The US Navy and Defence Innovation Unit (DIU) announced on Monday (17 June) that it had developed new AI infrastructure to support the detection of underwater targets. 

In 2022, the US Navy partnered with the DIU to address concerns that machine learning (ML) models were inaccurate and slow to adapt to enemy attacks or changing environments.

Two years ago, the DIU identified five commercial machine learning operations (MLOps) vendors that could collectively provide a pipeline to track, modify and redeploy ML algorithms for underwater target threat detection. 

The five commercial MLOps, including Arize AI and Domino Data Lab, were awarded prototype agreements in 2022. 

Each vendor contributed an essential component of the overall capability which laid the foundation for the US Navy’s ML developers to focus on the development and refinement of the new AI infrastructure.

In April 2024, each vendor successfully prototyped and deployed their portion of the MLOps pipeline. 

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By utilising commercial vendors, the DIU found that the time needed for ML model updates decreased from six months to just a few days, according to a DIU blog post.

As stated by Commander Eli Ford, Principal Assistant Program Manager, the “new models were trained against an expanded threat environment” to ensure that they could “adapt and evolve at the speed of tactical relevance”.

The five vendors are now in the process of receiving production contracts. The Navy is currently in the process of expanding the use of this new AI infrastructure across the US Department of Defence and other naval missions.

Commander Shaun Lieb stated that the success of Project AMMO has improved the US Navy’s “ability to detect targets of interest in a complex and dynamic undersea environment”.

US Marines Corps major Nick Ksiazek stated that the Navy were also testing ML algorithms that use sonar sensors to detect underwater target, according to Bloomberg.

This will be a significant step in the DoD’s efforts to integrate AI technology into its military operations, Ksiazek added.