How to define information

Don’t go to universities.

Don’t get in touch with big biz.

Except for learning.

Just try to do a good job, not to make career – why? To make career you have to be a winner and a winner is never free. (S)he has to follow the mainstream to be able to win. But you have to have experience with truth and reality, you have to be a rebel to detect information – and you have to be curious.

You have to understand reality since your childhood: therefore you must not be a wealthy child, because wealthy children never learn reality, too much protection creates a pampered mind.

But you shouldn’t be too poor, because you have to be able to learn mathematics and physics (political aside: therefore you have to be lucky enough to grow up in a country, where good education is offered by the state without payment and without things like “elite schools”, as if human intelligence is something class-specific: the “Brahmans” are clever, the “Parias” are stupid and not allowed to learn - a waste of intelligence which no country can afford today).

You have to be curious to ask – but you also have to be something like a dreamer to feel the need to understand, even when nobody else is asking. You have to wonder about this miracle “time” and “life”, you have to be able to spend time for nonsense...

non sense...

n o n

s e n

s e

nonsense fades away in...

what?

the word doesn’t make sense if you focus on the letters – imagine that! Think about that, say it:

“nonsense”

“n” – wait – “o” – wait – “n” – wait - “s” – wait – “e” – wait – “n” – wait – “s” – wait – “e”.

Where’s the meaning now? What is it, that you can “understand” now? N? S? E?

What’s left after splitting the word into its particles? Hmmm?

But that’s only one of many steps to understand information.

Because the meaning of words fading away makes you accept without hesitation that particles fade away into the quantum noise.

The Queen of Mathematics, Functional Analysis, teaches you that structure creates structure – or fades away.

After a while you realize, that any order...

just fades away if you focus too closely on it.

If you try to catch something – to bind it in stable chains, to store it in perfect stability, to analyze it in its defining atoms – it fades away like the atoms faded away into those interesting “particles” quarks and strings.

But that’s nothing worth to consider, isn’t it? Do your job, program objects working together via messages and don’t care about information, that’s not your job, that’s the job of the clever and wise, the experts.

The Binnigs and Chaitins, the professionals of big biz and rich universities.

All those thousands and thousands and thousands...

not able to simply explain information – offering instead thousands of different definitions of information.

Where’s the 1001st definition, the lord of the definitions, the one, “to rule them all, to find them, to bring them all, and bind them”?

Never asked, why all those masterminds can’t understand information?

You should – because Bertrands Paradox teaches you one simple thing: information about things helps you to better understand them, to be able to better foresee, how they behave – or in simple words: how the results of their changes may look like. And it doesn’t matter if that information seems to be important or not: it is important.

And to prove Bertrands Paradox: The question, why no mastermind was able to understand information leads to an interesting result. Because those masterminds are neither blind nor stupid, the problem has to be not difficult. Difficult problems are problems made for masterminds, they solve them with pleasure.

So the problem of information has to be – that it is simple. So simple, that experts can’t understand it anymore. Therefore they create 1000 definitions of a cute, complex information they can handle.

They create webs of formula and interfaces and standards and best practices to prove how difficult their job is. But none of their words and definitions helps you to understand the formulas and interfaces and standards and best practices of other experts well knowing what information is.

Whether you are physicist or biologist, computer scientist or linguist – does matter.

The information of the computer scientist doesn’t fit with the one of the linguist, the quantum information doesn’t really explain the design of the human brain.

So what do all those “informations” have in common?

The construction of the star signs of Europe and China is the same – what does this tell you? The fish and the bird is part of the ancient art of Europe, China and Egypt – what does this tell you? The colors Red and White and Black are spread over the whole wide world, the same with the five-pointed star, wellknown symbol of America and Russia (btw: an ancient symbol for a human body with head, arms and legs) – what does this tell you?

Information is like a spider, spinning webs all over the human mind, the human culture, the Earth and Solar System, the whole universe.

Nobody can understand all those different, complex, intertwined webs, creating connections from here to there, from the small to the large, from yesterday to tomorrow, creating history and complexity and surfaces which seems to have no similarities.

So don’t focus on the webs.

Focus on the spider.

Parting the Sea

The Set.

What a wonderful construct a set is, simply a collection of something which only has to be distinct - and nevertheless, “It can be viewed as both the foundation upon which nearly all of mathematics can be built and the source from which nearly all mathematics can be derived.”

You don’t like sets? They remind you of school? Annoying, deadly boring?

Think again, you are grown up now.

Just focus. Forget about native or axiomatic theories, forget about paradoxes, forget about cardinality, unions or intersections: focus on the set.

A collection of something distinguishable.

How can such a simple concept be so important to mathematics? Something put together and voila, it’s a set by the touch of a magic wand?

How about a glass of water? Do the molecules build a set? No, they don’t, just because we can’t distinguish one H₂0 from the other.

But if?!? Yes, if we could, it would be a set, really.

For nothing more than separating the water from the rest of the world into a special glass and be able to “call them by their names” – we would have created a set.

Imagine that!

Imagine, how much you know about things, if they form a set, because the fact, that the things in a set have to be unique proves you a very, very important point: you have to be able to measure something, some distinctive value like identity to distinguish one set member from the other.

But that’s just a part of the information you got from sets. Because the simple little word “collection” shows you something else: You must be able to decide, whether something belongs to that collection or not.

Again, you must be able to measure something to decide, whether it’s part of the collection.

Look at our water glass of magically distinguishable H₂0-molecules. “Water in my glass” defines the collection. So air or children or cars don’t fit with the definition – and water? Water has to be in “my glass” to belong to my set. My glass can be defined by its space-time curve or by form or matter, the keys you choose to measure can be anything: They just have to be unique...

and stable.

Remember? It wouldn’t make sense to use changing values as identity, because after the change, how could you track the changes?

That’s the reason, why a set is so important to mathematics – and to each and every information processing system or procedure: it defines identity and properties...

it defines measurability: the precondition for mapping systems.

It’s the “zero-point-information”, the point, where you can stand to structure the whole wide world in two distinct parts: inside the set, outside the set.

And inside the set, you know, there is identity – therefore you can track movings, you can follow events, you can construct relations, you can map and store, retrieve and compare.

A set creates order in a random world.

That’s the magic.

Pars Pro Toto

The first thing to say about information is:

forget what you know. Everything you're told about.

Because it's just a piece of the puzzle: (often) correct, right and proven, nevertheless just a piece.

Why?

We think of information as state-based or object-based – and that’s understandable. We have information, get information, store information, retrieve information, send information, map information, measure information...

so information must be stable: must be storable, must be mappable, must be sendable and retrievable – since it is describable by states and stable objects and their connections.

Why storability or mappability or measurability needs stability?

Just consider, how it is done: to store things you put in in a “store” and after a while, the things should be as they were before. If they had changed, your store isn’t that good. To measure things you have to compare it with some other thing of the same kind, defining the “unit”, to be able to say: “oh, that’s 4 times the unit”. And to map things you have to postulate some attributes, which are part of the mapped objects – and part of the capabilities of your mapping system, so that you can use them to link a real object with an “image”. And after a while, when another object of the same kind happens to cross your path you can decide if it is the same as before: just by comparing the stored values of the describing attributes with the newly measured data.

So the basic precondition for all our measuring and formulating, thinking and understanding is: stability.

And states are stable – they may be replaced by another state, but the state itself is based on values and values are like numbers: eternal.

The question never asked, however, is: Why should information itself be eternal? Only because we need it to be? Only because we can’t think outside the box, can’t think in other categories than mappable states and their mappable relations?

Pars Pro Toto.

We often describe whole things by characteristic parts, that works fine. That’s called “symbolism” and works even if the symbol is not really part of the thing (“by proxy”): the basic nature of natural laws or our language. That’s also called “abstraction”: “Abstraction uses a strategy of simplification of detail” – Pars Pro Toto.

But, alas, in case of information...

we did simplify too much.

Because we forgot that each and every state – in reality – has to be entered.