Technological Thoughts by Jerome Kehrli

From Transistors to Intelligence

We live surrounded by computers.

They sit in our pockets, run our cars, power global markets, filter our information, and increasingly make decisions that affect our lives. And yet, for most people, including many professionals who work with them every day, computers remain strangely opaque.
We use them fluently. But do we truly understand them?

That question is the quiet thread running through two complementary books:

1. L'informatique – Des transistors aux microservices
2. Les sciences informatiques – De Turing à l'intelligence artificielle

Together, they form a single intellectual journey: from the physical foundations of computing to the abstract ideas that gave birth to algorithms, cryptography, and artificial intelligence.
They can be read independently. But together, they tell a deeper story, one that is rarely told in a structured, accessible, and honest way.

A Project Born Long Before the First Page

This project did not start with a publishing contract.
It started in 1987, when a father chose to give his child a Commodore 128D instead of a game console.
It continued years later, when a twelve-year-old wrote his first lines of BASIC without knowing that these clumsy instructions would open the door to a lifelong exploration.

What followed was not a straight line, but a long accumulation of questions:

• How does a machine really work?
• Why do architectures look the way they do?
• Where do our algorithms come from?
• Why do some problems resist computation?
• And how did we end up building systems that can now learn?

These books are not encyclopedias.
They are the result of years of ordering knowledge, making choices, and accepting renunciations, because clarity always comes at the price of exclusion.

Book I - From Matter to Systems

L'informatique – Des transistors aux microservices

The first book is firmly anchored in the concrete reality of machines.
It starts at the lowest possible level - electricity, transistors, logic gates - and slowly builds upward:

• microprocessors,
• memory and execution,
• operating systems,
• networking,
• virtualization,
• distributed systems,
• cloud architectures,
• and finally, microservices.

But the ambition is not to list technologies.
The goal is to explain why things evolved the way they did.

• Why abstraction layers exist.
• Why operating systems look the way they do.
• Why distributed systems are hard.
• Why modern infrastructures inherit constraints that date back decades.

This book is for readers who want to reconnect the dots between:

• hardware and software,
• systems and applications,
• historical constraints and modern design choices.

It is written with the intent to be particularly valuable for:

• junior engineers who learned tools before foundations,
• developers who want to understand what happens below their code,
• architects who need a coherent mental model across layers,
• curious readers who want a structured entry point into computing as a system.

Book II - From Ideas to Intelligence

Les sciences informatiques – De Turing à l'intelligence artificielle

If the first book explains what machines are, the second explores what they can compute, and why.
This is the more abstract book.
It is also the one that required the most difficult choices.

Computer science is vast: computability, complexity, data structures, logic, formal languages, graphs, optimization, cryptography, machine learning...
Everything matters.
But a book is not an encyclopedia.

So this volume focuses on a coherent intellectual trajectory:

algorithmic thinking and problem construction,
• hard problems and computational limits,
• optimization as a unifying discipline,
• cryptography as a bridge between pure mathematics and real-world security,
• blockchain viewed technically rather than symbolically,
• and finally, machine learning - from the perceptron to generative AI.

The goal is not to turn readers into specialists, but to give them conceptual depth: to understand what is happening behind the buzzwords, to see how modern AI is rooted in decades of theory, and to grasp the limits as clearly as the possibilities.

This book is ideal for:

• students who want meaning behind formulas,
• engineers who use ML without fully understanding it,
• professionals navigating AI discourse with critical thinking,
• educators looking for a narrative that connects ideas rather than isolating them.

Why These Books Are in French - And Why That Matters

Many excellent books on these topics already exist in English. Much fewer in french.
And that is not the point.
The point is that language is not neutral when it comes to understanding.

For a large part of the francophone world, English technical literature creates friction, translation dilutes nuance and conceptual depth often gets lost behind vocabulary barriers.

Writing these books in French is not a limitation, it is a deliberate choice:

• to make deep technical knowledge accessible without linguistic overhead,
• to serve students, engineers, and educators who think and teach in French,
• to contribute durable reference material to francophone technical culture.

These books assume intelligence, curiosity and rigor, but they do not assume perfect fluency in English.
And that matters.

Emotion, Doubt and the Discipline of Renunciation

Writing these books was not about accumulating content. That was the easy part. It was much more about:

• cutting chapters,
• abandoning beloved topics,
• rewriting explanations until they were both precise and readable,
• redrawing diagrams,
• verifying references,
• and constantly choosing clarity over exhaustiveness.

The hardest part was not technical. It was accepting that some things would not make it into the book.
That discipline is what gives these volumes their coherence.
They are not showcases of erudition. They are guided paths through complexity.

Who These Books Are Really For

These books are not for people looking for quick answers or shortcuts. But rather for people who want:

• to understand rather than memorize,
• to build mental models rather than collect tools,
• to connect history, theory, and practice.

They belong on the shelves of:

• junior engineers building their foundations,
• experienced professionals filling conceptual gaps,
• educators seeking coherent narratives,
• and lifelong learners who refuse to treat technology as magic.

Two Independent Books. One Coherent Vision.

Each book stands on its own. But together, they offer something rare: a complete, structured exploration of computing, from physical reality to abstract intelligence.
They explain:

• how machines are built,
• how computation is defined,
• how limits emerge,
• and how modern AI fits into a much longer story.

Not as hype. Not as prophecy. But as engineering, science, and human ingenuity.

Final Thought

Technology moves fast.
Understanding lasts longer.
These books were written for those who want to slow down just enough to truly understand what they are building, using, and shaping.

And once you see the whole picture, you never quite look at a computer the same way again.