Introduction to Artificial Intelligence

This series of articles is focused generally around the topic of Artificial Intelligence (AI). We will embark on by looking at what AI is, and cover the various ways in which it is able to be implemented and applied using computers and modern technology in further articles.

Part 1 - An Introduction


Artificial intelligence is a very broad field, and far from being isolated to computing it encompasses a lot of other disciplines such as philosophy, neuroscience and psychology. it's significant to note though, that instead of just seeking to understand intelligence, AI practitioners seek also to build or produce it. The applies and applications of AI are a lot of and varied, and although a lot of look on humanoid robots when we discuss AI, you might be surprised to know that we already encounter applied AI in our day-to-day lives.

AI is full of big questions - how does an entity (either biological or mechanical) think? How does it understand or solve a problem? Can a machine truly be intelligent? What is intelligence? The answer to these questions may not be easy, but there is an answer staring us in the mirror so we know the quest to find out is achievable.

Through this series of articles I will be exploring the a lot of different approaches, sub-fields, applications and questions that we encounter when exploring this vast and exciting field of research.

Part 2 - What is AI?

Firstly I would like to say that the term Artificial Intelligence (AI) means different things to different folks. In fact even the words we use to describe the topic are ambiguous. The term artificial can have subtly different meaning; look at what we mean when we refer to 'artificial light'. This is real light, that has been created by a man-made source. It functions exactly as we would expect light to function, and from a physicists point of view it simply 'is' light. When we refer to 'artificial grass' even so, we use the word artificial to mean something subtly different. Artificial grass is not grass. it's not a plant, it's not made of the same material as the plant, and it doesn't share all the properties of real grass. It does even so perform the main functions of grass adequately, and may often fool folks into believing that grass is present.

The term intelligence is also open to interpretation, and then we end up with some very different definitions of what AI in reality is. The definitions we come up with even so tend to fall into a among two categories - they're either focused on the process used to achieve the goal, or on behavior. for instance, Luger & Stubblefield define AI as 'The branch of computer science that is interested with the automation of intelligent behavior' Whereas Winston defines it as 'The study of the computations that make it possible to perceive reason and act'.

We also have to look at how we measure success, and again there are a few common standards. We tend to either assess our system when equated to human performance, or against an ideal concept of intelligence often referred to in the field as 'rationality'. A system is rational if it makes the correct decisions.

Broadly speaking we end up with four acceptable goals in producing AI - systems that think like humans, systems that act like humans, systems that think rationally, and systems that act rationally. In the next part of the series we will embark on to examine each in more detail.