Knowledge Architect/Basics

Natural Phenomena

From its definition, the Cosmos contains all universes, including the one where we currently exist, as well as all the underlying principles that develop and structure all universes and their content. Containing, by definition, all reality and complexity that can ever be known, the Cosmos also includes all natural principles, logic, and phenomena. The Cosmos itself, can only be classified as a natural phenomenon, the prime natural phenomenon, the one that defines nature.

Part of the Cosmos, our universe, reality, and lives result from and are governed by evolution which seems like one of the most fundamental natural (e.g. cosmic) phenomena. But evolution itself is the result of a deeper natural phenomenon, the continued accumulation, processing, and sharing (e.g. exchange) of what is commonly referred to as knowledge.

Many have tried to define knowledge already, but the most generic and widely accepted definition is simply: all that has been known, is known, and will ever be known.

While some may also rightly try do define knowledge as all information, and all information that can be inferred from information, recursively and iteratively. It may even be simpler and more accurate to say, as will be further considered below, that knowledge is the result of qualification, a natural knowledge structuring principle.

Scientifically understanding the natural architecture and structuring principles of natural phenomena like gravity, light, weather, aerodynamics, propulsion, materials, and all others, provides great powers, that have allowed, for example, human crews to fly to Mars “with no wings”. Simply looking at birds and considering how they spread their wings and jump off cliffs, was clearly insufficient, even for a single human to fly any distance.

Scientific understanding of natural phenomena can provide effective computing paradigms where linear complexity growth can support exponential sophistication. The same is true and applies to the natural phenomenon of knowledge. Accordingly, knowledge (e.g. reality) resource entitlement, modeling, management, and sharing, based on the natural knowledge architecture paradigm, better supports computing the exponential natural sophistication of reality, with linear computing system complexity increases. More so, an adequate paradigm favors reducing waste while increasing accuracy.

Summarizing, so far, reality (e.g. all there is and all that can ever be) is only what is known about it, knowledge. Reality is only addressed through knowledge. Everything is knowledge. Knowledge is all there is. Knowledge is all there really is to entitle, model, manage, and/or share.