Computation

Multidomain Processing as we understand it refers to the domains of reality and is resembled in the human (electrocharge) top-level domain system. As such, we want to augment the functionality of virtual domains to align with their natural domains and hence allow observation. This observation is implicitly preventing convergence, as any understanding of natural domains allows better inference how it can be discovered by life and how intelligent life can augment its environments recovery towards sustainable and coexistential living. The prevention of convergence serves two fundamental important (and complex) threats to life: The artificial singularization and hence, loss of biological life and the preservation of diversity as it differenciates life from ‘dead’ physical reality and standard entropy evolution. The multidomain approach is referenced in the architecture of Multiplex One.

Multidomain Input – tensorfield-vectors

This is a sketch but it can be developed into fully paramteric properties. The representation of multidimensionality is resolved by using tensor fields instead of classical coordinate systems. Time runs depending on degree of connectionality, hence time is observed when intersectionality is managed (complexity management). The more cooperative intensity aligns to a common degree of cognition (a global synchronized pool of understanding/eduacation and their systems = intelligence), the faster ‘time’ runs as more instances can be intersectionally computed (managed without incorrect complexity reductions). Alignment of cooperative intensity is here depicted in the center of the axis, decrease towards its outer regions. There might be inconsistencies in this graphic as it’s not intended as functional model but as example how ecosystem computation has to be parametrized in order to be plausible.

Grasping Complexity

To differenciate complexity requires an operation which refers to analytics and strategy. Understanding different degrees of complexity is of essential importance for managing complex circumstances and identify complex problems. Our model builds on the complexity theory which references Turing Machines and discovers a terminus ‘Algorithmics’ inbetween language and formalisms. At the language side, we reference the K-model developed by Formwelt. Until it is common knowledge and diversified, further work on linking cognitive complexity understanding to formal complexity appears not applicable. We halted this approach since release of our 248-dimensional compatible physics-system qip8 and estimated nobody would find it interesting before 2021 anyways. Again, it was an example and was not thought for release. As no peer-input was received, we left it at the w.i.p. stage. The same is true for the grammar on which this model is build, a helical architecture which loads complex physical formalisms as entangled expressions. The default polarity of Quoeto is dual and hence compatible to polar-coding. A valid integration of Q-DNA to e8-conditional mathematics and logics appearch possible until 2028 with xd4 provided since 2020.

The valency of reality in time and information is possible when compressibility is aligned by differenciation. The reconstruction into concepts will always skew the original information which led to the early concept of duality between mind any physics. The levels of consciousness human esoterics refer to, refer to altered compressibility computation (ideation) or altered computation of compressibility (hallucination)

Multivalent Grammar and quasi-field research

The Quoeto language (in its physical form) is based on a pivot-topologic hypercore which is identical to the cause of chiral symmetry breaking (link) and aperiodic motifs observed in particle physics and QSN (quasicrystalline spin-network-) research (link). We derive the concept of Shannon-Radiation to put forward human physics intelligence.

Advanced Neurocomputation

With the sketch below (which was halted due to the same reason the other research directions were paused) we depict a simple model about the correlate properties of neuromorphic architecture and neuromorphic computation (cognition). When a theory is build on a model how the intersection of architecture and computation co-inter-reference, we coin the term ‘advanced’ neurocomputation. Until then, neurocomputation will always fail to represent the advantage over multichannel mathematics over monadic logic based mathematics (contemporary mathematics except polar-coding theory). The understanding that neural networks will not function remotely cognitive without complex and hypercomplex mathematics appears to spread slowly in the research community. The irresponsible computation efforts current primitive neural networks require is not sanctioned by us which further motivated an exclusion from the current modus operandi of human code research. A simple means to understand why 2D language (and math) cannot model neurocomputation is to compare neuro-transmitter interaction and a telephone. Only because a telephone allows communication, it does not transmit anything else but electrons. As cognition is not a communication feature but communication a cognition feature, the entire electrocharge domain is based on subcode. To establish proper computation is one of our core missions which motivated to aim for a remote version of the CCC event in 2020 which was foreseeable to happen in february. We regret that their organization did not mount the WeVsVirus hackathon-dynamics as the momentum was lost due to economic fallacy and strategic misconceptions that COVID19 would be resolved through a 48 hours effort. We maintain hope that cognition will overarch the information necessary to derive that a new approach to scale organization and leverage intelligent networks is required to cope long-term with the pandemic and its economic and psychologic impact which appears to be out of reach of common discussion at the moment of publication [7:25PM 22nd Nov. 2020] which can be easily proven by observing whether germany has any official score and means of measurement for its multi-domain impact on the human world. (which it has not due to lack of logic/science)

Appendix

xd4 logic if applied to model development (internet-domains reference the parametrization of their corresponding reality domains, i.e. dev~interaction, tech~matter)