DARPA seeks AI solutions for sourcing critical minerals

DARPA has launched a competition to find AI solutions that can help with sourcing critical minerals.

Critical minerals are raw, non-fuel materials that are vital for manufacturing products that are essential to national security.

DARPA is teaming up with the US Geological Survey (USGS) to explore how machine learning and AI can accelerate critical mineral assessments.

“The USGS’s critical mineral resource assessments are at the heart of our domestic supply and production of critical minerals,” said Dr Anne Fischer, Deputy Director of DARPA’s Defense Sciences Office.

“We want to have a measurable, immediate impact on the USGS’s ability to reach some of its objectives, especially in ways that are critical to national security.”

DARPA says that assessing the current list of 50 critical minerals is labour-intensive and takes too long to meet today’s supply chain needs.

The AI competition will include two challenges:

  • Map Georeferencing Challenge: Participants will receive a dataset of 1,000 or more maps of various types for training and validating models with the goal of fitting coordinate points that can be referenced to known locations in one or more base maps.
  • Map Feature Extraction Challenge: Participants will be provided with a training set consisting of maps with each legend item labelled and characterised (as point, line, or polygon) and a binary pixel map reflecting the feature’s coverage in the map. The goal of the challenge is to identify all features in a map that appear in the map’s legend.

“DARPA is known for fostering innovation by creating problem-focused research communities, and we’re excited to put the results of this competition to immediate use,” said Sarah Ryker, associate director for energy and mineral resources at the USGS.

“The United States is under-mapped, and the Bipartisan Infrastructure Law provides a historic opportunity to catch up – if we can precisely target our investments in new mapping. We hope that new capabilities emerging from these challenges will enable us to do exactly that.”

For each of the challenges, $10,000 will be awarded for first place. Second place will take home $3,000. $1,000 will be awarded for third place.

While the rewards on offer aren’t huge for the AI industry, they’re a nice bonus and participants can take pride in contributing to projects that could make a real difference.

Registration for the map georeferencing challenge is now open. Registration for the map feature extraction challenge opens on 29th August.

You can find out more information and register for the challenges here.

(Photo by Elena Mozhvilo on Unsplash)

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Tags: ai, artificial intelligence, competition, critical minerals, darpa, machine learning, us geological survey, usgs

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