Fields of Artificial Intelligence
Demystifying Machine Learning for Banks is a five-part blog series that details how the machine learning era came to be, explains why machine learning is the key artificial intelligence technology, outlines how machine learning works, and explains how to put all this information together in the data science loop. This is the second post in the series.
Artificial intelligence (AI) refers to computer technology capable of carrying out functions that normally require human intelligence, such as decision-making. AI consists of sub-fields which use various techniques. Let’s look at some of these subfields.
The Subfields of Artificial Intelligence
Machine learning refers to the ability of a computer system to use data to learn automatically, predict, act, and explain the decisions it makes. The technology is a subset of a broader field of artificial intelligence, which contains other related capabilities.
Deduction and Reasoning Systems
This subfield includes systems that can solve problems by applying rules and deducing further information, given their current awareness of their environment.
Robotics and Motion
This subfield relates to control systems that let machines manage physical tasks like movement, sometimes in a human-like manner.
This field relates to the ability to represent abstract concepts about the world and the relationships between them. By building an ontology of concepts, the system can structure data into different classes more effectively.
Image and Voice Recognition
These systems can identify and communicate with humans in an effective manner, providing the facility for automated assistance (tying in with expert systems) or identity verification.
These fields include planning and creativity, artificial general intelligence, and expert systems.
Machine Learning: AI’s Key Technology
Of all the technologies in the AI family, machine learning is particularly versatile. Many contemporary business problems involve predictions based on a pool of complex data, often including multiple dependent variables. Machine learning is already delivering real value in a vast variety of business environments: it detects changes in customer sentiment, alerts security teams to potential fraud patterns, and reduces healthcare costs by detecting tumors almost as accurately as a trained oncologist. Machine learning can even re-engineer business processes themselves.
Artificial intelligence positions the technology sector for explosive growth. According to the market research firm Tractica, revenues will increase from around ten billion U.S. dollars in 2018 to an expected 126 billion by 2025.
Why AI Is the Future of Growth
By 2030, AI has the potential to incrementally add 16% percent or “around $13 trillion to the global economic output– an annual average contribution to productivity growth of about 1.2 percent” according to the Wall Street Journal.
Machine learning is the decisive artificial intelligence technology to address many contemporary business problems that relate to insights from large-scale data. The marketplace recognizes its ability to transform how organizations make decisions, predictions, and reach insights.
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