The system provides operational guidance in natural language to military personnel, advising on countermeasures to enhance response efficiency.

Researchers are also developing language model-based interfaces to assist human operators in managing multiple AI agents during complex missions.

These technological advancements threaten to undermine traditional submarine stealth strategies, impacting naval dominance, nuclear deterrence, and intelligence gathering.

Once detected, the likelihood of submarines remaining undetected drops to just 5%, allowing surface ships to engage effectively.

Future enhancements may include integrating aerial drones, surface ships, and unmanned underwater vehicles into a coordinated, multi-dimensional naval hunting network.

It integrates data from sonar, underwater noise detection, radar, and oceanographic measurements like temperature and salinity to create a comprehensive real-time underwater environment map.

The AI employs a three-layer structure—perception, decision-making, and human-machine interaction—enabling rapid, adaptive responses to underwater threats.

This development poses a challenge to the US Navy's roughly 70 nuclear submarines, which rely heavily on stealth and decoys for strategic advantage.

Chinese scientists have developed an advanced AI system capable of detecting and tracking covert submarines by analyzing data from underwater sensors, potentially ending the era of stealth submarines.

Simulations demonstrate the AI's ability to locate and track enemy submarines with about 95% accuracy, regardless of stealth tactics or decoys.

This AI-driven anti-submarine warfare system can identify even the quietest submarines with approximately 95% success, including those using decoys and evasive maneuvers.

The success rate of this AI system significantly reduces a submarine's chance of escape to around 5%, diminishing the effectiveness of conventional stealth tactics.