The complexity of financial market prediction has led companies to develop statistical models with decision-making capabilities. These models rely heavily on AI. Starting in the 1990s, research focused on using the personal computer to develop new technological enhancements. Of course, much has changed since the 1900s, the most important of which being AI. Applying AI to financial market prediction involves using automated processes that recognize patterns in trading activity, consume those patterns, and make an appropriate decision. The information analyzed and consumed by the AI system is actually the same data and the same patterns that humans use when trying to predict stock market action. The main difference between a human analyzing this information and an AI system is the lack of human judgment. AI does not rely on human judgment in its decision-making processes. This is beneficial since human decisions are sometimes irrational, emotional, and subjective and can cause humans to overlook important and subtle points. AI systems can recognize and act on patterns in real-time without the hindrance of these “human” factors. Another difference is speed. A computer system—AI—can easily process a hundred times the information a human could and can do so in seconds. This quantitative finance niche quickly developed into an entire industry devoted to understanding and predicting market behavior.