Hello...

More of my philosophy about inductive logic and more..

I am a white arab and i think i am smart since i have also invented many scalable algorithms and algorithms..

I invite you to read the following article about Hume’s on inductive logic:

Problem of induction

https://www.britannica.com/topic/problem-of-induction

Read about David Hume philosopher here:

https://en.wikipedia.org/wiki/David_Hume

And i invite you to also read the following article about inductive
reasoning:

Be Humble: Black Swans and the Limits of Inductive Reasoning

https://www.datarobot.com/blog/be-humble-black-swans-and-the-limits-of-inductive-reasoning/

I will say that i am not in accordance with David Hume philosopher on inductive logic, since notice that in the above article is saying the following about David Hume views on induction reasoning:

"It is important to note that Hume did not deny that he or anyone else formed beliefs on the basis of induction; he denied only that people have any reason to hold such beliefs (therefore, also, no one can know that any such belief is true)"

So i think that we have not to be "pessimistic" as David Hume philosopher about inductive reasoning, since we have to distinguish between the inductive reasoning that work and the inductive reasoning
that doesn't work correctly, so let me show you an example of inductive reasoning that works, here it is: So to give an interesting example of science of computing, we can ask: What is the time complexity of the following binary search algorithm:

https://www.guru99.com/binary-search.html

And here is my mathematical calculations of its time complexity, so notice that it uses inductive reasoning that works:

Recurrence relation of a binary search algorithm is: T(n)=T(n/2)+1

Because the "1" is like a comparison that we do in each step of
the divide and conquer method of the binary search algorithm.

So the calculation of the recurrence equation gives:

1st step=> T(n)=T(n/2) + 1

2nd step=> T(n/2)=T(n/4) + 1 ……[ T(n/4)= T(n/2^2) ]

3rd step=> T(n/4)=T(n/8) + 1 ……[ T(n/8)= T(n/2^3) ]

..

..

kth step=> T(n/2^k-1)=T(n/2^k) + 1*(k times)

Adding all the equations we get, T(n) = T(n/2^k) + k times 1

This is the final equation.

So how many times we need to divide by 2 until we have only one element left?

So it must be:

n/2^k= 1

This gives: n=2^k

this give: log n=k [taken log(base 2) on both sides ]

Put k= log n in the final equation above and it gives:

T(n) = T(1) + log n

T(n) = 1 + log n [we know that T(1) = 1 , because it’s a base condition as we are left with only one element in the array and that is the element to be searched so we return 1]

So it gives:

T(n) = O(log n) [taking dominant polynomial, which is n here)

This is how we got “log n” time complexity for binary search.

More philosophy of what is philosophy..

I think i am a philosopher that is smart, so i will explain what is philosophy, philosophy is by logical analogy like software engineering
(and read about software engineering in my thoughts below), i mean that it is a high level knowledge and a high level view of the "way", for example philosophy is the "way" of how do we have to behave as a society or a global world, also you will notice that philosophy doesn't get into the details as is getting science into the the much details, so this proves that it is a high level knowledge, but more than that philosophy can also give the high level way to science so that science gets into the much details, so i think i am a philosopher that is smart and i am like feeling more deeply philosophy and finding patterns of philosophy with my fluid intelligence, so i am still inventing thoughts of philosophy, so i invite you to read all my thoughts of my philosophy below so that to understand my philosophy:

More philosophy about software engineering and about computer science..

I will ask a philosophical question of:

What is software engineering and what is computer science ?

I think i am smart and i will answer that it is related to abstract thinking and pattern recognition of human fluid intelligence,
since software engineering is about the high level knowledge,
i mean that it deals with such high level things as concepts
and there relationships, connections, and context..., so in software engineering the most important thing is like abstract thinking , but
it can use sophisticated pattern recognition of fluid intelligence, so it also uses high pure smartness, and this abstract thinking of software engineering doesn't get into the "details" as is getting computer science, so computer science gets into the much details, so software engineering is like mathematical modeling that is also a science, but computer science is "hard" science.

And to know more about mathematical modeling, i invite you to
look at my following software project of PDQ for Delphi and Freepascal
and it is my port of PDQ version 6.2.0 to Delphi on Windows and to Freepascal on both Windows and Linux, i have also provided you with two demos, one queuing MM1 demo, and another Jackson network demo. Also i have provided you with my html tutorial on how to solve analytically(by using mathematical modeling) the Jackson network problem provided to you as a PDQ demo, and here it is so that to know what is mathematical modeling:

https://sites.google.com/site/scalable68/pdq-for-delphi-and-freepascal

More of my explanation of my just new proverb about fluid intelligence and smartness..

Here is my just new proverb:

"Human smartness is finding a small number of tools that permit to
solve a great number of problems, so when you look carefully at what is human smartness you will notice that it is not about great quantity, it is about a small quantity of good quality that permits us to be so powerful. Being smart is not about quantity, it is much more about quality."

So i think i am smart and i will explain my new proverb above:

With pattern recognition of fluid intelligence we are finding
patterns that are the tools, and we are understanding and applying those patterns that we are finding with fluid intelligence to
other many other new problems, so then we are not finding the patterns again and again, so then we are not finding the tools that are those patterns again and again, so pattern recognition of fluid intelligence is a minimization process that permits to find a small number of tools that permit to solve great number of problems. I think i am smart, and I have to be more precise, so you have to understand that the minimization process above is on the "finding", so when i say in my proverb above: "Human smartness is finding a small number of tools that permit to solve a great number of problems", the "finding a small number" is my good abstract thinking and it means that it is a minimization process on the "finding", since we are not "finding" the tools that are the patterns again and again.

More of my philosophy about human fluid intelligence and smartness..

Human fluid intelligence involves being able to think and reason abstractly and solve problems, so it needs abstract thinking and pattern recognition, but we have to ask a philosophical question of:

What is abstract thinking in human fluid intelligence ?

So i will rapidly answer that abstract thinking is like
when in software programming we construct a "class" (that leads to an object in runtime) and its attributes, it is like the way of constructing a "concept" and knowing about what is its characteristics,
so abstract thinking is not finding a thing of a particular Husky Dog and what is its characteristics, but it is finding the general concept of a Dog and its attributes or characteristics, so i think that
good abstract thinking is much more powerful, so now i will ask a philosophical question of:

What is the "relation" in human fluid intelligence between pattern recognition and abstract thinking ?

I think that i have to define what is pattern recognition in human fluid intelligence, so i will say the following:

Pattern recognition in human fluid intelligence is to recognize a particular way in which something is done, is organized, or happens, so i think that it is with this pattern recognition that we are able to incrementally understand and we are able to construct concepts etc. so this also permits to do abstract thinking in human fluid intelligence.

So i will give my example of pattern recognition with my fluid
intelligence that permits me to understand, here it is:

So if you want to go fast from my country Morocco to another country called USA , how will you do it ? or what will you do ?

It is like my IQ test..

So if you answer that you need for example to use a fast airplane to go fast from Morocco to USA, your answer is a stupid answer, so you need the smart answer, so i will answer that the fast airplane too has to be "reliable" and your "health" has too to permit it and the "weather" has too to permit it, so now you are clearly noticing that you need to take into account many "factors" so that to go fast from Morocco to USA, so you are clearly noticing that being smart needs also a good plan

So that to understand more, let us say that you are measuring a human IQ, so if it is high human IQ , this value is a measure that is relative to the other human IQs, so you will say that this high IQ is much better at adaptability than the other humans, but it is not correct measure, because even science and technology have constraints that constrain(or limit greatly) the expressiveness of human IQs, so then we can not say that a high human IQ is better at adaptability than the other humans..

On 5/25/2021 8:29 AM, Amine Moulay Ramdane wrote:
> Hello...
>
> I am a white arab and i think i am smart since i have also invented many scalable algorithms and algorithms..

Shut up idiot.

Amine Moulay Ramdane wrote:
> Hello...
>
"Induction" has two meanings (it has more than two but there are two
relevant to your post). There is a valid proof-method, often used in
mathematics, and there is an invalid proof-method supposedly (but not
actually) used in science.
>

Acres of crap snipped.

--
Just as 'beautiful' points the way for aesthetics and 'good' for ethics,
so do words like 'true' for logic. All sciences have truth as their
goal; but logic is also concerned with it in a quite different way:
logic has much the same relation to truth as physics has to weight or
heat. Frege in 'Thoughts' (Der Gedanke)