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To a computer, input is the information needed to make decisions.
For example, if you get dressed, you will need information such as what clothes are available to you, then you might consider the temperature, the season, and personal preferences.
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The instructions tell a computer how to transform a set of facts into useful information.
The facts are data. The useful information is knowledge for people, instructions for machines or input for another algorithm. Typical examples are sorting sets of num...
Computation is the heart of an algorithm and involves arithmetic, decision-making, and repetition.
To apply this to getting dressed, you make decisions by doing some math on input quantities. Wearing a jacket might depend on the temperature. To a computer, part of getting dressed algor...
The last step of an algorithm is output - expressing the answer.
Output to a computer is usually more data. It allows computers to string algorithms together in complex ways to produce more algorithms. Output can also present information, such as putting words on a screen.
It can sometimes be too complicated to spell out a decision-making process. Machine learning tries to "learn" based on a set of past decision-making examples.
Machine learning is used for things like recommendations, predictions, and looking up information.
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Neuroevolution is a form of artificial intelligence. It is a meta-algorithm, an algorithm for designing algorithms. It adopts the principles of biological evolution in order to design smarter algorithms. Eventually, the algorithms get pretty good at their job.
published 7 ideas
Quantum Computing is a form of computing that takes advantage of quantum mechanics to process information exponentially faster than classical computers.
Classical computers use classical bits which can consist of either a 0 or a 1 to encode information.Quantum computers,on ...
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