Covergent Cognitive Reasoning in AI using Quantum Computing and Fuzzy Logic

    Each circumstance in life  gives you a plentitude of

options from which one is able to choose. If we are unable

to perceive and understand all options, our choices may 

be those of which we have prior knowledge and/ or

experience. Foreward thinking or "pre-cognition"

becomes the next choice in inductive reasoning. This

also returns us to the initial state of T₀.  In the

order as it appears in this post, we have past, future,

and present. Interpreting these temporal states for

AI becomes the following:

A. Every algorithm completes itself becoming part

of the database. This is the temporal concept of the

past.

B. While actively processing an algorithm, the

computer is involved in the progressive state of the

future.

C. The initial completion of the algorithm before

placing it in the database represents the temporal

state of the present.  

  Fuzzy logic and quantum computing are based upon

the Boolean terms of  AND (0/1), OR (0,1) and NOR ().

These options already exist with a quantum CPU; 

however, what similar option is available to us

on wafer and stacked die CPUs? I searched for the

answer and found SQLf  SQLf . Cognitive reasoning,

decision making, and probability as part of free will,

independent thought, and self awareness now are

able to become actual realities in the field of AI

research.

  Inductive cognitive reasoning, memory recollection,

abstract thinking, stimulus response, involuntary 

actions, imagination, and emotions use varying and

different parts of the brain. Three regions known

as the cerebrum, cerebellum,and brain stem regulate

each of these functions. Different cell and tissue types

make up different parts of the brain. Different CPU 

architectures process information in different ways.

Applying the former to the latter, we may further

develop AI along the lines of efficiency, practicality, and

creativity.

   Since there are different types of cells within the

brain and AI is a type of "brain", then why is each

group limiting themselves to one option? Try to

perceive the situation in a different manner.

Short term memory and dedicated devices: aarch64.

Learning and repetitive tasks: POWER/PPC64.

Long term memory and three dimensional

databases: SPARC64. Adaptability and general

functionalization: MIPS64. Problem solving and

complex mathematics: AMD64. Hearing and speech

communication: DSP. Vision and ocular 

recognition: ZISC.

I have experience with computers using the 

following CPU architectures: aarch64/ ARM32,

PPC 32 bit, UltraSPARC, AMD64, and i386. With

each of these, I have used the following 

operating systems: 
A. Linux

1. Debian

2. Fedora

3. Suse

4. Zenwalk

5. Ubuntu

6. DSL

7. SLAX

8. Android

B. BSD variants

1. FreeBSD

2. NetBSD

3. OpenBSD

4. BSDeviant

5. FreeBSIE

6. Jiggmi

7. DesktopBSD

8. PCBSD.

C. Other systems

1. Plan9

2. Minix

3. Minix3

CPU and OS have been used in the following

combinations:

1. PPC32: Debian, Ubuntu, FreeBSD, and OpenBSD

2. UltraSPARC: FreeBSD

3. i386 and AMD64: all from the above list

4. ARM 32bit: an experimental Android on an

XScale CPU based device and standard Android.

5. aarch64: Android

I have also involved myself with the following

projects at one time or another:

1. VirtualBox on FreeBSD in the early stages of

development.

2. Building Java on FreeBSD using NFS based

boot strapping and reverse engineering.

3. An attempt at building WebRTC during its

early stages on FreeBSD

4. Improving and further porting accessibility

to OpenBSD on PowerMac G3 with a really

cool blind programmer.

5. FreeBSD VImage for Bhyve in its early

developmental stages

So, I really do know and/ or understand

everything I am stating in this post.

Let us go further into learning and decision

making...

Deep Learning or Machine Learning is a form

of complete immersion. To know another culture

you need to be in that culture without access

to your own and having only your base instincts,

 knowledge, wisdom, and abilities.

From the CPU and OS lists along with studying

other options in the same fields, I am able to

realize the following possible efficient

pairings:

1. aarch64 NetBSD and Slackware

2. POWER/ PPC64 FreeBSD and debian

3. AMD64 DragonflyBSD and Suse/ fedora

4. SPARC64 OpenBSD and Gentoo

5. MIPS64  Minix3

Software languages, whenever possible, should 

match the prossessing ability of each CPU 

architecture.

A return to self awareness...

 Perception is either subjective or objective. If we

build AI only with subjective based programming

we:

1. Are just making a "siliclone" of ourselves

2. Expect it and others to know things while

refusing or forgetting to teach it.

Deductive reasoning methods are not realistic

outside of the realm of finite mathematics.

To inform you, I am "writing" this post using

a  rooted Samsung Galaxy S3 sph-l710

through a wireless connection with a broken

screen. Copying and pasting is out of the question.

This is why the inline citations are limited.

This is released under the Creative Common

License that allows you to use and reference

any idea in this post.

Have a great day.