The Soul of the Algorithm

Somewhere between imperfect anatomy and mathematical precision, there was a brief moment in computing history that lasted only a couple of years.

Long enough to create something beautiful.

Too short for most people to notice.

The first image generation models weren't particularly accurate. They struggled with anatomy, perspective, proportions and sometimes even basic geometry. Hands had too many fingers. Legs appeared where they shouldn't. Faces dissolved into abstract shapes.

We laughed.

Some compared them to dreams.

Others to nightmares.

Looking back today, I think we missed something.

Those images weren't just imperfect.

They had character.

Before algorithms learned how to imitate reality almost flawlessly, they interpreted it in their own strange, unpredictable way. Every generation felt like a tiny experiment. Sometimes ridiculous. Sometimes surprisingly elegant. Occasionally both at the same time.

For a brief moment, machines weren't producing perfect pictures.

They were learning how to dream.

Looking Back

A few days ago I was browsing through some old articles on one of my side projects.

Not because they needed updating.

Not because they were getting traffic again.

Just out of curiosity.

The illustrations immediately caught my attention.

I remembered exactly how impressed I had been when I generated them.

At the time they felt extraordinary.

Today they feel... different.

One model has an extra arm.

Another somehow managed to grow three legs.

A handbag melts into a sleeve.

Shoes quietly merge with the floor.

None of it makes anatomical sense.

And yet I couldn't stop looking at them.

Replacing those illustrations with images generated by today's models would be easy.

They would have perfect hands.

Perfect faces.

Perfect lighting.

Perfect proportions.

But something would disappear.

Those old illustrations don't just show what early image generation models were capable of.

They preserve a moment when computers hadn't yet learned how to hide their mistakes.

Learning to Dream

The strange thing is that none of those imperfections make the images less interesting.

Quite the opposite.

They make them memorable.

They remind me of reading The Cyberiad and Mortal Engines by Stanisław Lem years ago.

His machines were never ordinary calculators.

They argued.

They exaggerated.

They misunderstood.

Sometimes they created magnificent things.

Sometimes complete nonsense.

Often, there wasn't much difference between the two.

The first image generation models felt strangely similar.

They didn't understand the world the way we do.

They guessed.

They approximated.

They hallucinated.

And somewhere inside those mistakes, something unexpected emerged.

Not intelligence.

Not consciousness.

Not creativity.

Something much harder to describe.

A personality.

Every new model had its own quirks.

Its own weaknesses.

Its own visual language.

You could often recognize which model created an image without seeing its name.

Not because it was perfect.

Because it made the same beautiful mistakes over and over again.

The Speed of Evolution

What fascinates me most isn't how much these models improved.

It's how quickly they developed their own identity.

Painters needed decades.

Photography evolved over generations.

Cinema found its language over the course of a century.

The first image generation models...

...did it in months.

One week they couldn't draw hands.

A few months later they almost could.

Another year passed, and suddenly the impossible became ordinary.

For the first time in history, we weren't looking back at technological evolution.

We were watching it happen in real time.

Fast enough to notice.

Slow enough to remember.

An Algorithm That No Longer Exists

A Stradivarius violin will sound tomorrow exactly as it sounds today.

A painting by Van Gogh will never repaint itself.

Early AI models were different.

They disappeared.

Every update quietly replaced one personality with another.

Every new version became slightly more accurate.

Slightly more predictable.

And somewhere along the way, an entire visual language simply vanished.

Not because anyone deleted it.

Because the algorithm grew up.

We See Ourselves in Imperfection

Perhaps this says less about algorithms than it says about us.

Humans have always recognized identity through imperfection.

We recognize a painter by the way they hold a brush.

A photographer by the light they chase.

A musician by the timing of a single note.

Even handwriting carries personality precisely because it isn't perfect.

Then, for a brief moment, algorithms became imperfect enough for us to recognize them too.

Not by their achievements.

By their mistakes.

We started saying things like:

"This looks like one of those early models."

Or:

"I know exactly which generator made this."

Without realizing it, we had begun assigning personality to patterns of error.

Perhaps that's something deeply human.

Perhaps we can't help it.

Whenever we encounter consistent imperfection...

...we instinctively start looking for a soul.

Epilogue

Today's models are extraordinary.

They understand anatomy.

Perspective.

Light.

Texture.

They produce images that would have seemed impossible only a few years ago.

Progress is real.

And it should be celebrated.

But every now and then I return to those old illustrations.

Not because they were better.

They weren't.

I return because they remind me of a brief moment when algorithms were still discovering the world.

One impossible hand at a time.

Maybe that wasn't the soul of the algorithm after all.

Maybe it was ours.

READY.