Reinforcement Learning is rapidly progressing. Every other day, new applications across domains are developed. At PickleTech we closely follow the progress of reinforcement learning techniques, researching, and being ready to apply them when beneficial for a project. We have already implemented them in the field of particle accelerators. Last week, we were invited to give a seminar at the Physics Department at the University of Oxford to talk about it. Now, we exploit its impact in the fields of Health and Sports.
When you read constrained multi-objective optimization problem or game theory, you will most probably not think of Julian Alaphilippe or Elisa Balsamo next… or will you? Last weekend of September we travelled to Flanders to assist, first line, to one of the most exciting cycling races of the year, the 2021 UCI Road World Championship. Beyond boosting our passion for cycling even more, we had time to reflect on the present and future of data science in such an epic context.
As scientists we are used to performing tests on pretty much everything we do. Usually, those are hypothesis tests involving statistics, modeling and data. But recently, we experimented with another type, an exercise stress test. A medically controlled assessment where you push your physical activity close to your maximum, and check how your body responds. Have we pushed too far on the experiment driven way of life?
At PickleTech we are born to provide Data Science services that help domain experts solve impactful problems in fields such as Health, Sports Performance, Supply Chain and Mobility. We describe the current context in data science solution development, the challenges we face, and our motivations and core philosophy at PickleTech.