As data increasingly becomes the difference in a competitive travel landscape, EyeforTravel’s new report explores the possibilities for deep learning
Artificial intelligence isn’t new, but it’s finally getting smart, thanks in part to a type of machine learning known as ‘deep learning’. But does deep learning really hold answers for the travel industry, is the question posed by EyeforTravel’s latest report.
In recent years, deep learning has taken a big step forward and made some major advances in image and pattern recognition, autonomous driving and speech recognition (aka natural language processing). Like the vast network of neurons in the human brain, the artificial neural network, that powers deep learning, is an interconnected group of nodes, but it’s not quite the human brain – yet.
“Neural nets are still simpler than biological counterparts,” explains Alex Hadwick, EyeforTravel’s Head of Research. “And today what it [deep learning] truly excels at is focusing on a single task, which is typically finding relationships and patterns in very large quantities of data,” he says.
Unsurprisingly, in the data rich travel environment that is a compelling enough reason to take note.
Report interviewee Amer Mohammed, Head of Digital Innovation at Stena Line, certainly sees the value. But according to Mohammed, “what we are doing now is artificial narrow intelligence, AI that’s specific to a certain task. We need to come up with mathematical models that can actually understand the world, not just fake understand it.”
In the meantime, however, some of the tasks that deep learning is already being used for in travel include pricing, language processing, image recognition, consumer analysis, and market modelling.
For Trainline, a rail ticket retailer, using AI technology to make predictions on likely shifts pricing is an interesting application, because this would directly benefit the customer. According to chief operating officer Mark Brooker, Trainline is strongly focused on product development, and is investing in technology that enables it to delve more deeply into its data. “We are looking at technologies like machine learning, and what sort of outcomes can be achieved from artificial intelligence, but always with a focus on improving the customer journey,” he stresses.
So, what’s driving this growth?
