FY 2020 Navy Artificial Intelligence Investments
Published: April 04, 2019
The Department of the Navy is driving up their proposed spending on Artificial Intelligence in their fiscal year (FY) 2020 budget.
The Department of Defense and the component military departments have been early pursuers of Artificial Intelligence (AI), machine learning (ML) and other automation solutions through their Research, Development, Testing, and Evaluation (RDT&E) budgets, R&D for short. The Department of the Navy, which includes the U.S. Marine Corps, has been increasingly pursuing the advancement of these and related technologies to increase warfighting capabilities, stretch manpower capacities and increase efficiencies.
Artificial Intelligence and Machine Learning in the Navy R&D Budget
The Department of the Navy is proposing to spend more than $900M in FY 2020 research dollars aimed at AI/ML efforts, which is up more than $113M from what they are budgeting for FY 2019 and more than $230M more than FY 2018.
Several of the programs in the FY 2020 budget are new efforts, with artificial intelligence and machine learning being making up substantial percentages of the work, while the majority of the programs are continued efforts that receive funding increases in the new budget.
Navy’s Top 5 AI-Related Programs by Budget
The table below lists the five Navy programs with the largest FY 2020 budgets that have an Artificial Intelligence/Machine Learning component that we could identify in the Navy RDT&E budget requests, indicating that these efforts may likely include incremental or new work that could be available to industry if a contract for products or services is competed. The $279M represented in the table accounts for more than 30% of the identified $906M in Navy AI/ML budget shown above.
Summaries of Navy’s Top 5 AI Programs
- Surface Ship & Submarine Hull Mechanical and Electrical (HM&E) – This program supports advanced sea platforms, sea survivability, and autonomy technologies through applied research advanced analytics, machine learning and artificial intelligence. This includes research focused on scalable and robust distributed collaboration among autonomous systems; human/unmanned system collaboration; autonomous perception and intelligent decision-making; and intelligent architectures for autonomous systems.
- Mathematics, Computer, and Information Sciences – This project supports research into the mathematical foundation and computational theory and tools for design, communication, and control of intelligent autonomous systems; theory, algorithms and tools for decision support; decision theory, algorithms, and tools; and others. Efforts focus on basic research in Machine Learning, reasoning and intelligence to build intelligent and autonomous agents.
- Air, Ground, and Sea Vehicles – This programs supports ongoing advancements in sea-based aviation through research including advanced ship concepts; distributed intelligence for automated survivability; autonomous rotorcraft operations in shipboard environment; and autonomous deck operations.
- Common Picture Applied Research – This effort supports applied research on artificial intelligence in support of collaborative complex decision-making; developing artificial intelligence technologies that actively inform and assist different stages of the decision making process; developing interfaces and dialogue systems for human-machine teaming; developing agile intelligent cognitive electronic warfare algorithms and architectures; integrating artificial intelligence with robotic systems for human-machine collaboration and robot training; and predictive maintenance (digital twin) for Naval platforms.
- Electronic Warfare Technology – This program supports the development of Deep Learning methods for improved electronic warfare functions in the signal processing chain and the application of machine learning techniques to surface self-defense systems. It also supports improved modeling of sensor systems to provide integrated capability across optical and RF domain and developing test technology for affordable fielding of cognitive, collaborative Electronic warfare (EW) effector systems.
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