Hello,

More philosophy about what is artificial intelligence or general
artificial intelligence..

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

I think i am smart, and i have just explained below that the divide and
conquer algorithms are a particular case or special case of Swarm
intelligence of PSO(Particle Swarm Optimization), and i will explain
it more in my next posts, now notice with me that Swarm intelligence
uses localized optimization with exploitation as heuristics like Greedy
algorithms so that to enhance much more the artificial intelligence
algorithm, but notice with me that general artificial intelligence can
use Swarm intelligence like PSO at a lower level layer, and at a higher
level layer it can use the divide and conquer algorithms, i mean that
the unknown meaning can be divided and conquered by measuring it with
previous meanings from the data using artifical intelligence of for
example PathNET so that to find the unknown meaning, and i define the
meaning in artificial intelligence as as the higher concept that is
recognized with deep learning, and this way we can construct much more
rapidly more and more meanings and incorporate them in PathNET so that
to converge more and more to much more generalized artificial
intelligence that will rapidly approximate general artificial intelligence.

More philosophy about Swarm intelligence and PSO and artificial
intelligence..

Can we ask a philosophical question:

Is Swarm intelligence like PSO(Particle Swarm Optimization) a
brute-force general problem-solving technique and what is it ?

So i invite you first to read the following interesting article about
artificial intelligence of PSO(Particle Swarm Optimization):

https://docs.microsoft.com/en-us/archive/msdn-magazine/2011/august/artificial-intelligence-particle-swarm-optimization

And read my following thoughts about artificial intelligence:

https://groups.google.com/g/alt.culture.morocco/c/BKGvkTI5FY4

So I think i am smart and i will say that since artificial intelligence
of PSO(Particle Swarm Optimization) is guided by not only exploration
but by the mechanism of exploitation, so this shows that this mechanism
of exploitation guides the problem-solving technique, so we can
not say that Swarm intelligence of PSO is a brute-force general
problem-solving technique, since brute-force general problem-solving
technique and algorithmic paradigm consists of systematically
enumerating all possible candidates for the solution and checking
whether each candidate satisfies the problem's statement, but notice
that brute-force general problem-solving technique is not guided by the
quality of exploitation of artificial intelligence of PSO(Particle Swarm
Optimization), and i can say that the artificial intelligence of
PSO(Particle Swarm Optimization) is Swarm intelligence that is more
general than the
particular case of the divide and conquer algorithms, since in the
divide and conquer algorithms we are guided by the divide mechanism that
is the "exploration" that finds a solution and after that there is an
exploitation of this solution of this quality that is the already sorted
small arrays in the case of mergesort that will permit the recursive
merge algorithm to reduce the time complexity to n*log(n), so i think it
is the same for PathNet in artificial intelligence that i also think
uses a kind of divide and conquer algorithm.

Here is PathNet in artificial intelligence, read carefully about it here:

https://medium.com/@thoszymkowiak/deepmind-just-published-a-mind-blowing-paper-pathnet-f72b1ed38d46

More philosophy about declarative programming and imperative programming
and object oriented programming..

I invite you to read the following interesting webpage from wikipedia
about declarative programming:

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

I think that declarative programming is too much abstraction
since Functional programming is declarative programming that attempts to
minimize or eliminate side effects by describing what the program must
accomplish in terms of the problem domain, rather than describe how to
accomplish it as a sequence of the programming language primitives (the
how being left up to the language's implementation). This is in contrast
with imperative programming, which implements algorithms in explicit
steps. So declarative programming like functional programming generally
uses higher levels of abstractions than imperative programs or OOP. That
is, they’re further away from describing what’s actually happening in
the computer or lower level layers of programming, so i think that
declarative programming like functional programming is too much
abstraction that lacks understanding of the lower level layers of
programming that is also very important to know so that to become
efficient, so i think that this way of too much abstraction or/and too
much centralization of cloud computing like of Amazon or functional
programming and such look like the old way of too much centralization
and too much abstraction of the mainframe computer that was lacking on
efficiency, so then we have to know how to "balance" so that to be
efficient.

More philosophy about functional programming and more..

I think that the Delphi List Monad and the Delphi Maybe Monad that i am
giving below are not slower and they are working correctly.

I think i am smart and i understand the objections of neo-Nazism and
white supremacism, but i think that neo-nazis and white supremacists are
not thinking correctly, because there way of thinking there racial
superiority is not the correct way simply because they are not taking
correctly into account the exponential progress of our humanity,
since i am convinced that with this exponential progress of our humanity
we will soon (in about 20 years or 30 years from now) be able to enhance
much more our genetics and become much more smart
or much more beautiful and we will soon be able to do much more
than that because we will soon become so powerful because of this
exponential progress of our humanity, so this is why i am not in
accordance with white supremacism and neo-nazism since they have to
adapt to this exponential progress of our humanity.

More philosophy about the exponential progress and about artificial
intelligence..

I think i am smart and i think that we are going to become so powerful
soon, i mean that this exponential progress of our humanity is an
amazing thing, and i think that with this exponential progress,
artificial intelligence too will soon become so powerful soon, so i
think that the most important thing now is not to ask if we are going to
become so powerful soon, but the most important thing it is that we have
to ensure high "safety" or high "reliability" of this process of
becoming so powerful by for example being a sophisticated philosophy.
And i invite you to look at the following video so that to understand
this exponential progress of our humanity:

Exponential Progress: Can We Expect Mind-Blowing Changes In The Near Future

https://www.youtube.com/watch?v=HfM5HXpfnJQ&t=144s

More philosophy about artificial intelligence and about the objective
function that guides..

I think i am smart, and i have quickly thought about the objective
function of artificial intelligence that guides, so the important
philosophical question in artificial intelligence is:

Is general artificial intelligence possible and what is the the
objective function that guides general artificial intelligence ?

I think that the objective function of general artificial intelligence
is not the same as a gradient descent with wich we optimize, since i
think that the objective function in artificial intelligence is
that we have to build like a model that approximate the result
of the reality, i mean that the objective function of general artificial
intelligence has to be that we measure the meaning with the previous
meanings from the data, and this way we approximate the meaning, so we
have to build much more meanings and meaning from the data and we have
to measure the unknown meaning with the previous meanings and if it
doesn't approximate well, so it is like a baby that doesn't know about
the meaning and it can become a dangerous environment for the baby like
for general artificial intelligence, and my way is also valid in a
distributed environment with many artificial intelligence robots, so i
think that the more localized artificial intelligence will become
incrementally and rapidly a more and more generalized artificial
intelligence that can approximate a general artificial intelligence, so
i think that general artificial intelligence is possible.

More philosophy about Swarm intelligence and about the too much
abstraction and more..

I invite you to read about Swarm intelligence here:

How Swarm Intelligence Is Making Simple Tech Much Smarter

https://singularityhub.com/2018/02/08/how-swarm-intelligence-is-making-simple-tech-much-smarter/

I think that humanity is using "specialization" and the "division" of
labour that reduces complexity so that to be efficient, so our evolution
looks like Swarm intelligence algorithms, since Swarm intelligence
algorithms also have to both explore with a bigger size of the
population of the Swarm intelligence algorithms and have to do
exploitation so that to reduce complexity and be efficient, and this
bigger size of of the population in Swarm intelligence algorithms that
explore is the division of labour that we use and it is also a
specialization and it looks like a divide and conquer algorithms, since
notice in the mergesort algorithm that we are reducing the time
complexity from for example a time complexity of an n^2 sorting
algorithm to n*log(n), and you are noticing it clearly since the
mergesort algorithm reduces much more the time complexity by recursively
"dividing" the array of elements so that to obtain a small arrays that
are already sorted(or we can sort the small arrays of 10 elements by
using an algorithm of sorting of n^2 and it will be more efficient), and
notice that when we obtain those small arrays that are already sorted,
it is what reduces the complexity and brings much more efficiency, since
we are recursively using the merge algorithm after that, and notice that
the mergesort is also like Swarm intelligence since when we recursively
divide and obtain the already sorted arrays, notice that this
recursively dividing leads to many already sorted arrays, and it is like
the bigger size of the population in Swarm intelligence that explore and
that leads to high efficiency, so i think that artificial
intelligence must be like a divide and conquer algorithm, so you divide
like in a Divide and conquer algorithm so that to obtain a high quality
or high efficiency since you reduce complexity, so it looks
like PathNet in artificial intelligence, read my following thoughts
about it: