The COVID-19 pandemic has highlighted the importance of Artificial Intelligence (AI) as an enabler of cost optimization and business continuity. Contrary to the misconception that AI is a luxury, it is actually a revenue generator. AI can improve customer interactions, analyze data more quickly, generate early alerts about upcoming disruptions, and automate decision-making. From a scientific point of view, AI cannot think because there is no definition of “thinking” and it is generally associated with humans, who are biological beings rather than artificial machines.
Figure 1 shows three regions where AI, Machine Learning (ML) or Statistics predominate. The primary objective of AI is to understand what intelligence is and to make machines more useful. This article is distributed under the terms of the Creative Commons Attribution License (CC BY). It is important to note that neither AI methods nor ML or Statistics can be mathematically derived from a common underlying methodological framework, but have been introduced separately and independently.
Popular and basic methods of AI, ML and Statistics are listed below. Machine learning is one of the most common and successful ways to achieve this, so these two terms are often used interchangeably.
- Artificial Intelligence: Neural Networks, Fuzzy Logic, Expert Systems
- Machine Learning: Supervised Learning, Unsupervised Learning, Reinforcement Learning
- Statistics: Regression Analysis, Correlation Analysis, Time Series Analysis
