What is AI?
AI (short for “artificial intelligence”) is a computer-aided process for solving complex problems that are normally reserved for humans. Examples are machine vision, pattern recognition, speech recognition, and knowledge-based decision making in a wider sense. Distinctions are made here between classic algorithms which follow paths that are permanently fixed by the programmer, and applications of machine learning which identify solutions independently based on supplied data.
A special role is played by so-called “deep learning,” which goes beyond what traditional machine learning algorithms can achieve. These algorithms are trained and improved by adding high volumes of data continuously, equipping them to keep improving their error rate performance expectations.
Key AI concepts at a glance:
Artificial intelligence involves machines mimicking cognitive functions typically associated with the human brain.¹
Machine learning enables the machine to adapt to new circumstances and detect and extrapolate patterns.¹
Traditional machine learning algorithms are hand-crafted, hard-coded, and designed only for specific applications. They are “specialized” and cannot easily be used for other new tasks once they are up and running.
Deep (machine) learning is a type of machine learning that uses multi-layer neural networks with multiple hidden layers between the input and output layers. This permits faster algorithm development and yields more accurate results. Additionally, deep learning algorithms can identify relationships that traditional machine learning algorithms may miss.
1Artificial Intelligence, Russell & Norvig, 2016