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1. Fundamental science

In this document, I propose a fundamental — scientific — approach towards a profound understanding of natural intelligence and natural language — based on the way nature works.

1.1. Fundamental choice

But first, a fundamental choice must be made, because any variant of the Evolutionary hypothesis of Common Descent is fundamentally at odds with the Christian faith:

  • If man shares a common ancestor with the ape, Adam and Eve never existed;

  • If Adam and Eve never existed, the Fall — high treason against God — never happened;

  • If the Fall never happened, the redemption through Jesus is meaningless;

  • If redemption through Jesus is meaningless, the Christian faith is nothing but an empty religion.


On the other hand, one who sincerely investigates God's creation will gain fundamental insights from God, giving them a fundamental advantage in fundamental science.
 

For centuries, Christians were leading in fundamental science. These scientists sincerely observed the way nature — God's creation — works. As a result, their findings could be replicated in a controlled environment, after which their findings could be applied to daily life, in fields like:


By replicating their findings in a controlled environment — after which their findings are applied to daily life — these Christian scientists provided a Return on Investment to taxpayers, which we still benefit from today.


However, those who choose any variant of the Evolutionary hypothesis of Common Descent — or any other hypothesis denying God as the creator of the universe and life — will not be able to replicate their findings on the origin of the universe and life in a controlled environment. Let alone apply them to daily life because their findings do not describe the way nature works.

1.2. Fundamental truth

There is only one truth in fundamental science: the way nature works.

Nature works in only one certain way, enshrined in natural laws. One who investigates the way nature really works will be rewarded with their findings being replicated in a controlled environment and eventually being applied to daily life. In this way, taxpayers will have a Return on Investment in their funding of science.

1.3. Fundamental science is able to close the loop

All natural phenomena that are scientifically understood, obey laws of nature. And they all close the loop, like the following illustration of electromagnetism.

Electromagnetism is scientifically understood because it closes the loop:

  • We can convert motion to electromagnetism, and convert electromagnetism back to motion;

  • We can convert light to electromagnetism, and electromagnetism back to light;

  • We can convert magnetism to electricity, and electricity back to magnetism.

1.4. AI / NLP fails to close the loop

In primary school, we all learned a similar sum:

  • Given: “John has 3 apples.”

  • Given: “Peter has 4 apples.”

  • Logical conclusion: “Together, John and Peter have 7 apples.”

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The school teacher then wrote:

  • 3 apples + 4 apples = 7 apples


However, the result of the sum — “7 apples” — lacks a reference to “John and Peter”. So, from this result alone, it is impossible to generate a readable sentence:

  • “Together, John and Peter have 7 apples.”


Hopefully, mathematicians will come to the rescue, by closing the loop scientifically:

  • J = 3

  • P = 4

  • J + P = 7


Unfortunately, the mathematical result “J + P = 7” lacks a reference to “apples”. So, from this mathematical result alone, it is impossible to generate a readable sentence. It would require an engineered solution to come to:

  • “Together, John and Peter have 7 apples.”


This is just one example of my scientific challenge to beat my reasoning system. A generic solution to this particular example is described in Block 3.

Natural intelligence and natural language are not scientifically understood. Therefore, the field of AI / NLP itself is not scientific, because scientists are falling short of closing the loop for a childishly simple sum:

  • From natural language,

  • through logic (natural intelligence),

  • with the result expressed in natural language again.


It may seem like Large Language Models (LLM) can solve reasoning problems, from natural language — through logic — with the result expressed in natural language again. However, LLMs only have a limited, engineered reasoning capability. When reasoning problems are combined, LLMs will start to lose context.


We really must investigate the way nature works regarding natural intelligence and natural language, after which we will be able to develop algorithms — based on natural intelligence — that will not lose context when reasoning problems are combined.

1.5. Self-organization

The following ‘scientific’ paper states: “Self-organization refers to a broad range of pattern-formation processes in both physical and biological systems”.

However, no distinction is made between a static ‘organization’ — which is limited to pattern formation — and a dynamic organization, which requires natural influence to stay alive.

Self-organization is often misunderstood as the origin of natural intelligence. However, self-organization is the result of Natural intelligence.

Distinction:

  • Natural pattern formation — like fractals and the formation of snowflakes — is a static process, based on rules or laws of nature;

  • Swarming of birds is a dynamic, temporary process, based on the bird’s instinct. Instinct is an innate mechanism of survival. In case of no danger, swarming is practiced as an emergency drill, while it also improves bonding;

  • Self-organization is a dynamic, continuous process. It is a result of natural intelligence;

  • Any other organization — like a company or a pack of wolves — is a dynamic, continuous process of multiple intelligent actors.


So, organization and self-organization are a result of natural intelligence rather than being the origin.

1.6. Laws of nature

Intelligence and language are natural phenomena. All natural phenomena obey the laws of nature. And laws of nature are investigated using fundamental science.

The field of AI and NLP is investigated using behavioral/cognitive science. As a result, it is unable to close the loop of natural intelligence and natural language. So, we need to investigate natural intelligence and natural language using fundamental science. To illustrate the difference:

Fundamental science versus cognitive science
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