DARPA & USGS explore machine learning and AI to accelerate critical mineral assessments

News Analysis

16

Aug

2022

DARPA & USGS explore machine learning and AI to accelerate critical mineral assessments

The project aims to speed up the assessment of the nation’s critical mineral resources by automating key steps in the process.

The US Defense Advanced Research Projects Agency (DARPA) has partnered with the US Geological Survey (USGS) to explore the potential for machine learning and artificial intelligence tools and techniques to accelerate critical mineral assessments.  As part of the study, the two partners, in collaboration with MITRE and NASA’s Jet Propulsion Laboratory, have launched the AI for Critical Mineral Assessment Competition.  This competition invites innovative solutions for automatically extracting and georeferencing features from scanned or raster maps.  More information can be found here

The rationale for the project is that current assessments are labour intensive and that, using traditional techniques, assessing ~50 critical minerals would take too long to address present-day supply chain needs.

While the USA mines and refines more than 50% of the 40 critical materials scrutinised in Project Blue’s Critical Materials Risk Index (CMRI), security of supply remains a key issue for industry and policymakers in the world’s largest economy given the scale of its downstream manufacturing and end-use markets. The Project Blue CMRI puts 22/40 of the materials scrutinised at medium- or high supply risk for the USA.

In 2018, the US Government published a list of 35 mineral commodities considered critical to the economic and national security of the USA. This was followed, in 2021, by the US Department of Interior publishing a Strategy to Support Domestic Critical Mineral and Material Supply Chains comprised of three core pillars: diversifying supply, developing substitutes, and improving reuse and recycling.


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