Everyone has heard about AI, but how does it actually work?
– JOHAN BJURGERT, HEAD OF DATA SCIENCE, LEOVEGAS
Everyone has heard about AI, but how does it actually work? In somewhat simple terms, it means that computers learn to detect patterns or to create functions by measuring data that has been categorised by people. An example is Facebook’s facial recognition tool, which owing to a massive volume of training data has become as good as people at detecting what is, or is not, a human face.
So how does this affect society – and companies? First and foremost, a number of work tasks will be eliminated. According to a report from McKinsey,* AI is creating the opportunity to automate 44% of the hours spent on work in digitally developed countries. This is opening up new opportunities that we previously couldn’t have imagined. By processing large volumes of data we can discover entirely new ways to perform work tasks and thereby dramatically boost productivity. Over time we will be able to revolutionise things that we previously took for granted, such as how we conduct scientific research.
For businesses, in the coming years AI will be decisive for competitiveness. Companies that successfully take advantage of this new technology will be able to increase their lead over competitors that are slow to implement the new technology.
LeoVegas is a company that is doing precisely this – making full use of its data from day one – both to optimise its marketing and to improve the customer experience.
During the year LeoVegas continued its work on completing a central data lake, entailing processes for gathering, transforming, quality assuring and accessing data for the entire company. We are now cloud based and use a robust and scalable technology that allows both batching and streaming, which make up a strategically important foundation for future projects that require high precision management of data in virtually real time. Equipped with detailed and standardised data from the data lake, we have succeeded in considerably elevating performance in several of the prediction algorithms that are used in the daily operations. This has had an especially strong effect on our work with responsible gaming, where we are working to identify and prevent gambling addiction. By combining more traditional algorithms with deep, neural networks, today we are well equipped to identify problem gaming.
Another interesting application that requires scalable management of data involves recommendations. On this theme we have developed algorithmic support for personal game recommendations, which improves the gaming experience, as customers are offered game recommendations that are personalised to their specific tastes. The work on evaluating and improving recommendations is just one of many activities in predictive analysis in 2019.
"In the coming years AI will be decisive for competitiveness. Companies that successfully take advantage of this new technology will be able to increase their lead over competitors that are slow to implement the new technology"
About Johan Bjurgert
Johan Bjurgert has a Master’s in Industrial Economics from Linköping University and a Master of Science in systems technology and robotics from KTH Royal Institute of Technology. With his background in research and development, Johan joined LeoVegas in 2017, where he has worked primarily in quantitative finance and has developed algorithms for statistical arbitrage.
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