Never heard of distributional shift? If you’re in shipping, you should read our post on what it is and why you need to know!
Put simply – it’s one of the greatest challenges to effectively harnessing data, including the use of artificial intelligence, in every sector – and especially so in shipping. Handling this data phenomenon elegantly is the key to unlocking major efficiency improvements on your ships.
Over the past five years of research we have become industry leaders in this specialty – allowing us to make an average 8% efficiency improvement per vessel through performance routing powered by AI.
But we know that, together, we can increase these numbers – and that collaborating to share approaches to handling distributional shift can not only make shipping greener, but also help sufferers of Multiple Sclerosis, help accelerate the autonomous car revolution, and help improve the lives of millions.
DeepSea and the Shifts Project
To that end, we have launched The Shifts Project alongside a group of researchers from the Universities of Basel, Cambridge, HES-SO Valais and Lausanne. This is an international collaboration dedicated to studying and improving approaches to the critical topic of distributional shift in high-stakes, real-world settings (such as shipping).
Test your (virtual) metal
On that note, the Shifts Project has also launched the Shifts Challenge, an open initiative which encourages AI researchers – industrial and academic – in the shipping domain to test their own models’ capacity to handle real-world shipping challenges. The winners and runners-up will receive awards and – above all – a serious “stamp of approval” from some of the world’s top experts in the field.
More information on the Shifts Challenge can be found on the Shifts website.
Working with AWS
The Shifts Project is powered by AWS, providing a fully scaleable environment for evaluating the submitted models. DeepSea's cloud-based infrastructure is also powered by AWS end-to-end - including platform hosting, data storage, and a complete AI environment.