Artificial Intelligence & Co - What Does It All Mean?

Artificial Intelligence (AI) and in this context also Cognitive Services, Neural Networks, Deep or Machine Learning; all these are terms we hear and read more and more often lately. Yet -- contrary to what many believe -- AI is not a new phenomenon of the digital age. AI concepts have been around for much longer. As early as 1956, the term was first used and coined by U.S. computer scientist John McCarthy at the Dartmouth Summer Research Project on Artificial Intelligence. And as early as 1950, Alan Turing formulated his idea for a procedure to find out whether the thinking ability of machines could correspond to that of humans. The methods and algorithms of Artificial Intelligence are therefore basically old hat.

But why are these topics surfacing so vehemently right now? The answer to this question is simple: AI & Co are receiving so much attention because we now have the technical means (unlike Turing) to make AI usable. These are exponentially increased computing power, cloud computing and the ability to collect, store and analyze extremely large amounts of data. Moreover, the potential of these now feasible AI applications is extremely exciting.

In this respect, Artificial Intelligence should be seen as the next stage of Digital Transformation. AI has long since left the research labs and is taking over more and more tasks in our everyday lives. It supports us, gives us tips and recommendations, and makes our lives easier and more convenient in many areas, for example through digital assistants, cooperative robots, autonomous vehicles, or drones. Smartphones tell users the traffic situation for the way to work at the right time without their manual intervention. Continuous intelligent analysis of machine data allows optimized and predictive maintenance. And on websites, we communicate with chatbots that act as the first point of contact for online stores.

At first, the idea of AI is quite simple: Artificial Intelligence imitates human abilities to see, hear, analyze and understand - for example, for image recognition or natural language processing - and applies them to large amounts of data. In this way, activities that require cognitive skills can be performed by machines, and new insights can also be gained that were previously inaccessible - for example, when it comes to learning more about customer behavior. What offers can companies make to their customers and at what (appropriate) time? What conclusions can be drawn from customer behavior about the further development of the company's own portfolio? The list of possible questions and areas of application seems endless. The sub-disciplines of Artificial Intelligence include machine learning (ML) and deep learning (DL). In the Machine Learning sub-discipline, IT systems can use algorithms to recognize patterns in data sets. The insights gained in the process are used to answer new questions, allowing the software to learn independently and develop new solutions. Deep Learning, on the other hand, refers to neural networks that are designed to imitate human thought processes and can solve classification problems (recognize and react to facts) on text, sound and voice, image or video files by training them in advance.

All of this shows that Artificial Intelligence is no longer a dream of the future. The technical possibilities for realizing AI projects are there and AI has already arrived in a growing number of companies. Due to the possible applications that already exist today and the continuing rapid technological development, it is becoming very clear that Artificial Intelligence is not a short-lived hype, but has substance and will decisively shape the future in the business environment as well. AI is not an end in itself, but an intelligent way to realize efficient solutions for business challenges. Or to put it another way: Artificial Intelligence is already an extremely useful tool today that can support the business success of companies.