined, and lithium production needs to increase tenfold to meet demand.
The speaker reframes mineral exploration not as a problem of resource scarcity, but of information scarcity. The core challenge is not a lack of minerals in the Earth's crust, but a lack of precise information about where high-concentration deposits are located, which is what their data-centric approach is designed to solve.
While the success rate of exploration is historically low, the financial returns on a successful discovery are extraordinary, potentially 100 to 1,000 times the initial investment. Once a deposit is found, its value can be calculated with relative certainty based on ore grade, size, and commodity prices.
The company emphasizes a symbiotic relationship between geologists (human intelligence, HI) and AI. AI models provide predictions and quantify uncertainty, while geologists provide domain expertise, make hypotheses, and collect new data in the field, which in turn retrains the models daily.
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