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Project Maven (officially Algorithmic Warfare Cross Functional Team) is a Pentagon project involving using machine learning and data fusion to process data from many sources, identify potential targets, display information through a user interface, and transmit human decisions to weapon systems, among other functions.
At the second Defense One Tech Summit in July 2017, Cukor also said that the investment in a "deliberate workflow process" was funded by the Department of through its "rapid acquisition authorities" for about "the next 36 months".
According to Lt. Gen. of the United States Air Force Jack Shanahan in November 2017, it is "designed to be that pilot project, that pathfinder, that spark that kindles the flame front of artificial intelligence across the rest of the Defense Department". Its chief, U.S. Marine Corps Col. Drew Cukor, said: "People and computers will work symbiotically to increase the ability of weapon systems to detect objects." Project Maven has been noted by allies, such as Australia's Ian Langford, for the ability to identify adversaries by harvesting data from sensors on and satellite.
In 2022, the National Geospatial-Intelligence Agency took over Project Maven.
Companies that have contributed to the data fusion include Palantir Technologies, Amazon Web Services, ECS Federal, L3Harris Technologies, Maxar Technologies, Microsoft and Sierra Nevada Corporation. The main data-fusion platform is made by Palantir. At least 21 private companies had been involved. Building the Tech Coalition: How Project Maven and the U.S. 18th Airborne Corps Operationalized Software and Artificial Intelligence for the Department of Defense. Emelia Probasco, August 2024. Center for Security and Emerging Technology
The data sources include photographs, satellite imagery, Geopositioning data (IP address, Geotagging, metadata, etc) from communications intercepts, Thermography, synthetic-aperture radar, etc. Machine learning systems, including object recognition systems, process the data and identify potential targets, such as enemy tanks or location of new military facility. The training dataset included at least 4 million images of military objects such as warships, labelled by humans. The user interface is called Maven Smart System. It could display information such as aircraft movements, logistics, locations of key personnel, locations on the no-strike list, ships, etc. Yellow-outlined boxes show potential targets. Blue-outlined boxes show friendly forces or no-strike zones. It could also transmit, directly to weapons, a human decision to fire weapons.
Beginning in 2020, Maven was used for live-fire exercises ("Scarlet Dragon exercises"). The first took place at Fort Bragg. An AI system identified a tank in satellite images, the human approved, and the AI system signaled an M142 HIMARS to strike the target (in this case, a decommissioned tank). It was the first AI-enabled artillery strike in the US army.
There are 6 steps in the kill chain: identify, locate, filter down to the lawful valid targets, prioritize, assign them to firing units, and fire. Of these 6 steps, Maven can perform 4. A senior targeting officer estimates that with Maven, he could decide on 80 targets per hour, vs 30 targets per hour without Maven. The efficiency was comparable with the targeting cell used during Operation Iraqi Freedom, but whereas the OIF used a targeting cell with roughly 2000 staff, the 18th Airborne used a targeting cell with 20 people.
In the 2022 Russian invasion of Ukraine, the US has used satellite intelligence and Maven Smart System to supply the locations of Russian equipment to Ukrainian forces.
In February 2024, Maven was used for narrowing targets for airstrikes in Iraq and Syria. It was also used for locating rocket launchers in Yemen and surface vessels in the Red Sea, some of which were destroyed in February 2024 according to CENTCOM.
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