LR partners with The Alan Turing Institute to advance maritime digitalisation

Classification society Lloyd’s Register (LR) has teamed up with The Alan Turing Institute, UK’s national institute for data science and AI, to advance maritime digitalisation.

The parties will collaborate to provide companies adopting digital technology with a fast and cost-effective independent assurance and testing service provider, using each other’s resources and expertise.

The cooperation is expected to lay the groundwork for delivering more assurance of AI technology services, allowing for the necessary learning to create the requirements and standards demanded by the industry. 

“Lloyd’s Register is excited to announce this collaboration with the … Alan Turing Institute. The cooperation between both of our historic organisations offers a clear pathway to maritime digitalisation, helping to accelerate the uptake of digital/AI applications by reducing the cost and prioritising safety for our clients”, said Luis Benito, Innovation and Co-creation director at Lloyd’s Register.

Mark Girolami, chief scientist at The Alan Turing Institute, added: “We’re delighted to announce this collaboration today with Lloyd’s Register. The successful deployment of data science and artificial intelligence research results to the maritime industry will help make digitalisation happen much more quickly and we look forward to working together to accelerate progress in this field.“

Last year, LR launched an Artificial Intelligence (AI) Register, a standardised digital register of LR certified AI providers and solutions, “a first of its kind for the maritime industry“.

The register will assist maritime stakeholders in finding appropriate providers and solutions for business challenges, minimising the risk and cost of investing in AI technology. 

According to a recent report published by the classification society in cooperation with Thetius, the maritime industry is forecast to spend $931 million on AI solutions in 2022.

The report shows that the emerging use cases for the technology can be seen in digital twins, machine learning, knowledge-driven AI, natural language processing (NLP), neural networks, and sensor fusion.