Blog of the EP-KI Team

In the last blog post, we opened up the topic of »Explainability of Artificial Intelligence« (AI), which we want to continue in this blog post. »AI systems should not only be the best possible. Sometimes they should say ‘I have no idea what I’m doing here, don’t trust me.’ That’s going to be really important«, says Stanford University professor Herb Lin.

Are predictions from AI systems misleading or can we rely on them? As a real-world example, in this post we look at sales around Christmas using time series prediction models.

In any application that uses Artificial Intelligence (AI), the first step is the data. The second step is to apply an algorithm and thus develop an AI application. We want to take a closer look at this process in today's blog entry.

While searching for current algorithms for special solutions, I keep coming across the most diverse designations and, upon closer inspection, realize that I already know this algorithm, but in a different setting. Therefore, the first step here is to clarify which possible questions we can/would like to answer with AI algorithms.

We at Fraunhofer ITWM are mostly mathematicians and do research in different fields. Two major fields and methods are »Artificial Intelligence« (AI) and »Machine Learning« (ML). Our goal is to improve and understand these methods and to open up new fields of application. This also includes the application in business processes.