No PriorsNo Priors Ep. 111 | With KoBold Metals Co-Founder and President Josh Goldman
At a glance
WHAT IT’S REALLY ABOUT
AI-Powered Mineral Exploration Reshapes Global Supply of Copper and Lithium
- Josh Goldman, co-founder and president of KoBold Metals, explains how the company uses AI, novel sensors, and massive geoscience datasets to dramatically improve the success rate of mineral exploration. Rather than operating mines, KoBold focuses on the high-upside, high-failure exploration phase, treating discovery as an information and prediction problem. The conversation covers KoBold’s large global portfolio, its world-class Mingomba copper discovery in Zambia, its custom technology stack, and its philosophy-driven approach to uncertainty and scientific method. Goldman also situates these efforts within the macro need to supply metals for batteries, electrification, and AI-driven data center growth.
IDEAS WORTH REMEMBERING
5 ideasTreat mineral exploration as an information problem, not a resource problem.
The Earth has abundant lithium and copper; the real scarcity is reliable information about where economically viable, highly concentrated deposits are located. KoBold’s business centers on improving prediction quality to reduce uncertainty and exploration failures.
Focus on exploration can yield outsized returns compared to mining operations.
With a few million dollars, a successful discovery can create 100–1000x returns, whereas operational mining is more commoditized. KoBold targets $50–$100 million of exploration spend per major discovery, versus an industry that now often spends $1 billion for less than one high-quality find.
Combine diverse, messy datasets to gain predictive power, rather than betting on a single “silver bullet” technology.
KoBold integrates satellite imagery, airborne surveys, rock and soil samples, historical maps, regulatory filings, and text reports into a unified data system. Their advantage comes from high-dimensional data fusion and uncertainty-aware models, not from any one special dataset or sensor.
Use fieldwork to actively retrain models by targeting uncertainty, not confirmation.
Geologists are directed to locations where models are least certain, collect new ground-truth data, and feed it back daily. This continuous loop between human experts and machine learning systematically sharpens predictions about surface and subsurface geology.
High-grade deposits drastically improve economics and environmental footprint.
Mingomba’s core is over 5% copper versus the global average of ~0.6%. For the same copper output, a 10x higher grade means roughly 10x less rock moved, lower capital and operating costs, and a smaller environmental impact—key to being a low-cost producer in a commodity market.
WORDS WORTH SAVING
5 quotesWe talk about exploration as an information problem because the scarce resource is not lithium or copper metal in the ground. The scarce resource is the information about where the ore deposits are located.
— Josh Goldman
In a commodity business, everybody sells copper for the same price. Our ability to make money depends on what our margin is, which means we need to be a low-cost producer.
— Josh Goldman
There is no way to isolate the AI from the HI. There is no way to isolate one piece of data that's uniquely powerful.
— Josh Goldman
Cobalt is kind of an epistemic project really. Our business is about making better predictions.
— Josh Goldman
To build a future that is powered by batteries and AI, by mid-century we will need to mine, over the next 25 years, more copper than has been mined so far in all of human history.
— Josh Goldman
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