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As researches around the world rush to gain as much information and knowledge about the new Covid-19 virus as possible, it is of high importance to be able to convey any new findings to politicians, experts, and the public in general. This task may sound simple enough, but with lacking visualization techniques and a very high speed in the data flow, the important information could easily get lost. In this blog post you can read about some updates in the Data Science field concerning Covid-19.

The task of calibration is often time consuming, complex, and requires a good understanding of your system and a systematic workflow. We have noticed that some students, unfortunately, are anxious of control systems due to the endless hours spent on calibrating hardware in labs. The main issue often lies in the time it takes to try multiple sets of parameters. To address this problem, we have developed an application to aid calibration on hardware by enabling real-time calibration. In this post, we will describe the concept and how to use it. 

With the Covid-19 virus on the rise in multiple countries around the world, authorities are battling to control its spread and minimize human loss. In a globally connected world, this is an extremely complex problem.

The oceans are producing huge quantities of valuable data that could provide answers to many global issues such as climate change. In fact, by 2030 the "blue economy" is expected to grow at twice the rate of the rest of global economies. ODF Sweden is an initiative that aims to encourage broad AI innovation using ocean data that engages with academics, industry experts and the public sector to put these massive amounts of data to work. It also aims to educate and inform the general public about AI advancements and applications, as well as crucial ocean issues facing the world today. Here's a look at what our Data Science team has contributed to the project so far.

There is currently discussions going on related to Machine Learning and Deep Learning and where this “new” technology will have its use. Does it actually need a super computer to run the algorithms or can you get it running in an embedded system. Since we are a company in the forefront of technology and exist in both Control Theory and Data Science domain we were intrigue by those discussions and wanted to try it out in practice. In this post we will present our finding from our thesis work doing just this!