Three Parameters of Collapse: Is AI Putting Science in Checkmate?

Part One. AI Ignites the Collapse of Science: The Theory of Misunderstanding
🎙️ Science Collapse: The Limit of Reduction — Exposing the Great Illusion of Knowledge

What if everything you think you know about science is just a ritual for self-reassurance?
What if every word, every term, every academic tome is just a blind filter that slices reality into fragments — until there’s nothing left but a noisy echo?

In this episode, we begin dismantling the greatest myth of modern civilization: the belief in reduction as a path to truth.
You’ll see how language shrinks the world into a caricature, how conceptual thinking drains meaning dry, how every new theory multiplies ignorance, turning science into an endless maze of questions without answers.

We’ll break down:

The 7 levels of reduction that destroy the original experience.

Why every formula is just a door — with five more behind it.

How “progress” actually speeds up the decay of knowledge.

Why working technologies are just convenient black boxes — destined to explode one day.

This isn’t philosophy for philosophy’s sake. This is an engineering theory of misunderstanding — the first attempt to prove that modern knowledge devours itself, reducing any “understanding” to zero.
All the calculations, formulas, and collapse parameters are detailed in our article on Telegram — link under this video.

You can laugh and close this video. Or you can risk it — and open the first door.
But remember: behind it, there will always be five more.

Enjoy the dive — and welcome to a corridor with no exit.

A detailed article on this topic is available in our Telegram channel. To find it, just search:
“AI Ignites the Collapse of Science: The Theory of Misunderstanding”
Part Two: The presentation of the Theory of Everything.
Channel link — in the profile bio.

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🔍 Disclaimer: Pure Logic vs. Human Illusion
This is not a declaration of belief or a manifesto. It’s an attempt to step beyond personal preferences and look at reality through the lens of systemic reasoning.

My compass is logic and verifiable facts — not sympathies, intuitions, or desires.
But I’m human. Which means:

• I’m subject to cognitive biases
• My conclusions may be wrong — in scale or structure
• I have blind spots, thinking habits, and illusions of control
• I can’t know the full context: some errors may stem from unknown variables that are critically important yet invisible in the moment

So — don’t believe. Verify.

Use AI (ChatGPT, Claude, Gemini) — but not as infallible truth engines.
They may sound confident — and still be wrong, reflecting data biases.
Compare their outputs — and check them against testable sources.
Break your own beliefs — especially the ones you’re emotionally attached to.

Truth isn’t about being right.
Truth is about the willingness to let go of what’s false — even if it’s comforting.

Roughly 62% of people, according to Anderson (1980) and Nyhan (2010), continue to believe falsehoods even after being shown they are wrong.
But it’s not about numbers.
It’s about the human tendency to cling to familiar illusions rather than face inconvenient truths.

Look for contradictions.
If logic dismantles your worldview — that’s not collapse. That’s cleansing.

Science is not a dogma.
It must be willing to doubt even itself.

I’m not trying to convince you.
I’m trying to start a process of thinking.

If you find flaws in my reasoning — tell me.
That’s not my defeat — it’s our shared victory over illusion.