Artificial intelligence (AI) is no longer a foreign concept to us humans in this age of digitalization. In recent years, it has become increasingly important in our everyday lives and has also made groundbreaking progress in research. The basic concept of an AI is to imitate human cognitive abilities. AIs have complex algorithms that must be extensively tested before they are released. This is because, depending on the AI type and area of application, errors can have serious consequences - for example, in areas such as autonomous driving. For reliable quality assurance, testing and consulting, we are your partner. The imbus team has made it its business to help customers develop trust in their software and, in the course of this, advises and tests your projects against professional quality standards - get advice on AI applications now and develop trustworthy artificial intelligence!
Different testing methods will be used for different AI systems. For example, one will have to test an expert system in which the experience of doctors has been implemented in a set of rules differently than a system that is supposed to detect fraud in lending after learning from very many data sets.
Therefore, we each need to define what exactly we mean when we talk about quality assurance and testing of AI.
There are different types of AI (see the following graphic), but mostly machine learning is meant when we talk about it.