There’s much confusion around artificial intelligence at the moment, and the term seems to be thrown around a lot but what it is exactly. To clear things up, first of all, let’s take a look at the definition. Here is the earliest and hence purest definition of AI for the time when it was first coined. So, the official idea and definition of AI were first invented by Jay McCarthy in 1955 at Dartmouth Conference. Of course, plenty of research works done on AI by others such as Alan Turing before this. But what they were working on was undefined field before 1955. Here’s what McCarthy purposed quote;
“Every aspect of learning or any other feature of intelligence can, in principle, be so precisely described that a machine can be made to stimulate it. An attempt will be made to find how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves.”
Areas of AI
AI is the machine with the ability to solve the problems that are usually done by us humans with our natural intelligence. However, the computer would demonstrate a form of intelligence when it learns how to improve itself at solving these problems. Further, to elaborate, the 1995 proposal defines seven areas of AI today. There’re surely more, but here are the original seven.
- Simulating higher functions of the humans
- Programming a computer to use general language
- Arranging hypothetical neurons in a manner so that they can form concepts
- A way to determine and measure problems complexity
- Abstraction: defined the quality of dealing with ideas rather than events
- Randomness and Creativity
After sixty years, we have realistically completed the language measure problem complexity and self-improvement to at least to some degree. Nonetheless, randomness and creativity are just starting to explore.
What is Intelligence?
According to Jack Copland (who has written several books on AI) some of the essential factors of intelligence are;
- Generalization Learning
- Problem Solving
- Language Understanding
Types of AI
Moreover, there are different types of AI in terms of Approach. For example, the strong AI and weak AI
Strong AI is simulating the human brain by building systems that think and in the process, give us an insight into how the brain works. But we are nowhere near the stage yet. On the other hand, weak AI is a system that behaves like a human. But it doesn’t give us insight into how the brain works.
It doesn’t stop there. There’s a new kind of middle ground between strong and weak AI. This’ where the system is inspired by human reasoning but doesn’t have to stick to it.
Examples of AI
So, now we have an understanding of AI and intelligence to bring it together a bit and solidify the concept of what AI is. Here are some examples of Artificial Intelligence
- Machine Learning
- Computer Vision
- Natural Language
- Pattern Recognition
- Knowledge Management