Science and research have always been at the core of all our endeavors. We collaborate with prestigious universities such as MIT, Chicago Booth and ETH Zürich to devise truly state-of-the-art technologies and funnel them into retail practice. As a result of this fundamental research work,...
The common understanding is that AI is a black box that devours data and spits decisions at scale. But is it possible to use it to visualize data from billions of shopping baskets into a simple product map that will allow us to see how...
Online and offline retailers in the FMCG market must regularly make decisions about assortment planning, product placement, category management, advertising, shelf design, and product categorization. These decisions directly influence the ability of retailers to acquire new customers, develop better relationships with them, and make important...
Applying the SO1 Supermarket Gym in software integration projects and upcoming research projects This is the last part of our interview series with Sebastian, our Chief AI Officer, on the Supermarket Gym. So far, we have covered: Part 1: Introduction to the Supermarket Gym – what it...
In our previous blog posts, we introduced the Supermarket Gym, a tool to simulate the shopping behaviour of individual customers. So far, Sebastian, our Chief AI Officer at SO1 (Segment of One), has explained the following: Part 1: Introduction to the Supermarket Gym – what it is and...
In the first part of this interview with Sebastian, our Chief AI Officer at SO1(Segment of One), we introduced the Supermarket Gym, a tool to simulate shopping behaviour of individual customers. One first step to utilize this tool is to generate data, which this part (edited for clarity...
How SO1 simulates individual shopper behaviors and choices with the Supermarket Gym We’re often asked what distinguishes SO1 (Segment of One) from other solution providers. One core aspect is our fundamental research work, which is closely tied to academic research. The following interview (edited for clarity...
Explaining latent properties — where meaning has no name Explaining AI is somewhat of a challenge, because for most humans outside of our development lab, the matrices of numbers don’t mean a great deal. So this post attempts a practical comparison. At SO1 (Segment of One) we operate in the...
Decision tree algorithm One of the machine learning approaches that we use at SO1 to predict consumer preferences makes use of decision tree algorithms (models). We use specific features based on consumer preferences, information about time intervals from previous product purchases, the time of year,...
This article analyzes the current state of Java and JVM support for high performance computing. The focus will be on optimizations based on hardware architecture and avoiding synchronisation. It is assumed that your algorithm complexity is optimal or the best you can achieve but as...