Science works: the GPS case

 Relativity theory is a great practical example of how, and why, science actually works.

Science is true because it works *). Science allows us to drive cars, fly airplanes, make video-calls, cure diseases, and save lives.

But science requires education to be discussed. Otherwise it's like magic **). People without scientific education cannot understand its language, and cannot distinguish science from magic. 

This is how you get stupid conspiracy theories, religion, and antivaxers.

As a great example, here's a great story about our GPS navigation. 

You know, we open Google maps or Waze on our phone, and it gives us precise directions on how to get home. Behind this every day tool there's an incredible amount of another and engineering. 

Gps positioning works by measuring and comparing frequencies of signals sent by satellites. 

There are 30 GPS Satellites orbiting the Earth. Designing satellites and sending them to orbit the earth is an incredible scientific and engineering accomplishment in itself. 

Each satellite broadcasts towards Earth a signal with: the satellite’s location in space, and the exact time the signal was sent. 

Each phone has a GPS receiver that continuously listens to the signals from 2-4 satellites, and continuously measures its distance from them based on the time needed by the signal to reach the phone. Then the phone calculates its own position, based on 1-4 such distances (theoretically min 4 for correct trilateration, but you can get reasonable estimations with less, if using additional local data such as GSM towers and wifi-s).

And the beauty part? Nothing would work without taking into account Einstein's theory of relativity. 

Because the clock of each satellite is slightly different from the clock of your phone and the time on Earth. Because satellites move faster, and their gravity field is lower.

So the time of their signals must be continuously updated to account for this difference.

This is why we know that relativity theory works. Because we can place satellites in orbit with precision, and we can then calculate the position of every phone also with incredible precision, by adjusting for the time difference between objects in space, correctly predicted by Einstein 100 years ago, when there were no satellites, phones or GPS.

Why I Don't Believe in the Pension System (Even Though I'm Pro-Social Policies)

I'm very socialist when it comes to pensions — and broadly, when it comes to education, research, healthcare, and social safety nets. I deeply believe in the state’s responsibility to provide basic protections for its citizens.

But in most other areas, I’m quite capitalist. I believe in market dynamics, personal responsibility, and economic freedom.

That’s exactly why I don’t believe in the pension system — not Pillar I, not Pillar II, not Pillar III.

Pillar I: Social safety net, not a real pension.

Let’s be honest: Pillar I is not a retirement savings plan. It’s a social assistance mechanism — and that’s okay! It’s like unemployment benefits, public education, or universal healthcare. It’s meant to be a safety net for the elderly, to ensure a minimum standard of living in old age.

But let’s stop pretending it’s a “contributive” system. It never was, and it never will be. It has never been financially sustainable. It runs on political promises, electoral cycles, and constant state patchwork. It’s been eroded consistently — especially through inflation, special pensions, and arbitrary decisions by the state.

So yes, it’s a socialist system — and that’s fine. But it’s not what people are told it is.

Pillar II: State-controlled investment? That’s not real investment.

Pillar II was supposed to be a privately managed pension fund. In reality, it’s state-controlled. And I’ve never trusted a system where the state tells me how to invest my own money.

That’s not investment. That’s just another political instrument.

I’ve always been certain that the state will eventually seize or redirect those funds — and so far, it’s doing exactly that. It controls where and how the money is invested, how and when it can be withdrawn, and whether we’ll even see it again.

I’m convinced we won’t. Pillar II was just electoral marketing.

In short, we need to rethink how we talk about pensions. We need to stop mixing the language of "social protection" with "financial independence".

What I Learned Losing a Million Dollars – A Modern Fairy Tale About Gambling in Business

I don’t read business books much anymore. I used to. Obsessively. At one point, reading felt like a compulsion—an intellectual sugar rush I couldn’t resist. These days, I prefer something sharper: peer-reviewed science, niche blogs, curated newsletters, specialized courses, and a healthy dose of GPT-fueled learning. Less time consuming, more frictionless, and far more adaptable to what I’m actually trying to do—learn and build.

But sometimes a book sneaks through the firewall.

What I Learned Losing a Million Dollars, by Jim Paul, came recommended by Sabin Gilceava.

This is an easy read - more of a business fable than a textbook. The story is compelling, a tale of gambling your way into (and out of) trading and business. It follows a tried-and-true formula: tell the reader simple but intriguing truths, sprinkle in some elementary insights from psychology and statistics, and package it all in a way that makes the reader feel smart. It’s accessible. It's a modern fairy tale - i.e. it’s about money.

It dances with ethical ambiguity. You keep wondering: is the author reflecting or justifying? It is not about value creation, nor business. It's about money, connections, bluffing, image, cheating, misrepresentation, risk, gambling, trading, speculation, money.

In that context, the introductory references to Edison or Ford are ironic. Please. Those men were engineers; they built things. 

That said, the book serves as a good reminder of foundational, state-of-the-art scientific and educational literature from psychology, economics, and statistics. The application of the five stages of grief (from pain management) to business loss is actually quite interesting. But like many books in this genre, it overstays its welcome, and sometimes exagerates with elementary truth until they become false. There’s a point where you realize you’re reading another 10-page explanation of why having a plan is better than not having a plan. And surely, both experience and research suggest that rigidly following an initial plan is usually a mistake, something the author simply ignores. Likewise, the value of objective over subjective decision-making is a repeated theme, in literature as well as in this book. Even though, surprisingly, it’s contradicted in the book’s very conclusion.

One quote stands out as a neat summary of the entire work:

“Most people who think they are investing are speculating. And most people who think they are speculating are gambling.”

Simple. Sharp. That wraps it up.

The great modern urban myth: no, AI doesn't replace programmers

AI doesn't replace programmers. It's a modern urban myth.

The net is full of stories about how AI/GPT writes full product code, and replaces programmers. 

It's an urban myth.

It sounds cool. But it's wrong.

AI/GPT is great at boring repetitive tasks. Great at searching. SearchGpt replaces successfully most manuals and documentation. It is even much faster and better than Stackoverflow.

It's also useless for solving any original or complex problem. It makes silly mistakes, writes redundant code, and doesn't really "understand" anything.

Yes, I write code, I love AI, we use it extensively, and I use GPT every day. AI is great. Technology is great.

But no. There is no "product" fully written by AI, by amateurs. 

It's a modern urban myth.

AGI and "true reasoning", vs "AI" and "reasoning. How society handles language mis-use and abuse

Obviously, current AI is not really intelligent, doesn't have "true reasoning" or "true understanding". And we may argue (scientifically) that the terminology is wrong. Which it is. 

But this will not change the way people use, and mis-use, words.

What we do, when words are mis-used or abused, is invent new words.

So, we say AGI (General Artificial Intelligence), and "true reasoning", to clarify that "AI" and "reasoning" are improper terms.