Our everyday lives are nowadays greatly influenced by computers and software. Many of the even simplest tasks are unthinkable to be carried out without the current technology on hand. And society is shaped to many extends by its new achievements, as the progress in technology is so fast that often the older generations have to learn from the younger ones. Today, many people work in the field of computer science or related branches with an increasing tendency. For those and many more reasons, the current epoch is often called the digital age  or information age. But how did we get there? Was it predictable to come? And who are the fathers of this sophisticated machines that are carried around in everybody’s pocket today?

 

        On this blog, three revolutionary papers are presented, which impacted the scientific community of their time and the future. More precisely, the articles of Shannon [107], McCulloch and Pitts [74], and Turing [116] are examined to see under which circumstances they emerged and how they influenced proceeding works. Thanks to their level of abstraction, these theories yielded applications in many different fields. But this is at the same time a crucial point of caution when one wants to make direct use of them. It will be also shown in this blog that researchers need to be aware of these limitations and avoid using the theories blindly, especially when the field of research is not much related to the field for which they were originally developed for.

 

        In Section HISTORY, it is shown that the development of mathematics and physics subsequent to the Second Industrial Revolution  in the middle of the 19th century were in many points radical. This also laid the foundations for modern theories that were developed in these three papers and in the scope of “cybernetics”. In addition to that, the technological improvements during the Second World War  contributed to the astonishing progress of science. It should become clear that the need of digitization and mechanical computation  emerged logically from the quest of that time.

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        The reader dives deeper into the three landmark papers in Section THREE LANDMARK PAPERS. Moreover, she or he will understand their revolutionary impact when they aroused attention and how we are able to build devices that exceed already human capacities. 

 

        Section IMPACT focuses on the impacts those papers have on humanity. Among others, it explains the use of information theory in deep-space communication, how neural models were pioneering - the field of what became machine learning - and e.g. how the Turing test helped conceive bot detection in the Internet. It then details the intrinsic drawback of the artificial neural networks, namely that their internal functioning is extremely hard to grasp. Maybe this is a warning that one day we might not understand machine computation at all. This chapter also compares the learning processes of machines and humans and builds upon this to suggest hints for designing machines that think and learn the way human beings do. Finally, the limitations of information theory are underlined.