The first idea and definition of AI was first coined by John McCarthy in 1955 at Dartmouth Conference. Of course, they were 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.

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John McCarthy proposed that “Every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate 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.” In essence A.I is a machine which has the ability to solve problems but it is usually done by us humans with our natural intelligence. A computer will demonstrate a form of intelligence when it learns how to improve itself by solving these problems. To elaborate further the 1955 proposal defines seven araes of A.I.  Today there are surely more but below is the original seven;



  1. Simulating higher functions of the human brain.
  2. Programming a computer to use general language
  3. Arranging hypothetical neurons in a manner so that they can form concepts
  4. A way to determine and measure problem complexity.
  5. Self-improvement.
  6. Abstractions: Defined as the quality of dealing with ideas rather than events.
  7. Randomness and creativity

After sixty years, I think realistically we have completed the language, measure problems complexity, and self-improvement at least to some point. However, randomness and creativity is just having to be explored. This year, we have seen a lot of web episode script, short films and even a feature length film co-written or completely written by A.I.

Artificial Intelligence, what is intelligence? According to Jack Copeland who has written many books on A.I, some of the most factors of intelligence are;

  • Generalization learning that is, learning that enables the learner to be able to perform better in situations not previously encountered.
  • Reasoning that is, to reason is to draw conclusions appropriate to the situation at hand
  • Problem solving that is, given such and such data find x.
  • Perception that is, analyzing a scanned environment and analyzing features and relationships between objects, self-driving cars are examples.
  • Language Understanding that is, understanding language by following syntax and other rules similar to human.



So now you have an understanding of A.I  and intelligence, to bring it together a bit and solidify the  concepts in your mind of what A.I is, here are few examples of A.I. which are Machine Learning, Computer vision, Natural language processing, Robotics, Pattern recognition and Knowledge management. There are also different types of Artificial Intelligence in terms of approach for example strong A.I and weak A.I. Strong A.I is simulating the human brain but building systems that think a little process give us an insight into how the brain looks while Weak A.I is a system that behaves like a human but does not give us an insight into how the brain looks, IBM’s deep blue a chess playing A.I was an example it processed millions of moves before it made any actual move on the chess board. It does not stop there though, there is actual a new kind of middle ground between strong and weak A.I. this is where system are inspired by human reasoning and it does not have to stick to it IBM’s Watson is an example, like humans it reads a lot of information recognizes patterns and builds up evidence to say “Hey, I am X percent confident that this the right solution to question that you have asked me from the information that I have read”.

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