In recent years, advances in computing have allowed machines to perform more complex operations and tasks. This has enabled the development of Intelligent Systems (IS), which are being used to solve real-world problems in an efficient and autonomous manner. The transition from an Information Society to an Intelligent Society is a critical juncture in modern human society. It requires a continued development of advanced computing theories and algorithms that rely heavily on autonomous perception, information gathering, analysis and reasoning capable of outclassing living organisms.

The world of IS of automated operations and autonomous processes is one actively being explored by scientists. It has the potential to significantly improve a range of aspects of modern life. These include healthcare, manufacturing and transportation through data-driven decision-making and optimization. By granting machines a level of independence, it’s possible to create a wholly automated environment with few, if any, external human inputs.

What allows machines to exhibit higher level characteristics of functional autonomy is a combination of advanced computing architectures and algorithms. Central to this are the newly introduced Machine Learning (ML) systems, which rely on deep learning principles to achieve unprecedented performance levels. This allows for a level of automation and operational intelligence formerly unseen in the world of machines.

It is clear then that the transition from an information society to an intelligent one is a critical point in the development of modern technology and with it, the potential for new opportunities and realms of possibilities previously unconceivable. To ensure this transition is a success, we must continue to develop and test new theories and algorithms that can imbue machines with a degree of intelligence never before seen. With each improvement we make, we come one step closer to achieving a truly autonomous, intelligent and, ultimately, safer society.