The U.S. Navy is turning to artificial intelligence to accelerate a critical and dangerous task: clearing mines. In a significant move, the Navy has partnered with Domino Data Lab, a company specializing in AI and data science platforms. This collaboration aims to dramatically speed up the process of identifying and neutralizing underwater mines, a mission that traditionally takes months.
Domino Data Lab's Role
Thomas Robinson, Chief Operating Officer of Domino Data Lab, explained the company's contribution. Domino Data Lab provides a software platform designed to help organizations build, deploy, and manage AI models. For the Navy's mine-clearing operations, the platform will be used to analyze data collected by unmanned underwater vehicles (UUVs). These UUVs utilize sonar and other sensors to scan the seabed. The AI models process this vast amount of data to detect and identify potential mines.
Accelerating a Critical Mission
The core of Domino Data Lab's value proposition in this context is speed and accuracy. Robinson highlighted that traditional mine-clearing methods often rely on human analysis of sensor data, a process that is time-consuming and prone to human error, especially under fatigue. "
Humans get tired, you know, eight, ten hours on the job, maybe you make mistakes.
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From Commercial to Defense
Domino Data Lab has a strong track record in commercial sectors, serving clients in pharmaceuticals and financial services, where they apply AI for tasks like drug discovery and risk modeling. Robinson noted that the company's expertise in handling large, complex datasets and developing robust AI solutions is transferable to defense applications. "
We've been on business a little over 10 years and we started as a commercial technology.
" he said. "We help ten of the top 20 global pharma organizations across their entire pipeline.
" This cross-sector applicability demonstrates the versatility of advanced AI platforms.The Challenge of Underwater Mine Detection
Robinson elaborated on the complexities of mine detection. He explained that UUVs gather data from sonar, vision, and other sensors. This data stream needs to be interpreted to identify objects that are likely mines. Historically, this involved sailors manually sifting through data, a task that is both labor-intensive and susceptible to errors. "
You can imagine underwater vehicles have sonar, vision, other sensors. That comes in as a stream as they pursue the waters and look for objects.
" he described. The AI's ability to rapidly process this information and distinguish between actual mines and other seabed objects, such as rocks or debris, is a significant advantage.