The Artificial Intelligence term is not new, but its definition changes since the first use it.
Alan Turing created the first paper about AI in 1950: “Computer Machinery and Intelligence”, where he tried to answer the question “Can machines think?” – and based on that Turing Test term was well known as a method for determining if a machine is intelligent.
From that time, there was a lot of changes, where people played around the algorithms and writing different programs with intelligent behaviour, such as playing chess or automatic translation. New programming languages were developed to create more clever programs such as PROLOG (1972) – the first logic programming language or MATLAB (1984), software to accelerating engineers and science.
Based on Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig, there are four categories of Artificial Intelligence, such as:
- Systems that think like humans
“The exciting new effort to make computers think… machine with minds, in the full and literal sense.” (Haugeland, 1985)
“The automation of] activities that we associate with human thinking, activities such as decision-making, problem solving, learning…” (Bellman, 1978)
- Systems that think rationally
“The study of mental faculties through the use of computational models.” (Charniak and McDernott, 1985)
“The study of the computations that make it possible to perceive, reason and act.” (Winston, 1992)
- Systems that act like human
“The act of creating machines that perform functions that require intelligence when performed by people” (Kurzweil, 1990)*“The study of how to make computers do things at which, at the moment, people are better” (Rich and Knight, 1991)
- Systems that act rationally
“Computational Intelligence is the study of the design of intelligent agents” (Poole et al., 1998)
“AI… is concerned with intelligent behaviour in artefacts” (Nilsson, 1998)
Artificial Intelligence is a system that can learn from data and based on that, decide to achieve a specific goal or task using Machine Learning. Natural Language Processing, Speech, Vision, Robotics etc.
AI is an entire field dedicated to making machines smart. AI is an umbrella for all intelligent algorithms.
Machine Learning (ML)
Machine Learning is a division of Artificial Intelligence. ML analyses, understand and identify a pattern in the data, such as recognise text, recognise voice etc.
There are two main types of Machine Learning:
- Supervised Learning – getting dataset with labelled training data and training examples – it’s based on input-output pairs
- Unsupervised Learning – predict outcomes on the recognising patterns in input data.
Deep Learning (DP)
Deep Learning is a subset of Machine Learning and Artificial Intelligence. It’s using Artificial Neural Networks that was created based on biological neural networks in human. It’s using multiple layers to extract higher-level features from the raw input progressively.
In other words
Artificial Intelligence, Machine Learning and Deep Learning are techniques to help you create an intelligent program.