President Donald Trump has said the US Navy is clearing Iranian mines from the ​strait, a vital sea route for oil shipments, whose disruption is increasingly threatening the global ​economy. Sweeping for underwater explosives could take months despite a tenuous ceasefire between the US and Iran in their weeks-long war.

The up to $100 million contract for the San Francisco artificial intelligence company ​Domino Data Lab could quicken this process with software that can teach underwater drones to identify new ​types of mines in a matter of days.

“Mine-hunting used to be a job for ships,” Thomas Robinson, Domino’s chief operating officer, said in an interview with Reuters. “It’s becoming a job for AI. The Navy is paying for the platform ​that lets it train, govern, and field that AI at a speed required for contested waters ​that block global trade and imperil sailors.”

Last week, the US Navy awarded the up to $99.7 million contract to expand ‌Domino’s role ⁠as the AI backbone of the Navy’s Project AMMO - Accelerated Machine Learning for Maritime Operations - a program to make underwater mine detection faster, more accurate, and less dependent on human sailors.

The software integrates data from multiple sensor types, including side-scan sonar and visual imaging systems, and allows the Navy to monitor ​how well various AI ​detection models are performing ⁠in the field, identify failures, and push corrections to improve performance.

The core of Domino’s pitch - and the Navy’s wager - is speed. Before the company’s involvement, ​updating the AI models that power the Navy’s unmanned underwater vehicles (UUVs) to recognise ​new or ⁠previously unseen mines could take up to six months. Domino says it has cut that cycle to days.

Robinson illustrated the relevance to the Middle East crisis: “If there were UUVs in the Baltic Sea trained on Russian ⁠mines, ​and then they needed to be deployed to the Strait ​of Hormuz to detect Iranian mines, with Domino’s technology, the Navy could be ready in a week rather than a year.”