MolaKule
Staff member
The Clock program mentioned in another thread
YouTube Self Generating Clock - Post #3200737
purports to generate (or evolve) a fully functional clock after so many iterations (or generations) after converging on a supposed solution. No reference was given as to the author or its source. This C++ code closely resembles an Optimization algorithm developed a number of years ago (originally written in Pascal) by Thomas Schneider (a computational biologist).
It is also claimed that no intelligence or investigator interference was involved, which is definitely not the case.
In Aerospace Engineering graduate school I wrote a thesis and a program that used Optimization and AI to develop target aircraft designs, which was later adopted by a major aerospace firm. All kinds of inputs were used, such as number of passengers, desired cargo load, range, speed, max altitude, etc. The target of this optimization was an optimum aircraft configuration using a database of engine designs, structural design rules, FAA rules and other constraints, etc.
In Optimization parlance, we search the “phase space” for the best possible solution defined by the fitness function. To converge on a solution, it has to do more than simply do blind searches, and therefore requires an “informational” context.
In Optimization, there is something called a fitness measure, or a “fitness function.” A set of possible solutions is generated within the program in which one of those solutions best converges on the target. In the aircraft design, a number of iterations are done with many possible configurations proposed, but only one is best suited for the target design. In other words, a set of possible suggestions are generated but only one best fits the target design. In my case, the fitness function is defined or created by the inputs and constraints.
And this point is crucial, the “fitness function” guides the search. In my case, the fitness function is defined or created by the inputs and constraints, all generated by intelligent beings.
So supposedly, as shown on the YouTube video, one simply starts the execution of the program without interrupting the program and wolla!, a Clock majically appears after so many generations, or “iterations” of the codes subroutines.
This YouTube program attains its goal by the choice of its fitness function. I.E., the fitness function implicitly inserts information and guides the program to its intended target.
The fitness function of course, and the program’s optimization code was designed by unintelligent beings or aliens.
This Clock example on YouTube is a futile exercise in an attempt to impress those less versed in the mathematics of Optimization.
It does not explain to the viewer how you can sneak information into an Optimization algorithm to attain your desired outcome.
YouTube Self Generating Clock - Post #3200737
purports to generate (or evolve) a fully functional clock after so many iterations (or generations) after converging on a supposed solution. No reference was given as to the author or its source. This C++ code closely resembles an Optimization algorithm developed a number of years ago (originally written in Pascal) by Thomas Schneider (a computational biologist).
It is also claimed that no intelligence or investigator interference was involved, which is definitely not the case.
In Aerospace Engineering graduate school I wrote a thesis and a program that used Optimization and AI to develop target aircraft designs, which was later adopted by a major aerospace firm. All kinds of inputs were used, such as number of passengers, desired cargo load, range, speed, max altitude, etc. The target of this optimization was an optimum aircraft configuration using a database of engine designs, structural design rules, FAA rules and other constraints, etc.
In Optimization parlance, we search the “phase space” for the best possible solution defined by the fitness function. To converge on a solution, it has to do more than simply do blind searches, and therefore requires an “informational” context.
In Optimization, there is something called a fitness measure, or a “fitness function.” A set of possible solutions is generated within the program in which one of those solutions best converges on the target. In the aircraft design, a number of iterations are done with many possible configurations proposed, but only one is best suited for the target design. In other words, a set of possible suggestions are generated but only one best fits the target design. In my case, the fitness function is defined or created by the inputs and constraints.
And this point is crucial, the “fitness function” guides the search. In my case, the fitness function is defined or created by the inputs and constraints, all generated by intelligent beings.
So supposedly, as shown on the YouTube video, one simply starts the execution of the program without interrupting the program and wolla!, a Clock majically appears after so many generations, or “iterations” of the codes subroutines.
This YouTube program attains its goal by the choice of its fitness function. I.E., the fitness function implicitly inserts information and guides the program to its intended target.
The fitness function of course, and the program’s optimization code was designed by unintelligent beings or aliens.
This Clock example on YouTube is a futile exercise in an attempt to impress those less versed in the mathematics of Optimization.
It does not explain to the viewer how you can sneak information into an Optimization algorithm to attain your desired outcome.
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