Transforming from Human to Artificial Intelligence

Cem Kadir ŞAHİN, Ahmet YILDIRIM, Kerem SAVAŞ, Mutlu KAPLAN

Artificial IntelligenceAlgorithmBrainLearning
August 25, 2022

Everything is a repetition of its smallest part.

 

SUMMARY

In this study, the birth of the 3rd wave artificial intelligence algorithm, which will be equipped with decision-making abilities with humanoid feelings that exhibit learning behavior like the human brain, is described. In the study, with the philosophy of "Everything is the repetition of the smallest part", the most primitive and smallest known structure of the brain and the cells that enable us to learn is explained; The historical development of intelligence, wisdom and cognition processes are mentioned, and the development processes of artificial intelligence and its stages are exemplified. The numerical brain structure, which can learn with small data on its own by teaching only the rules,  and which can perform learning by matching with images, sounds or similar sensors, and the birth of the algorithm that creates this structure is explained.

Keywords: Artificial intelligence, algorithm, brain, learning.

 

1. INTRODUCTION

The decision-maker, by its very nature, chooses what is comfortable and simple. If the decision-maker chooses the difficult and the risky, he is in the determination and determination of the effort to be himself. In this way, it can be said that there is nothing but change, uncertainties, problems, and risk confusion. Risk is strategic in meaning. When the decision-maker takes the risk, the decisions made, and the consequences of those decisions can evolve into advantages or disadvantages.  However, it depends on the fact that the risks taken or to be taken by the decision maker in the decision-making process can lead to new advantages, and that the environments in which the decision is made change in a situation that is open to change and can be constantly renewed.

As a result of the changes in hardware with the advancement of technology, the first was manual machines, energy-consuming motor machines with the presence of electricity and automatic machines that followed them. In general, these automatic machines, which perform a single function or a specific function, have been developed into machines that perform multiple different functions with the technological changes in recent years and it has been tried to add intelligence to these machines and these studies are continuing.  (2) (Aysever, 2001)

In parallel with the change in machines, there have been developments in software systems. While the first software systems performed simple arithmetic operations, the resulting data was stored and transferred. Office automation software has been developed from developing software to facilitate our fast and complex life with developing technology. With the data obtained from office automations, management information systems and decision support systems have been developed. Likewise, this can be given as an example of intelligent, unmanned military vehicles in the defense industry, such as intelligent robot systems in factories. When it comes to the game world, we encounter universes with numerical twin structures and virtual, intelligent players who play games on their own in these universes.

Looking at the current approaches in today's machines and software, after manual control, human-controlled machines, traditional machines, and then automated machines have followed. Today, with automation systems consisting of automatic machines, many conveniences are provided in enterprises, factories or in our daily lives. All these systems work on specific software and perform specific jobs.  (5)(Euphrates and Euphrates, 2017)

These changes in technology have brought about social transformation. *0)(Yalçınkaya, 2010). The agricultural society that processes the land has been ruled by the agricultural lord, the mechanized industrial society has been ruled by the bosses, and with the development of information, the digital society has been managed by digital investors. Today, with the awareness and hunger for knowledge, and innovation, an innovative society is created and it is questioned who will manage this society (7)(Ozdemir, 2014)

With the rapid developments in information and communication technologies, systems that know the future by predicting the future will develop, the developing and changing social organizational structure will changes with it, and the smart organization of the future is moving towards the smart organization. (3) (From the beginning, 2003) Professor Stephan Hawking's warning that artificial intelligence could bring about the end of humanity raises different questions in minds.  (6)(Köroglu, 2017)

 

2. ARTIFICIAL INTELLIGENCE

We can define artificial intelligence as a branch of science that develops algorithms that try to bring certain features of human intelligence to the computer. It is aimed to develop artificial intelligence systems that can produce solutions to problems by exhibiting intelligent behaviors. According to scientist John McCarthy, who first coined the term artificial intelligence, artificial intelligence; is the branch of science and engineering that intelligence computer programs.

Edward Fredkin (Computer Scientist at MIT) says in a BBC interview: "There have been three important events in the past: The first is the formation of the universe, the second is the formation of the beginning of life, and the third is the emergence of artificial intelligence." (1)(Act. Acar, 2007)

To understand artificial intelligence, one must first understand the similarities and differences between the computer and the human brain: 

The human brain has an average mass of one and a half kilograms and has the ability to memory, process and reprogram 500 to 800 units of data per second in a life span of 65 years. That's about 3,600 bits of information per minute, 2,160,000 per hour, and 51,840,000 bits per day. 

As a scientist who researches on the brain, Dr. V.  When Grey Walter's work is examined, it is concluded that "It takes more than 300 trillion dollars to build a computer or machine that looks like a human brain."  He says that in today's technology, more than 1 trillion watts of electrical energy would be needed for a machine that works in this way. 

Throughout our lives, we receive information with electrical signals from all our sensory organs, send information and store this information. In addition, there is no consensus on how much of the concept of intelligence can be measured and what it means. As the common idea of the expressions used, we can define intelligence as the brain's ability to receive information and analyze it correctly and quickly. Since it is an open-ended and abstract expression such as consciousness, soul and subconscious, a general expression of intelligence could not be made. 

The concept of intelligence, on the other hand, is measured by the ability to create cause and effect relationships, understand information, process information, and derive information from knowledge.  Your intelligent behavior; learning, monitoring, problem-solving, reasoning, planning, making decisions, controlling, and diagnosing.

 

2.1 The formation of the universe 

Hesiod's 'Theogonia', which has an important place in the Greek philosophy of thought, gives clues to the formation of the universe. The most important thing is Khaos, one of the phenomena that make up the universe, according to Hesiod, "Khaos is the head of everything." (* 1) (Akderin, 2014). A word derived from the Greek word "Chaos" is "to open up, to yawn, to split" or "to yawn and open up to give birth to something."  (4) (Dürüşken, 2014) "Khaos means 'abyss, stretching slit, opening, emptiness' and expresses that everything has been thrown into the world system from an unknown cliff or void." (* 2)( (Werner, 2011).

Khaos, the chasm that stretches and opens to give birth to something, first  forms Gaia.  Gaia is Mother Earth with great space, where every being emerges as her immortal home. Mother Earth is the earth. Khaos, which is itself a formless and yawning void, separates the earth from its complex and disordered state, and the universe thus begins to form.  He creates Eros, the third main element after  Gaia  . Eros means "love, love" in Greek.  The exact equivalent used by Hesiod is "desire". (*3) (Erhat, 2014)

Gaia gives birth to Ouranos spontaneously with Eros, that is, with Eros’ desire. Ouranos, which means "starry sky”, is the sky from which Gaia was born in a way that will envelop and cover herself from all sides. Thus, the formation of Ouranos and  Kosmos,  which was born with the formation  of Gaia and Eros from Khaos, begins to take place completely.

Kosmos  means "to arrange, to arrange, to tidy up," derived from the verb kosmo. In Greek thought, Kosmos means "harmony, beauty, intelligibility and explain ability". 

2.2 The Beginning of Life and Evolution

The development of the brain, which governs the most primitive and most advanced vertebrates, is 600 million years old. To understand the evolution of the mind and the evolution of man, one must look at the evolution of the nervous system in living things and the evolution of vertebrate animals within it. Figure-1 In unicellular cells, cells sensitive to feeling in euglena  or paramecium or amoebae behave like a kind of nerve cell. 

Figure 1 Paramecium and Euglana

Living things; are divided into two basic groups vertebrates and invertebrates. Invertebrates do not have a nervous system. It has simple nerve cells that are sensitive to stimuli such as touch and light. For example, although bivalvia, which is found in mussels we know, is stimulated in members of the class of two crustaceans, they activate the muscular system of nerve cells and close their open shells.  In the Vertebrate class, as in Figure-2, there are living things ranging from fish with nervous systems to mammals according to the order of evolution.  Among these creatures, it is seen that the most developed and the most complex living thing is the human brain. 

It is necessary to know the mammalian brain simply:

Temporal lobe: It is the place of the hearing. 

Cerebrum: It holds our memories and controls the different signals we receive from the outside world.

Brain root: This is where all tasks are sent.

Cerebellum: It is the place of movements related to our muscles, such as running, for example. 

Ossipital lobe: Imaging works can be examined here. 

Frontal lobe: Speech control is in these sections. 

Parietal lobe: It is our center of touch and feel.

Pons: It is the location of the heart and respiratory functions.  (8)(Sakınç, 2015).

Figure 2 Vertebrate and Mammalian Brain Structure

However, in the modern age today, virtual minds, and high-speed recording systems that do not disappear, how they will affect the evolution of the human brain is one of the questions that are wondered today.

 

2.2.1 Pineal gland

The nervous system in mammals in vertebrates is closely related to brain development and the formation of intelligence. The Epithalamus, which forms part of the intermediate brain or forebrain, is the brain region where the biological clock and time concept are adjusted, hormone release and emotions are managed. 

The pineal gland, which is in this region, is located buried in the middle of the brain in all mammals.  The pineal gland: is a sensitive biological clock that converts the periodic neural changes produced by the light in the environment into hormonal information, the cellular structures in the organism during these hours are the structures of time measurement.  (Richards & Gumz 2012). As a result of types of research, it has now been determined that the pineal gland is a fourth neuroendocrine converter. That is, the pineal gland is the gland that converts from the nerve into a hormonal outlet (Wurtman & Julius, 1965).  When the sun rises, the production of the pineal gland stops, and in the dark, the melatonin it secretes begins to be produced. As darkness increases, its secretion increases.

In some cultures, and as in the Sumerians, the pineal gland was symbolized in the form of a pinecone. Hindu statues of God often hold a pinecone forward. Christian popes used pine cone handles for their mace. In Freemasonry, it is seen that the pineal gland is symbolized with the cone. 

2.3 Neuron and Brain Scientific Studies

  An Italian doctor named Camillo Golgi, while examining brain tissue with a microscope, poured the dye prepared by him on the brain tissue, making the axons, branched dendrites, and neuron cells easily visible. (1909) Using the highest technology today, Henry Markam tries to simulate a real human brain by initiating the Blue Brain Project and inserting all sections of human and animal brains into supercomputers, as in Figure 3. In doing so, he tried to remove his digital twin by increasing the concentration of calcium by transmitting electrical impulses to a neuron, examining all the nerves and connections of the dead brain. 

 

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Figure 3 Brain simulation image from the Blue Brain Project

Blue Brain is the name given to the world's first virtual brain. This means a machine that can function as a human brain. He has the goal of creating an artificial brain that can think, react, make decisions, and keep everything in its memory. To date, similar studies have been conducted on worms and mice. 

2.4 The Emergence of Artificial Intelligence

In his essay "Can machines think?", Turing states that thought and machine are terminally decided. Instead of the word "thinking", he introduces the game "Imitation Game" by naming it with another equivalent question.  (Lame, 2017)

In 1951, he introduced a test called "The Imitation Game", which led Alan Turing to reveal what machine thinking is. In its first version, this game did not include machine intelligence. The person in 2 different rooms wants someone in a 3rd room to deceive him and the other to convince him. In later versions, the computer replaces the person who wants to be tricked and finds out whether it is a human or a computer. In this way, it has been useful in the development of natural thinking methods by forming the basis of many problems related to artificial intelligence. 

2.4.1 Artificial Intelligence Foundation and History

If the purpose of artificial intelligence is to gather under 3 main headings:

• To make computers more intelligent, 

• Understanding intelligence, 

• Making computers useful for their benefit.

Many behaviors of humans or animals reveal their intelligence or definition of intelligent behavior. Examples include:

• Learning and understanding from past and previous experiences

 • Making sense of complex and inverse situations 

• Ability to give a quick answer instantly

• Ability to compare in finding solutions to problems

 • Ability to make sense of and use data 

• Ability to overcome different situations     

 substances.

The basis or history of artificial intelligence can be classified in different ways, according to different periods. 

Prehistoric Period: Thousands of years ago, the attempt of Daedelus, the creator of the wind, to create an artificial man in Greek mythology can be cited as an example. However, the year 1884 can be cited as an important turning point for artificial intelligence. Charles Babbage, who experimented on mechanical machines, showed that these machines could not behave as intelligently as  human. But in 1950, a scientist named Shannon proposed that computers could play chess.

Birth: At the conference of scientists in 1956, held in Dartmouth, United States  , artificial intelligence was born. In this conference, A.  NewellJ., McCarthy, M.  Minsky, H.  Simon and C. Shannon proposed to investigate the possibility of computer programs creating artificial intelligence. Thus, the term 'Artificial Intelligence' was used. 

The first artificial intelligence programs (Chess program, logic theories program, Logic Theorist; both theories are Simon and Newell theories) and LISP (artificial intelligence programming language) were created in this process. 

The information about 'intelligent machines' in human history dates to ancient times. Theoretical and practical developments on automata in a scientific plan, on the other hand, the first foundations of artificial intelligence were mathematical studies and logic studies.

One of the first is mentioned by Babbage (the "Analytical" Machine in 1842) and A. Turing (the Universal Machine in 1936) about cybernetics (Wiener) in the brain's interpretation of the data obtained. 

One of the main factors in the birth of artificial intelligence is the emergence of the computer. In this way, studies were carried out by considering whether we could combine computers with intelligence, and Alan Turing created a test that revealed the decision of whether computers are intelligent or not.

The Dartmouth Conference can also be called the beginning of a new era in artificial intelligence. This conference, organized by Dartmouth College, mentioned artificial intelligence (AI) for the first time and accepted the participants as the pioneers of artificial intelligence. 

One of the important achievements of this period is software used to distinguish similar geometric shapes. The successful results of this period marked the beginning of very early and unrealistic period of anticipation about the creation of intelligent computers. 

Dark Period (1965-1970): The fact that the hardware and software inadequacies in this process were very few and that software was produced in this way revealed such a period. The hasty attitude and excessive optimism created in the previous process convinced scientists on the subject that producing intelligent computers is a very simple process. As a result, computer experts tried to develop a philosopher-type mechanism and aimed to make intelligent computers by simply loading data. For these reasons, this period has the characteristics of a dark waiting period. 

Renaissance Period (1970-1975): In this process, especially software such as disease diagnosis was developed, they formed the basis of an exciting and long adventure that is still trying to reveal the results that are exciting today. 

Partnership Period (1975-1980): In this period immediately after the Renaissance period, artificial intelligence researchers saw that they could benefit from different branches of science such as psychology, language, etc.

In the 70s, great success was achieved in artificial intelligence with the introduction of the basis of artificial intelligence in subjects such as understanding the native language, robotics issues, and representation of information. 

In the 80s, with a serious increase in efforts to investigate by critical practical studies and industrialized countries in parallel, studies with high goals in a significant part, applications increase with the introduction of artificial intelligence into economic life.

In the 90s, the theme of artificial intelligence, it began to be heard with chess, which is identified with intelligence, and the DeepBlue software developed by IBM defeated the world champion Garry Kasparov in 1997.

With the 2000s  , artificial intelligence began to be found even in artistic activities and even computers began to be able to draw pictures. Today, there are artificial intelligence applications where we get much better-quality results with fact that we have ranked in every field.

In 2016, DeepMind's AlphaGo program defeated Lee Sodol, the world champion, in a game with a probability of over 14.5 trillion after the 4th move. 

As the most important feature of this entrepreneurship process that we are currently in the 2020s, there are attempts to take artificial intelligence out of the laboratory and adapt it to the needs and wishes of today's world. With the spread of many libraries and methods to large masses, it is seen that very wide areas of use have emerged. 

2.4.2 Artificial Intelligence Technologies

If we try to gather artificial intelligence under 3 main headings; The first wave can be done with more limited processors up to the 2000s, with training processes spread over longer periods using more limited memory spaces, and with primitive algorithms. But what happened was the spread of the internet, computers, technology, and the spread of information, and it was not easy to realize this in the flow of life as we could not notice what was happening now.

In the 2000s, computer technologies continued to spread and develop. With these developments, it has become easier to reach more memory and higher processing powers. In this way, artificial intelligence algorithms began to prove themselves by getting rid of normal algorithms. In this process, many different artificial intelligence models have emerged. Since these bits of intelligence are fed by data, big data hunting has started today.  The better your big data and model, the more successful your success begins to increase in terms of model results and even transfers the results much faster and more accurately compared to humans. For example, when pictures of many similar cats are given and piece of training are given, and then new cat pictures are shown, results can be reached with high accuracy in proportion to the similarity to the cat. Is he able to explain or question why he trained a cat, and how he came to this conclusion? Can it make meaning and context? Will they be able to adapt to the new environment, will they be able to improve themselves without people?  It is very difficult to say that artificial intelligence models work the same as the human brain, but we can say that some of them work in a similarly. This is how the 3rd wave will come to life by those who question. Figure 4 shows AI movements. The first wave is the output of artificial intelligence, classical programming, and outputs according to inputs from peripheral units. The second wave of artificial intelligence can be described as an example of intelligent optimization and the development of artificial intelligence algorithms, deep learning or machine learning, while the third wave of artificial intelligence is  characterized as super-intelligent algorithms with humanoid thinking and inference ability that produce decision output.