3 Rewinding 100 Years of AI: The Soul of Artificial Intelligence From Ancient Logic to the Foundational Laws of the Silicon World

Hello everyone, I’m Yanshen.

Welcome back to Rewinding 100 Years of AI. This is the third episode in the series.

In the previous article, we explored the material foundation of the Fourth Industrial Revolution: electricity as the “engine” of AI, and silicon chips as its “neurons.”

But that left us with a deeper question:

If electricity and silicon gave AI its physical body, what gave these cold semiconductors and circuits the ability to “think”?

If the soul of carbon-based life lies in consciousness, reasoning, and learning, then where does the “intellectual soul” of AI come from?

Today, we will travel across more than two thousand years of human intellectual history — from the origins of logic in ancient Greece, to the mathematical breakthroughs of the 20th century, and finally to humanity’s discovery of the boundaries of computation.

This is the story of how human beings encoded their own thinking into the foundational laws of the silicon world.

1. The First Seed: From Standardized Thinking to the Ancient Origins of AI

Every world-changing technological revolution begins with a seemingly useless philosophical question.

Just as Thales’ observation of static electricity opened humanity’s exploration of electric power, the intellectual origin of AI also began with a question that humans have asked for thousands of years:

Can human thought be broken down into standardized, repeatable rules?

The first milestone came more than 2,300 years ago in ancient Greece.

Aristotle wrote Organon and created the first complete system of formal logic in human history. Through syllogism, he gave reasoning a basic grammar.

A major premise. A minor premise. A conclusion.

For example:

All humans are mortal. Socrates is human. Therefore, Socrates is mortal.

For the first time, vague and intuitive human reasoning was broken down into clear, verifiable, and repeatable steps.

This was the first moment humanity realized that thinking was not a mysterious oracle from nowhere.

Thinking had rules. It had structure. It could be analyzed.

And that realization became the first seed of AI’s intellectual soul.

During the Middle Ages and the Renaissance, scholastic philosophers such as Thomas Aquinas further refined Aristotelian logic for theological debate.

At the same time, Ramon Llull invented his Ars Magna, or “Great Art,” using rotating mechanical disks to generate combinations of concepts. In a sense, this was an early attempt at automated reasoning and knowledge discovery.

It was one of the earliest shadows of computational thinking.

2. Rational Calculation: Leibniz and the Dream That Thought Could Be Computed

In the 17th century, the German genius Gottfried Wilhelm Leibniz pushed this philosophical question forward in a revolutionary way.

Leibniz, who independently developed calculus alongside Newton, proposed a bold vision:

A universal symbolic language and a calculus of reasoning.

He imagined that all human concepts, judgments, and reasoning could be transformed into operations within a universal symbol system.

When people disagreed, they would no longer need to argue.

They could simply say:

“Let us calculate.”

Then the correct answer would emerge through symbolic reasoning.

To pursue this vision, Leibniz made two contributions with lasting influence.

Binary: The Ultimate Simplification of Logic

Leibniz helped establish the modern binary system.

He believed that everything in the universe could be represented through 1 and 0 — existence and nothingness.

This idea directly influenced later thinkers, including George Boole.

Leibniz even designed a commemorative medal with a phrase expressing the idea that from 0 and 1, everything could be created.

The Stepped Reckoner: An Early Attempt at Machine Reasoning

To make calculation real, Leibniz also believed humans needed tools.

He invented one of the earliest mechanical calculators capable of addition, subtraction, multiplication, and division.

Pascal’s earlier calculator could mainly handle addition and subtraction, but Leibniz’s “Leibniz wheel” allowed repeated addition to perform multiplication.

His deeper hope was that machines could reduce human errors in reasoning — whether caused by careless mistakes or emotional bias.

Many people remember Leibniz for calculus.

But his more futuristic idea may have been this:

Thought itself might be computable.

More than 300 years ago, Leibniz had already written one of the first lines of the intellectual code behind artificial intelligence.

From Aristotle’s formal logic to Leibniz’s rational calculus, humanity spent two thousand years moving from “breaking down the rules of thought” to “quantifying the process of thought.”

But at this stage, the idea still remained mostly philosophical.

To turn it into a practical mathematical tool, humanity had to wait for a revolution in logic.

3. Breaking Through Theory: Boolean Algebra as the Mathematical Soul of the Digital World

If thermodynamics was the soul of the steam age, and electromagnetic induction was the soul of the electrical age, then computability theory became one of the deepest foundations of the AI age.

But before computability theory arrived, the key breakthrough came from a British mathematician:

George Boole.

In 1847, Boole published The Mathematical Analysis of Logic and created Boolean algebra.

What he did was unprecedented.

He transformed Aristotelian logic into algebra.

He used 1 to represent “true” and 0 to represent “false,” reducing human logical judgment to three basic operations:

AND, OR, and NOT.

The Basic Components of Boolean Algebra

Boolean algebra uses two values:

1 = true 0 = false

And three basic operations:

AND: true only when both conditions are true. OR: true when at least one condition is true. NOT: turns true into false, and false into true.

With only these simple elements, Boolean algebra can represent logical judgment.

Rewriting the Socrates Syllogism in Boolean Terms

Let us return to the classic syllogism:

All humans are mortal. Socrates is human. Therefore, Socrates is mortal.

In Boolean algebra, we can define:

M = the set of humans D = the set of mortal beings s = Socrates

The statement “all humans are mortal” means that there are no humans who are not mortal.

In Boolean form:

M × (1 − D) = 0

Here, 1 − D means “not mortal.”

If the intersection between “human” and “not mortal” is empty, then all humans are mortal.

The statement “Socrates is human” can be written as:

s × M = s

This means that when Socrates is combined with the property of being human, the result is still Socrates.

Now we want to prove:

s × D = s

That is, Socrates belongs to the set of mortal beings.

From:

M × (1 − D) = 0

We get:

M = MD

And since:

s = sM

Then:

s = sMD = sD

So Socrates is mortal.

Before Boole, logic was a branch of philosophy.

After Boole, logic became a branch of mathematics.

It became something that could be calculated, symbolized, and eventually executed by machines.

Every computer and every AI system today still depends on this foundation.

Boolean algebra gave the digital world its mathematical soul.

4. Is Everything Computable? The Territory of Truth Is Larger Than the Territory of Proof

Boolean algebra answered one question:

How can logic be calculated?

But in the early 20th century, mathematics faced an earthquake that forced humanity to ask a deeper question:

What are the limits of calculation itself?

At the time, the great mathematician David Hilbert proposed an ambitious program.

He wanted to build a complete and consistent system of mathematical axioms, in which every mathematical statement could be rigorously proven.

But in 1931, the 25-year-old Kurt Gödel shattered that dream with his incompleteness theorems.

Gödel proved that in any sufficiently powerful mathematical system, there will always be statements that cannot be proven or disproven within the system itself.

Even worse, the consistency of such a system cannot be proven from inside the system.

Here is a simple way to understand the idea.

Imagine a sentence that says:

“This statement cannot be proven.”

Now let a perfect logical machine judge whether this sentence is true or false.

If the statement can be proven true, then what it says becomes false, because it says it cannot be proven.

That creates a contradiction.

But if the statement truly cannot be proven, then what it says is correct.

So it is true, but unprovable.

Gödel showed that there is a gap between truth and proof.

Some things may be true, but impossible to prove within a given formal system.

This discovery changed mathematics forever.

It also planted a crucial question for AI:

If not every truth can be proven, then which problems can be solved by fixed mechanical procedures?

Where is the boundary of computability?

The person who answered this question was Alan Turing.

5. The Turing Machine: Defining the Ultimate Boundary of Computation

In 1936, at only 24 years old, Alan Turing published his landmark paper:

On Computable Numbers, with an Application to the Entscheidungsproblem.

In this paper, he proposed the Turing machine.

The model was extremely simple:

An infinite tape. A read-write head. A set of state transition rules. A state register.

Yet this simple model defined the essence of computation.

Computation is the process of reading and writing symbols and changing states according to fixed rules.

Before Turing, people believed different problems required different machines.

A machine for addition. A machine for multiplication. A machine for another specific task.

But Turing showed something far more powerful:

You do not need a different machine for every problem.

You only need one universal machine.

If the rules for addition or multiplication can be written as symbols and placed on the tape, then the same machine can execute those rules.

More importantly, Turing proved the existence of the universal Turing machine.

One machine could simulate the computation of all other Turing machines.

This was the first strict mathematical definition of computation in human history.

It also drew the ultimate boundary for all computers and all AI systems:

Any formalizable computational process can be simulated by a universal Turing machine.

But problems that are not computable cannot be solved, no matter how powerful the machine becomes.

In other words, there are mathematical problems that computers can never answer.

A simple analogy is the barber paradox:

There is a barber in a town who shaves all and only those men who do not shave themselves.

So does the barber shave himself?

If he shaves himself, then he is someone who shaves himself, so he should not shave himself.

If he does not shave himself, then he belongs to the group of people the barber must shave, so he must shave himself.

This kind of paradox reveals the limits of certain logical systems.

The Turing machine became the theoretical prototype of all modern computers.

It also became a central pillar of AI’s intellectual soul.

Because it answered the ultimate question:

If human thought, reasoning, and learning can be formalized as computational processes, then they can, in principle, be simulated by machines.

6. The Hardware Bridge: Shannon and the Path From Abstract Logic to Physical Circuits

In 1937, Claude Shannon made a critical breakthrough in his MIT master’s thesis:

A Symbolic Analysis of Relay and Switching Circuits.

Shannon proved that Boolean algebra could be directly mapped onto electrical switching circuits.

ON could represent 1. OFF could represent 0.

This transformed abstract logic into a physical engineering foundation.

From that moment on, logic was no longer only symbols on paper.

It became electric current flowing through circuits.

7. The Creation Moment: Z3 and the First Union of Soul and Matter

In 1941, Konrad Zuse built the Z3, widely regarded as one of the world’s first programmable computers.

The Z3 established the idea of automated computation controlled by programs.

It proved that a machine could solve different kinds of problems by receiving different sequences of instructions.

Its key features included:

• Around 2,000 to 2,600 electromechanical relays.
• Binary floating-point arithmetic.
• A 22-bit word length.
• Support for addition, subtraction, multiplication, division, and square roots.
• A clock frequency of roughly 5 to 10 Hz.
• A memory capacity of 64 words.
• Theoretical Turing completeness, although it lacked convenient conditional branching.

This was a key leap from calculator to computer.

From Aristotle’s syllogism to Leibniz’s rational calculus, from Boolean algebra to Gödel’s incompleteness theorems, from Turing’s universal machine to Shannon’s circuit mapping, and finally to Zuse’s Z3 computer, humanity spent more than 2,300 years encoding its own reasoning ability into the foundational laws of the silicon world.

This is the intellectual soul of AI.

It is not magic.

It is the highest crystallization of human rationality.

It is a relay race across thousands of years, carried forward by generations of extraordinary minds.

It is humanity’s ultimate exploration of the nature of its own thought.

8. What Comes Next

In the next article, we will arrive at the official birth of artificial intelligence.

We will return to the Dartmouth Conference in 1956 and see how a group of young scientists gave this new field a name and made a promise that would reshape the world.

Before we end, I want to leave you with three questions:

1. Aristotle and Leibniz both tried to standardize human thought. Do you think all human emotion, intuition, and inspiration could one day be broken down into logical operations of 0 and 1? Or will carbon-based life always contain a territory that silicon-based systems can never reach?
2. Turing and Gödel showed us that logic has limits, and some truths are unprovable. If AI’s soul is built entirely on logic, what would happen when an absolutely rational AI faces a logical loop like the barber paradox? Would it crash, or would it evolve a kind of wisdom beyond logic?
3. From Leibniz’s stepped reckoner, to Shannon’s mapping of Boolean algebra onto electrical circuits, to the Z3 computer’s first union of logic and hardware — when do you think the intellectual soul of AI was truly born? Was it in ancient philosophical questioning, in Turing’s strict definition of computation, or in 1941, when hardware first began to execute logical rules?

Feel free to share your thoughts.

Every comment is a huge source of motivation for me.

See you in the next article.