US Announces AI Hackathons to Strengthen Critical Mineral Supply Chains (darpa.mil) 16
This week the White House announced a series of "AI hackathons to strengthen critical mineral supply chains," starting in February of 2024.
There's 50 critical minerals are used in everything from electric motors and generators to the fuselage and wings of an airplane. So now the "Critical Mineral Assessments with AI Support" contest aims to "significantly speed up the assessment of the nation's critical mineral resources by automating key steps" using AI and machine learning tools, according to a DARPA announcement on X, pointing to details on a new DARPA web page: Clean energy infrastructure, along with many other next-generation technologies, consume more critical minerals than traditional energy sources, and expected demand for critical minerals used in clean energy will quadruple by 2040... The goal of this AI exploration effort is to transform the workflow from a serial, predominantly manual, intermittently updated approach, to a highly parallel, continuous AI-assisted capability that is comprehensive in scope, efficient in scale, and generalizable across an array of applications...
The challenge is that critical mineral assessments are labor intensive and using traditional techniques, assessing all 50 critical minerals would proceed too slowly to address present-day supply chain needs. An AI-assisted workflow could enable the U.S. Geological Survey to accomplish its mission, produce high-quality derivative products from raw input data, and deliver timely assessments that reduce exploration risk and support decisions affecting the management of strategic domestic resources.
While the primary focus will be critical minerals, it is expected that the resulting technologies and resulting data products will be valuable for a wide variety of U.S. government mission areas ranging from water resource management, to potential new clean energy sources.
It all started back in 2022, when the resource-identifying U.S. Geological Survey acknowledged that "The U.S. is under-mapped." They'd hoped an online contest could close the gap — with a first prize of $10,000 (with $3,000 and $1,000 for the second- and third-place winner). Working with NASA's Jet Propulsion Laboratory and the government-supporting research nonprofit MITRE, DARPA and the U.S. Geological Survey all teamed up for the big "AI for Critical Mineral Assessment" competition.
Participants were given images of maps from somewhere in North America — along with a list of points without their latitude-longitude coordinates (just a pair of numbers indicating their position within that image). They'd have to find a way to automate the determination of real-world latitudes and longitudes. The contest recommended using other features on the map as reference points — like roads, streams, and elevation-indicating topographic lines, as well as government boundary lines (and the names of places on the map). And last December during the awards ceremony a DARPA official said they were "really really pleased at the response we got."
The new 2024 AI hackathons are now intended to build on the challenges from that 2022 competition. One competitor had described it as a "well-organized competition, really engaging," adding "I think the complexity of the maps that were part of the data set just made it a really interesting and engaging kind of problem."
They noted that in the past we've always indicated data with maps — but that now, we're trying to turn maps back into data...
There's 50 critical minerals are used in everything from electric motors and generators to the fuselage and wings of an airplane. So now the "Critical Mineral Assessments with AI Support" contest aims to "significantly speed up the assessment of the nation's critical mineral resources by automating key steps" using AI and machine learning tools, according to a DARPA announcement on X, pointing to details on a new DARPA web page: Clean energy infrastructure, along with many other next-generation technologies, consume more critical minerals than traditional energy sources, and expected demand for critical minerals used in clean energy will quadruple by 2040... The goal of this AI exploration effort is to transform the workflow from a serial, predominantly manual, intermittently updated approach, to a highly parallel, continuous AI-assisted capability that is comprehensive in scope, efficient in scale, and generalizable across an array of applications...
The challenge is that critical mineral assessments are labor intensive and using traditional techniques, assessing all 50 critical minerals would proceed too slowly to address present-day supply chain needs. An AI-assisted workflow could enable the U.S. Geological Survey to accomplish its mission, produce high-quality derivative products from raw input data, and deliver timely assessments that reduce exploration risk and support decisions affecting the management of strategic domestic resources.
While the primary focus will be critical minerals, it is expected that the resulting technologies and resulting data products will be valuable for a wide variety of U.S. government mission areas ranging from water resource management, to potential new clean energy sources.
It all started back in 2022, when the resource-identifying U.S. Geological Survey acknowledged that "The U.S. is under-mapped." They'd hoped an online contest could close the gap — with a first prize of $10,000 (with $3,000 and $1,000 for the second- and third-place winner). Working with NASA's Jet Propulsion Laboratory and the government-supporting research nonprofit MITRE, DARPA and the U.S. Geological Survey all teamed up for the big "AI for Critical Mineral Assessment" competition.
Participants were given images of maps from somewhere in North America — along with a list of points without their latitude-longitude coordinates (just a pair of numbers indicating their position within that image). They'd have to find a way to automate the determination of real-world latitudes and longitudes. The contest recommended using other features on the map as reference points — like roads, streams, and elevation-indicating topographic lines, as well as government boundary lines (and the names of places on the map). And last December during the awards ceremony a DARPA official said they were "really really pleased at the response we got."
The new 2024 AI hackathons are now intended to build on the challenges from that 2022 competition. One competitor had described it as a "well-organized competition, really engaging," adding "I think the complexity of the maps that were part of the data set just made it a really interesting and engaging kind of problem."
They noted that in the past we've always indicated data with maps — but that now, we're trying to turn maps back into data...
AI = Algorithm = Series of Equations (Score:3, Informative)
Oh FFS. (Score:3)
Re: (Score:2)
then fucking do it
"Doing it" requires knowing what to do, which means knowing where to dig. That's exactly what this project is designed to do.
AI can also identify new materials that can reduce or eliminate the need for rare earths in many applications. A new material for magnets or battery cathodes that uses half as much dysprosium or cobalt is just as good as doubling production.
and stop wasting further money on thinking
My grandpa once told me that if I have two hours to chop down a tree, I should spend the first hour sharpening my ax.
He also taught me that "PPPPP
Re: (Score:2)
"That's exactly what this project is designed to do."
No, that's what the surficial mineralogy project is supposed to do. And let me tell you - AI isn't going to tell you shit about what's underground. Core drilling and prospecting will.
I do satellite imagery volunteer work for the USGS - AI isn't going to help much there, either. It might help make figuring out if a reading is iron or silica a bit faster, but that's about it.
This is a waste of time and money.
Re: (Score:2)
Be careful what you ask for. (Score:1)
This is how nameless, faceless wars get started against some omnipresent entity.
It's also how the fucking things last for decades.
Previous challenge description (Score:2)
Stop with the buzzwords and meetings, if you want to improve our supply chain then fucking do it and stop wasting further money on thinking about and maybe doing it someday.
Reading through the previous challenge details [darpa.mil], it seems that the USGS has a fuckton of survey maps made by innumerable entities (people, stake holders, companies) in innumerable formats, and were looking to:
a) Georeference the maps, by extracting the lat/lon information printed on the maps (in various formats), and
b) Extract feature polygons from the survey maps.
(Note that this was the previous competition, held in 2022, and awarded monetary prized to the winners.)
This looks exactly like the sort of proble
Re: (Score:2)
Stop with the buzzwords and meetings, if you want to improve our supply chain then fucking do it and stop wasting further money on thinking about and maybe doing it someday.
That's the US government for you. ALL TALK and NO DIG.
Re: (Score:2)
The challenge will be ... (Score:2)
Re: (Score:2)
Federal laws can overrule the NIMBYs, as they did with the Mountain Pass rare earth mine [wikipedia.org] which is reopening over the objections of California's brainless greenies.
"The needs of the many outweigh the needs of the few." -- Spock
Disclaimer: I am a greenie, but not the brainless type.
Hack oppressive governments (Score:2)
Probably the best strategy to strengthen critical mineral supply chains is to hack oppressive dictatorships into liberal democracies.
WTF will "AI" do for that? (Score:2)
Hallucinate that there is no problem or what?
Re: (Score:2)
It's a hackathon! They'll do some, uh, hacking! Problem solved.