Artificial intelligence is defined as the ability of a machine to think for itself. Scientists and theorists continue to debate if computers will actually be able to think for themselves at one point. The generally accepted theory is that computers do and will think more in the future. AI has grown rapidly in the last ten years chiefly because of the advances in computer architecture. The term artificial intelligence was actually coined in 1956 by a group of scientists having their first meeting on the topic. Early attempts at AI were neural networks modelled after the ones in the human brain. Success was minimal because of the lack of computer technology needed to calculate such large equations. AI is achieved using a number of different methods. The more popular implementations comprise neural networks, chaos engineering, fuzzy logic, knowledge based systems, and expert systems. Using any one of the aforementioned design structures requires a specialized computer system. In order to tell that AI is present we must be able to measure the intelligence being used. For a relative scale of reference, large supercomputers can only create a brain the size of a fly. It is surprising what a computer can do with that intelligence once it has been put to work. Almost any scientific, business, or financial profession can benefit greatly from AI. The ability of the computer to analyze variables provides a great advantage to these fields. There are many ways that AI can be used to solve a problem. Virtually all of these methods require special hardware and software to use them. Unfortunately, that makes AI systems expensive. Many new AI systems now give a special edge that is needed to beat the competition. Created by Lotfi Zadeh almost thirty years ago, fuzzy logic is a mathematical system that deals with imprecise descriptions, such as new, nice, or large This concept was also inspired from biological roots. The inherent vagueness in everyday life motivates fuzzy logic systems. In contrast to the usual yes and no answers, this type of system can distinguish the shades in-between. Fuzzy logic's structure allows it to easily rate any input and decide upon the importance. Moreover, fuzzy logic lends itself to multiple operations at once. Fuzzy logic's ability to do multiple operations allows it to be integrated into neural networks. Two very powerful intelligent structures make for an extremely useful product. This integration takes the pros of fuzzy logic and neural networks and eliminates the cons of both systems. This new system is a now a neural network with the ability to learn using fuzzy logic instead of hard concrete facts. Allowing a more fuzzy input to be used in the neural network instead of being passed up will greatly decrease the learning time of such a network. Another promising arena of AI is chaos engineering. The chaos theory is the cutting-edge mathematical discipline aimed at making sense of the ineffable and finding order among seemingly random events. Chaologists are experimenting with Wall Street where they are hardly receiving a warm welcome. Nevertheless, chaos engineering has already proven itself and will be present for the foreseeable future. Making recommendations on which AI systems work the best almost requires AI itself. However, there is something that can be said about this. On the one hand, neural networks require massive amounts of computing resources that restrict their use to those who can afford it. On the other hand, fuzzy logic is practically a win-win situation. Although some are rather simple, these systems perform their duties quickly and accurately without expensive equipment. They can easily replace many mundane tasks that other computer systems would have trouble with. The chaos theory has potential for 8 handling an infinite amount of variables. This gives it the ability to be a huge success in the financial world. While the expert systems, knowledge-based systems, and cased-based reasoning systems are here to stay for a long time. They provide an efficient, easy to use program that yields results that no one can argue with. Designed correctly, they are can be easily updated and modernized. While the massive surge into the information age has ushered some old practices out of style, the better ones have taken over with great success. The rate of advancement may seem fast to the average person, but the technology is being put to good use and is not out of control.