- Darpa collaborates with USGS for using AI in critical mineral analysis
- It announced two challenges namely Mapgeoreferencing Channel & Map Feature Extraction Challenge.
- First three winners of the challenge will get exciting rewards.
DARPA has launched a competition to find artificial intelligence solutions that can aid in the sourcing of key minerals.
Critical minerals are non-fuel raw resources that are required for the production of products that are critical to national security.
DARPA is collaborating with the US Geological Survey (USGS) to investigate how machine learning and artificial intelligence (AI) might speed up important mineral analyses.
“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.”
According to DARPA, assessing the current list of 50 key minerals is time-consuming and insufficient to fulfil 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.”
First place in each of the challenges will get $10,000. Second place will receive $3,000 in prize money. Third place will receive $1,000.
While the benefits aren’t big for the AI sector, they’re a nice bonus, and participants may take pride in helping to initiatives that have the potential to make a meaningful difference.
The map georeferencing challenge registration is now open. The map feature extraction challenge registration opens on August 29th.
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