The main drawback of describing AI as merely creating machines that are intelligent is that it fails to define AI and explain what constitutes an intelligent machine. Although there are many different approaches to the science of artificial intelligence (AI), advances in machine learning and deep learning are causing a paradigm shift in almost every area of the tech industry.
So what exactly is AI? Is it an approach? Is it technology? A field of knowledge?
We stick to the definition of AI as the study of simulating human intellect in computers that have been designed to think and behave like people. As a result, computers may be taught to carry out operations like speech recognition, decision-making, visual perception, and language translation that traditionally involve humans. And those operations themselves are achievements of AI’s subfields, machine learning and deep learning.
Machine Learning (ML)
Machine Learning refers to a group of computer algorithms that can learn from examples and improve themselves without being explicitly coded by a human.
Deep Learning (DL)
Deep learning is a subfield of AI that uses algorithms inspired by the structure and function of the brain, called neural networks, to process and analyze even bigger amounts of data.
Artificial Intelligence VS Machine Learning VS Deep Learning
Learn what the relationship between AI and ML and DL is and whether they can be opposed or juxtaposed.