Abstract
As advancements in the age of technology continue to achieve impressive feats, it is important to consider what past accomplishments built the foundation for humanity to get to this point in time. Throughout history, brilliant thinkers have contributed to the development of the computing world that we see today. One scholar in particular, Alan Turing, is well known for his contributions to modern computing and artificial intelligence. At a young age, he devised a theoretical model for a computer, creating a general concept of an algorithm. This model is called a Turing machine. A Turing machine at its most basic form is a machine that is governed by a set of rules. By inputting these rules into an bi-directional infinitely long tape, the Turing machine is able to provide an output on a specific computation. Turing also asserted the idea of a Universal Turing Machine (UTM) that would take the description of a Turing machine as input and then simulate that machine, effectively defining a computation. It is through his proof of the UTM that Turing reasoned that no computer can theoretically do more than the UTM. While UTM’s may be inefficient in terms of constructing the hardware, they are Turing complete. Turing completeness is defined as the ability of a UTM to replicate any computational problem that a typical computer would do. Some examples include powerpoint animations and programming languages. The notion of Turing completeness is important for modern computing because it reveals the limitations of what is computable. In this talk I will define the concept of Turing Machines, then explain the functionality of UTM’s and the importance of Turing completeness in modern computing. Finally, I’ll close with implications for future developments in the computing field.