Google and Rolls Royce Sign Deal for Autonomous Vessels

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The shipping industry is seeing a wave of technological innovations. In the wake of this, Rolls-Royce and Google have signed a deal to jointly develop technology for use on autonomous ships.

This is yet another first in the marine sector. The agreement was signed at the Google Cloud Summit in Sweden. According to the deal, the partnership will grant Rolls-Royce access to Google’s predictive analytics platform – the Cloud Machine Learning Engine, which will be used to train its own in-house AI.

Rolls-Royce is currently developing an AI-based object classification system designed to detect, identify and track objects that a vessel may encounter while at sea. The company will make use of the same neural net-based software that powers Google’s products, including its smart assistant and voice search.

Karno Tenovuo, SVP of Rolls-Royce’s dedicated ship intelligence unit, said, “While intelligent awareness systems will help to facilitate an autonomous future, they can benefit maritime businesses right now making vessels and their crews safer and more efficient. By working with Google Cloud we can make these systems better faster, saving lives.”

“By exploring the possibilities presented by machine learning, Rolls-Royce can combine the latest technology advancements with its deep knowledge of the maritime industry, ultimately bringing significant improvements to the sector,” said Eva Fors, head of Google Cloud Sales Nordics.

The agreement will see Rolls-Royce develop machine learning models built on Google’s Cloud software that are able to analyse vast amounts of marine data, training its AI to create relevant and accurate predictions. Onboard sensors, radar data, and current technology such as the Automatic Identification System will all be mobilised to collect data to form a global database.

While autonomous vessels are the ultimate goal, the deal will also see the development of systems that can improve the efficiency of existing ships, while giving crews an enhanced view of their surroundings and creating a safer operating environment. By accessing this software through the Cloud, the models can be developed from anywhere in the world and are immediately accessible globally allowing thousands of users. Models can, therefore, be trained on large quantities (terabytes) of data.