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Artificial Intelligence 04 – Propositionnal Logics or Relationnal Quantities ?

Written By: Jean-Paul Cipria - Juin• 23•17
It is ... a Car and also a Scientific Regression ?

It is … a Car and also a Scientific Regression ? Picture 1.

First articles 01, 02 and 03 on artificial intelligence used relational laws from quantities, measurements, statistics to and from same concepts. It is one of the 20th century sciences methods. We establish relationships  with mathematical equations on a real phenomenon descriptive variables.

Difficult ! Master Level.

Difficult ! Master Level.


Expériences En Construction

Expériences En Construction

Created :2017-06-23 11:41:33. – Modified : 2017-07-27 16:56:08.

Then we forgot since Galileo around 1600, with great, huge successes, to use smelling, hearing and common human sensations or sentiments. It was a great discover by scientists to do some methods seated on measurements with relationship with numeric quantities WITHOUT our own opinions.

Then, now we are trying to go forward ? How ? Why artificial intelligence is so difficult to grasp with « old « sensations » methods as non sciences ones ?

As you might guess …

You can see at animated picture 1 that you can infer that if you see a « wheel » and a « seat » the composition or assemblage may be a « car ». You are very clever in a « structural » composition of objects. But are you sure is it the only one « view » to describe your object ? Then you use « academic normal » description for an object. But rapidly you hurt you to some very big problems. How can we describe an liquid or gaz flow pattern ? The « structural view »  – Lagrange or Euler descriptions – seems to « explain » some structural forms but it is an illusion. As a map on a weather description you can’t infer, determine future maps ! We saw only, but it is well, stationary, fixed maps. We need, for example, differential equations to predict future.

To follow 23/06/2017.

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Jean-Paul Cipria
23/06/2017.

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