A research hub set to open next year at the Johns Hopkins Applied Physics Laboratory aims to bring generative AI into defense wargaming. The GenWar Lab will focus on upgrading traditional tabletop exercises by pairing human participants with large language models such as those behind common AI chatbots.
Project leaders say the technology will give players a chance to test ideas at a pace that traditional setups cannot match. During a game, participants will be able to call on AI assistants to evaluate options, propose actions, or even play the role of advisers and rival commanders. The system is structured to let users run quick variations of an event, then rewind and try again if they want to explore a different path.
Kevin Mather, who oversees the GenWar effort, noted that sponsors are increasingly asking for faster and more flexible ways to run these exercises. He noted that AI can support deeper analysis, including the chance to fold in modeling and simulation tools that are typically too slow or complex to use on the fly.
Tabletop wargames have long relied on human adjudication, a practice that traces back to 19th-century “kriegsspiel” drills in Prussia. These games usually pit Blue and Red teams against one another under the supervision of an umpire. Although effective for training, they take time to build and are difficult to replay, which limits opportunities to capture lessons or test alternative strategies.
With AI, if a proposed tactic is deemed unrealistic, an analyst can rewind the session and try again without rebuilding the scenario. To support this process, the GenWar team is creating a suite of tools. GenWar TTX builds the digital setting and the AI assistants. GenWar Sim, which uses the government’s AFSIM framework, lets players speak in normal language while the system converts their instructions into actions inside physics-based systems.
There is still concern about how well computer opponents can perform. Mather acknowledged that the AI is not expected to make perfect choices, only decisions that are believable enough to support training and let players explore multiple paths.
Experts outside the program see promise but urge caution. They warn of relying too heavily on the output of a single model and note that most general-purpose systems are not rigorously tested for strategic or policy use. The challenge, they say, is to expand AI’s role while documenting its limits to prevent common analytical errors.
As more tech advances are debuted by entities like D-Wave Quantum Inc. (NYSE: QBTS), we are likely to see those solutions adapted by various industries, not just the defense sector.
NOTE TO INVESTORS: The latest news and updates relating to D-Wave Quantum Inc. (NYSE: QBTS) are available in the company’s newsroom at https://ibn.fm/QBTS
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