Artificial Intelligence (AI) software performs complex tasks of learning and cognition at a level that matches or exceeds that of humans. This characteristic makes AI a particularly unique technology from the perspective of business models and value creation, as it simulates (and often exceeds) human performance.
Within AI, the progress of the field has caused a division of AI into a number of branches. Among this growing list of subcategories, each is often described as separate technologies on account of their own unique characteristics.
Artificial General Intelligence (AGI): Is achieved when the AI can perform functions associated with average human intelligence. This leads to enterprise-class AI software that can replace humans within the corporate workforce. This also is the lightning rod for negative portrayals of AI by politicians and the media.
Machine Learning: Is a type of AI that involves using computerized mathematical algorithms that can learn from data and teach it to evolve as the data keeps changing. Machine Learning algorithms build a probabilistic model and then use it to engage in pattern recognition within subsequent sets of data.
Natural Language Processing (NLP): Enables computers to understand human language including contractions, slang, and accents, and in turn produce human-like speech and text. Machine translation between human languages is also a form of Natural Language Processing. Among other effects, language barriers between humans may vanish within a few years, from NLP becoming a standard feature within smartphones.
Deep Learning: Is an advanced specialization within Machine Learning, originated by Geoff Hinton in 2006, that uses the model of human neural networks to make its predictions about new data sets. As a subset within Machine Learning (see image), it is the very forefront of new breakthroughs in AI and is responsible for the sudden resurrection of the entire field. Deep Learning is the most rapidly advancing component of AI, and will soon be the largest driver of AI revenue. It may eventually be dominant in every form of AI as it converges into other types of AI that do not yet utilize Deep Learning.
Machine Vision: Identifies images of visible objects as well as patterns that cannot be seen, such as time-elapsed images, infrared images, immediate magnification or telescopic sight at intelligently chosen instances, etc. This provides robots with vision, and helps search engines parse billions of photographs, images, and charts for relevant patterns of information.
Artificial Super Intelligence (ASI): Describes AI that performs at levels that greatly exceed the abilities of any living human being. This enables a user to achieve tasks that were previously entirely beyond reach, potentially creating business models that were previously impossible.