Table 3.

Glossary of common artificial intelligence terminology.

Terminology	Definition	References
Deep learning	The computation of the human independent critical thinking, interpretation, and resolution through the categorization of random data.	(Salman et al., 2020)
Machine learning	The recognition of data through identified patterns.	(Bansal et al., 2020)
Convolutional neural network (CNN)	A deep learning algorithm that targets AI systems designated in the segregation of multimedia information (i.e. video, audio, and images)	(Salman et al., 2020)
Supervised learning	Data comprehension through the use of cataloged data.	(Hussain et al., 2020)
Unsupervised learning	Data comprehension through the use of uncatalogued data.
Natural language processing (NLP)	The encoding of accumulated data obtained through natural linguistics and dialogue.
Natural inspired computing (NICC)	The development of novel algorithms and hardware through the multidisciplinary integration of mathematics, computer science, theoretical physics, etc.	(Agbehadji et al., 2020)
Convolutional layers	A set of predetermined parameters that shape the AI learning process.	(Salman et al., 2020)
Pooling	The learning blocks of CNN.
Fully connected layers	Interlinked sets of CNN neurons that transfer learning data.
Reinforcement learning	The training of an AI platform through a specified set of rewards and penalties established by the human programmer.	(Hussain et al., 2020)
Big data	The total volume of heterogeneous computed data in the present databases.	(Agbehadji et al., 2020)