Legal matter
Because the

we have made the following decisions:

C.S. has decided to withdraw all announced modifications of the original and unique work of art titled Ontologic System and created by C.S., which are legally required for opening our Ontologic System (OS), and allowing and licensing the performance and reproduction of certain parts of our OS.

Our Society for Ontological Performance and Reproduction (SOPR) has decided to withdraw all regulations discussed, announced, and introduced.
Therefore, a legal agreement, a legal framework, and a legal certainty other than the

do not exist without the consent of C.S. and our corporation.

Our SOPR remains a collecting society, and the end users or consumers remain members of our SOPR.
But our business unit Ontonics has suspended those activities of our SOPR, which have become obsolete without said modifications of our OS, until said essential demands, prerequisites, and requirements for opening our OS, and allowing and licensing the performance and reproduction of certain parts of our OS have been met, fulfilled, satisfied, executed, realized, and so on by all entities concerned.

The scopes and terms for licensing the performance and reproduction of certain parts of our OS will be decided on a case-by-case basis of a legal entity and state-by-state basis of a statutory union by following best legal practices and industry proven actions.

Obviously and as we already worked out in the past, the front line runs very deep through the business goals, strategies, and processes of fraudulent and even serious criminal entities, as the following short lists already show:

Integrations of the fields of

Creations of (the foundations of) our fields of

• (utility) Technology as a Service (TaaS) technologies (TaaSx), including (utility)
  • Platform as a Service (PaaS) technologies (PaaSx),
  • Service as a Service (SaaS) technologies (SaaSx), and
  • Data as a Service (DaaS) technologies (DaaSx),

• Peer-to-Peer Virtual Machine (P2PVM) for smart contract transaction execution,

• Data Center operating system (DCos),

• Personalized Assistant that Learns (PAL), including Reflective Agents with Distributed Adaptive Reasoning (RADAR) and Cognitive Assistant that Learns and Organizes (CALO), also wrongly called Siri, Alexa, Cortana, Bixby, Google Assistant, etc., and
• Conversational Intelligent Personal Assistant (CIPA),

If a State-Owned Enterprise (SOE) is granted an allowance and license for the performance and reproduction of certain parts of our OS, then said allowance and license is only granted in the scope of the jurisdication of its headquarter.

Either we have an environment with a rule-based law and order and a democracy, where

or said environment with such a concept and such an idea does only exist on paper and in hot air.

02:01 UTC+1
Designations and sales other than the ones of C.S. prohibited

have to be called, labelled, branded, communicated, advertised, sold, and so on by using our designations

See also the note SOPR # of today above.

05.January.2023

03:01 UTC+1
Other app stores than our MfE prohibited

All Ontologic Applications and Ontologic Services (OAOS) have to be sold and distributed exclusively on our Marketplace for Everything (MfE), also wrongly called app store.
All authors of OAOS have to publish their OAOS through our corporation on our MfE exclusively.
Authors of OAOS get 30% or maybe some more percentage of the revenue generated with said OAOS on our MfE, which is much more than the 20% authors get for writting and publishing a book.

03:01 UTC+1
Use of our OS for military use prohibited

The original and unique ArtWorks (AWs) and further Intellectual Properties (IPs) included in the oeuvre of C.S., including our Ontologic System (OS), are allowed and licensed for private and commercial performance and reproduction respectively use only.
Therefore, the use of our original and unique AWs and further IPs for military facilities, technologies, goods, and services, including military equipment, by other entities than C.S. and our corporation is in clear breach of our terms and conditions of

applicable to

alike worldwide.

Said illegal military misuse include the

• Joint Enterprise Defense Infrastructure (JEDI) and
• Joint Warfighting Cloud Capability (JWCC).

Companies involved in such an illegal military misuse of our original and unique AWs and further IPs face the

06.January.2023

16:46 and 26:26 UTC+1
Illegal Ontoscope clone iPhone now dead?!

It depends on the company Apple, or being more precise, if Apple complies to the

But sadly to say, we are forced to demand proper designation, labelling, branding, marketing, distribution, sale, and so on in relation to the original and unique ArtWorks (AWs) and further Intellectual Properties (IPs) included in the oeuvre of C.S. by court order worldwide, due to the

and therefore this legal action will happen in the next weeks, definitely, and most potentially will have significant implications on illegal plagiarisms of our original and unique work of art titled Ontologic System and created by C.S., including the

In former notes we have already

Also note that we have not forgotten the

If U.S.American entities refuse to comply with the

then we also have to

if they are based on the original and unique ArtWorks (AWs) and further Intellectual Properties (IPs) included in the oeuvre of C.S..
And of course we will get these prohibitions, as is the case with for example the prohibition of the produciton, distribution, provision, sale, and so on of our Ontoscope on Wheels by companies, like for example Porsche SE/Volkswagen, General Motors, Toyota, and Co., in the U.S.America, the European Union, the P.R.China, and other locations.

See also the notes

which are legally secured and protected by the granting of freedom of expression, self-expression, arts, and moral right of C.S., specifically modification, naming, and presentation, which cannot be circumvented by any dirty trick.
Also note that we do not need to consider and enforce the copyright of C.S. at this point at all, which nevertheless will become matter of further legal actions.

All those bad actors thought that they could get away with the individual illegal acts, because of their power, size, and cunning, even in court. But now the whole package is on the table and it has a completely different quantity and quality, which shows once again that it is not only a matter of anti-sociality, stupidity, and arrogance, but still also a matter of intelligence, diligence, and conscientiousness. In fact, if one constructs such a huge house of card and makes oneself so vulnerable, then another one only needs to pull some very few cards to destroy the whole structure. It is so incredibly easy. And now we are only beginning with just hammering on the others and whacking them away in the good old Wild West and Silicon Valley style. :)

Eventually, all of the rights, properties, reputations, and momenta, as well as follow-up opportunities of C.S. and our corporation will be reconstituted, restituted, and restored in one way or another, as we always crystal clearly said, demanded, and explained.

By the way:

16:46 UTC+1
Ontoscope Further steps

We are considering to ask the 20 largest manufacturers of handheld and wearable mobile devices to produce our exclusive Ontoscope for our business units exclusively. It might be their only chance to remain in this business.

See also the

08.January.2023

06:37, 08:03, and 29:09 UTC+1
Ontoscope Further steps

We are considering several measures regarding the production of our original and unqiue, copyrighted, and prohibited for fair use work of art titled Ontoscope, created by C.S., and exclusively managed and exploited by our corporation with the consent and on the behalf of C.S., specifically the

of our Ontoscope.

In case of the

of our Ontoscope, we will consider the following options for decision making:

In case of the

of our Ontoscope, we will consider the following options for decision making:

In case of the

of our Ontoscope, we will consider the following options for decision making:

In case of the

of our Ontoscope, we will consider the following options for decision making:

We already have informed manufacturers of mobile devices and vehicles to make preparations. This is now coming in the next few months and every company, that still refuses to comply with the

will get a cease and desist letter from us and a cease and desist order by a court, and eventually will be pushed out of the market.
It is that simple. :)

In this regard, our Hightech Office Ontonics is working out and finalizing the last details of our legal strategy, so that we are able to enforce the rights and properties of C.S. and our corporation as fast as possible and without another delay.

Please also keep in mind that

• opening our original and unqiue, copyrighted, and prohibited for fair use work of art titled Ontologic System, created by C.S., and exclusively managed and exploited by our corporation with the consent and on the behalf of C.S., and
• allowing and licensing the performance and reproduction of certain parts of our Ontologic System (OS) with its Ontologic System Architecture (OSA), Ontoverse (Ov), and Ontoscope (Os),

have been withdrawn by C.S., but

• utilizing the exclusive infrastructures of our corporation, and
• paying the triple damage compensations

are still mandatory and demanded by C.S..

Ontologic Applications and Ontologic Service Providers (OAOSPs) in general and Communications Service Providers (CSPs) in particular have to take care that they

• configuration and management of their
  • subnet structures in our Ontologic Net (ON),
  • subweb representations in our Ontologic Web (OW), and
  • subspaces, subenvironments, subworlds, and universes respectively realities in our Ontologic uniVerse (OV),

  which collectively are our Ontoverse (Ov) and New Reality (NR), and

• implementation and publication of their Ontologic Applications and Ontologic Service (OAOS) in our Marketplace for Everything (MfE),

because there exists only our one Ontologic System (OS) with its Ontologic System Architecture (OSA), Ontoverse (Ov), and Ontoscope (Os), and

We also would like to give the friendly and strong recommendation to work directly with our corporation and our business units to get the best Licensee eXperience (LX) and provide the best User eXperience (UX).

See also the notes

which are legally secured and protected by the granting of freedom of expression, self-expression, arts, and moral right of C.S., specifically the exclusive right to decide about modification, naming, and presentation, which cannot be circumvented by any dirty trick.

10.January.2023

05:34 UTC+1
Evidences of crypto Ponzi scheme plot

We have reviewed the events, which happened in relation to the companies working in the cryptologic technology industrial sector on the basis of the smart contract transaction protocol and the blockchain technique in the period of the years 2015 to 2022.
Investments, loans, and other actions, as well as the resulting collapse of the whole so-called crypto ecosystem, or better said house of cards or literally spoken chain of tokens, and bankruptcies of the leading companies suggest a conspiracy and a plot to infringe the rights and properties of C.S. and our corporation by

But the fiasco is not limited to the private cryptotulips concerned, because the whole scandal is also directly connected with the governments, commissions, federal authorities, universities, research institutes, companies, artists, other individual persons, cliques, and other entities of several federal states of the United States of America (U.S.A.), member states of the European Union (EU), and other individual sovereign states worldwide.

The situation is very similar to the conspiracies in the fields of

And for sure, we are not ready with all of them.

06:54 and 10:50 UTC+1
Fair goes first, but fairness without limits is unfair

Despite we have withdrawn all announced modifications of our original and unique work of art titled Ontologic System and created by C.S., which are legally required for opening our Ontologic System (OS), and allowing and licensing the performance and reproduction of certain parts of our OS, our maxim and credo of Fair, Reasonable, And Non-Discriminatory, As well as Customary (FRANDAC) entrepreneurial behaviour still remains.

In this relation, we would like to note at first that certain blacklistings make no sense anymore, because the issue respectively disputed matter is solved by the

and entities are allowed to implement their OAOS, if they also publish them on our exclusive MfE.
For example, the company Microsoft is allowed to

• operating systems respectively variants of our Ontologic Core (OntoCore or OC) and
• movements respectively raw versions of our OS,

and

under our FRANDAC terms and conditions, but Microsoft is not allowed to

which means for example no Microsoft Windows, no Microsoft Azure, and no Microsoft 365.
The same holds for other companies, like for example Alphabet (Google), Amazon, Apple, Meta (Facebook), Oracle, IBM, Tencent, Alibaba, Baidu, Samsung, Huawei, Xiaomi, Cisco, Intel, Nvidia, Qualcomm, Epic Games, etc., etc., etc., and their technologies, goods, and services based on or dependent on our OS. :)

In this relation, we would also like to note that we

because eventually we are the only Ontologic Applications and Ontologic Services Provider (OAOSP) and therefore there are no competitors, but only creators, authors, developers, implementers, programmers, customers, and users represented to other entities by our corporation exclusively.

In this relation, we would now like to note that indeed a justified question exists regarding the handling of public signals and data, and open signals and data sources respectively publicly available signal streams and datasets, and openly available signal streams and datasets, which are common items, obviously, doubtlessly, and definitely.
The proposed compromise respectively agreement of our Society for Ontological Performance and Reproduction (SOPR) for making said withdrawn modificatons of our OS comprises the regulations that

• legal scope of our Ontologic System (OS),
• domain of our New Reality (NR) respectively
• sovereign space of our Ontoverse (Ov), also known as our digital state OntoLand (OL).

A prominent example are raw signals and data, informations, knowledge bases, models, and algorithms related to the fields of geography and Geographic Information System (GIS), but also our OS with its Ontologic Net (ON), Ontologic Web (OW), and Ontologic uniVerse (OV), which collectively are our Ontoverse (Ov) and New Reality (NR), as well as the related

For a better understanding, we have to recall that there exists a white, yellow, or red line between the original and unique ArtWorks (AWs) and further Intellectual Properties (IPs) included in the oeuvre of C.S., which are exclusively managed and exploited by our corporation with the consent and on the behalf of C.S., and all the rest, specifically because of the

• is the proven creator and holds at least the moral rights for said original and unique AWs and further IPs in addition to certain copyrights, and also
• has no need and no interest to sell or give away any rights and properties, but has the power and interest to exercise all rights and control all properties,

and

which are further legal requirements for modifying and opening our OS.

We also have to mention that we wanted to avoid to draw said white, yellow, or red line at the courts, because on the one hand it is not optimal for the benefit of the public and on the other hand it becomes very restrictive and quite expensive for certain companies.
But finally, we had to conclude that too many entities are too incompetent or just too stubborn to comply with any limit and to understand our perfect solution with our SOPR, as we also mentioned several times in the past.

Both, the question regarding said common items and said unruly behaviour, are supporting our decision to withdraw said modifications and introduce stricter regulations, for example in relation to the performance and reproduction respectively implementation and publication of certain interfaces of our Ontologic System Architecture (OSA), which nevertheless are prohibited for fair use, and the allowance and licensing of the performance and reproduction of OSA interface by State-Owned Enterprises (SOEs) and militaries, as known as Armed Forces (AF).

Are there any questions by the U.S.American Federal Trade Comission (FTC) and European Comission (EC) regarding legal monopoly? If this is the case, then we are always happy to provide education, explanation, and clarification, as well as itemization.

11.January.2023

05:13 UTC+1
Does not look good for Microsoft and Co.

Unsurprisingly, we found more evidence, that support our view that the company Microsoft is an illegal monopoly (e.g. abuse of market power) and serious criminal actor (e.g. espionage, criminal copyright infringement, blackmailing, wire fraud, securities fraud, commercial fraud, lobbyism scam, corruption, conspiracy, and plot).
In fact, Microsoft is

as we have already shown multiple times and documented by maybe 100 or more individual cases, which crystal clearly prove all of our allegation in relation to more than 20 infringements of national and international laws, regulations, and acts, as well as agreements, conventions, and charters.
Our investigations also show that Microsoft and its accomplices have gone totally beserk in the last 2 years, as we have also shown with other companies and their partners in crime, because only blunt stealing and conducting other crimes in public and daylight are applyable. In fact, Microsoft is making war against C.S. and our corporation, and does not care for law and order, and other achievements of civilized societies anymore.
That issue cannot be solved by monetary penalities and other measures, but only by the complete break-up, as we always said, explained, and demanded.

But as we always said in this relation, Microsoft is not alone and a crackdown of national cliques and mafias is inevitable to solve that chaos.

06:41 and 09:26 UTC+1
More evidence transformer model, etc. based on OS

We quote a report, which is about the field of generative SoftBionics and was publicized on the 10th of January 2023 (yesterday): "[...]
As a Google engineer, he held a few credits that allowed him to run experimental software across the company's vast network of computer data centers. But these credits would grant only a small fraction of the computing power needed to train his chatbot. So he started borrowing credits from other engineers; as the system analyzed more data, its skills would improve by leaps and bounds.
Initially, he trained his chatbot using what is called an LSTM, for Long Short-Term Memory - a neural network designed in the 1990s specifically for natural language. But he soon switched to a new kind of neural network called a transformer, developed by a team of Google A.I. researchers that included [a second Google engineer].
Unlike an LSTM, which reads text one word at a time, a transformer can use multiple computer processors to analyze an entire document in a single step."

Comment
We have already explained that the so-called transformer, reformer, and transducer (e.g. perceiver) model and other models are based on the fields of Machine Learning (ML) and Artificial Neural Network (ANN), specifically MultiLayer Perceptron (MLP), and also concluded that such models are also based on our Evolutionary operating system (Evoos) and our Ontologic System (OS) (to a significant extend somehow).
With this statement about multi-processing or multiprocessing, which is also listed explicitly in the Feature-List #1 of our OS in direct context to ML, ANN, MLP, and so on, and integrated by our Ontologic System Architecture (OSA), we get another first-hand confirmation of our claims and explanation straight from the horse's mouth.

Add anything related to the fields of

• Geographic Information System (GIS),
  • digital maps, digital globes, etc.,

  and

• smart guidance system,

• Graph-Based Knowledge Base (GBKB) or Knowledge Graph (KG),

• Personalized Assistant that Learns (PAL)
  • Reflective Agents with Distributed Adaptive Reasoning (RADAR) and
  • Cognitive Assistant that Learns and Organizes (CALO),

also wrongly called Siri, Alexa, Cortana, Bixby, and so on,

and the infringement of the rights and properties (e.g. copyright) of C.S. and our corporation becomes even more obvious and proven.

06:35, 08:12, 12:00, 13:57, and 19:31 UTC+1
Further steps and Ontologic Net Further steps

We looked at Segment Routing (SR) technologies (SRx) and their relation to our Ontologic System (OS), specifically our creations or foundations of the fields of

In the following sections we quote publications in relation to the fields of

• Wireless Ad hoc NETwork (WANET),
  • Mobile Ad Hoc NETwork (MANET),
• mesh network, and
• sensor network,

At first, we quote an online encyclopedia about the subject Source Routing (SR or SourceR): "In computer networking, source routing, also called path addressing, allows a sender of a packet to partially or completely specify the route the packet takes through the network.[1 [Source routing in computer networks. [1st of January 1977]]] In contrast, in conventional routing, routers in the network determine the path incrementally based on the packet's destination. Another routing alternative, label switching, is used in connection-oriented networks such as X.25, Frame Relay, Asynchronous Transfer Mode and Multiprotocol Label Switching.
[...]
Many high-performance interconnects including Myrinet, Quadrics,[2 [Adaptive Routing Strategies for Modern High Performance Networks. [2008 or later]]] IEEE 1355, and SpaceWire support source routing.

Internet Protocol
In the Internet Protocol, two header options are available which are rarely used: "strict source and record route" (SSRR) and "loose source and record route" (LSRR).[3] Because of security concerns, packets marked LSRR are frequently blocked on the Internet. If not blocked, LSRR can allow an attacker to spoof an address but still successfully receive response packets by forcing return traffic for spoofed packets to return through the attacker's device.[4]
In IPv6, two forms of source routing have been developed. The first approach was the Type 0 Routing header.[5] This routing header was designed to support the same use cases as the IPv4 header options. Unfortunately there were several significant attacks against this routing header and its utilisation was deprecated.[6] A more secure form of source routing is being developed within the IETF to support the IPv6 version of Segment Routing.[7 [IPv6 Segment Routing Header (SRH). [20th of July 2017]]]

Software-defined networking
Software-defined networking can also be enhanced when source routing is used in the forwarding plane. Studies have shown significant improvements in convergence times as a result of the reduced state that must be distributed by the controller into the network.[8 [Source Routed Forwarding with Software Defined Control, Considerations and Implications. [2012]]][9 [SDN State Reduction. [7th of March 2013]]]

[...]"]

Comment
We are missing dates, which is often the case, when the public should be misled about the existence or relevance of prior art, specifically our Evolutionary operating system (Evoos) and our Ontologic System (OS).
We also have the impression that the truly interesting features and functionalities are based on our Evoos and our OS, SR-MPLS and SRv6 with our without SDN, as shown with the existing dates, which is often the case and proves the originality and uniqueness of our prior art, specifically our Evoos and our OS.

We also quote an online encyclopedia about the subject Scalable Source Routing (SSR): "Scalable Source Routing (SSR) is a routing protocol for unstructured networks such as mobile ad hoc networks, mesh networks, or sensor networks. It combines source routing with routing along a virtual ring, and is based on the idea of "pushing Chord into the underlay".[1 [Pushing Chord into the Underlay: Scalable Routing for Hybrid [Mobile Ad hoc NETworks (]MANETs[)]. [21st of June 2006]]]
[...] [2 [A Self-organizing Routing Scheme for Random Networks. [31st of May 2005]]]
[...]"

We also quote the document titled "Self-Stabilizing Ring Networks on Connected Graphs" and publicized on the 31st of January 2005: "Abstract
Large networks require scalable routing. Traditionally, protocol overhead is reduced by introducing a hierarchy. This requires aggregation of nearby nodes under a common address prefix. In fixed networks, this is achieved administratively, whereas in wireless ad-hoc networks, dynamic assignments of nodes to aggregation units are required.
As a result of the nodes commonly being assigned a random network address, the majority of proposed ad-hoc routing protocols discovers routes between end nodes by flooding, thus limiting the network size. Peer-to-peer (P2P) overlay networks offer scalable routing solutions by employing virtualized address spaces, yet assume an underlying routing protocol for end-to-end connectivity.
We investigate a cross-layer approach to P2P routing, where the virtual address space is implemented with a network-layer routing protocol by itself. The Iterative Successor Pointer Rewiring Protocol (ISPRP) efficiently initializes a ring-structured network among nodes having but link-layer connectivity. It is fully self-organizing and issues only a small per-node amount of messages by keeping interactions between nodes as local as possible.
[...]

Introduction
Autonomous systems like ad hoc and sensor networks require protocols which make the system self-organizing. A routing protocol, for example, should be able to cope with self-assigned random node addresses and to scale reasonably with the network size at the same time. Routing scalability traditionally is achieved by introducing a hierarchy in the address structure. The hierarchy is dependent on the position of the nodes in the network graph. In autonomous networks, the hierarchy thus has to be established dynamically, for example using clustering protocols. Still, as nodes commonly have self-assigned random network address, the majority of proposed ad-hoc routing protocols (see for example [Per00]) performs route discovery between end nodes using some variant of flooding. This approach is limited in its scalability. Although Peer-to-Peer (P2P) systems are mainly known from the various file-sharing applications, their main benefit is that they offer scalable routing in a virtualized address space [CF05b].
Structured overlays like Chord [SMK+01], Pastry [RD01], and others are well-known examples of P2P systems. Here, nodes also have self-assigned random addresses, however, overlay addresses. These systems assume the prior existence of a network-layer routing protocol.
We investigate cross-layer solutions where scalable routing in a virtual address space is implemented as network-layer protocol by itself. The Iterative Successor Pointer Rewiring Protocol (ISPRP) [CF05a [ISPRP: A Message-Efficient Protocol for Initializing Structured P2P Networks. April 2005] is our first step towards this. It is able to build a basic ring network on top of a network in which nodes only have link-layer connectivity. Once this ring has been established, messages can be routed between arbitrary nodes. The key concern with ISPRP was to limit the amount of messages required for the initalization as opposed to previously proposed flooding-based approaches [(e.g. DPSR cross-layer approach)] [HDP03 [Exploiting the Synergy between Peer-to-Peer and Mobile Ad Hoc Networks. 2003], PDH04 [Ekta: An Efficient DHT Substrate for Distributed Applications in Mobile Ad Hoc Networks. December 2004]]. This is done by locally restricting interactions and message exchanges to places where inconsistencies occur. Thus, ISPRP produces only very low overhead.
In this paper, we present a correctness proof for ISPRP. Moreover, we show that ISPRP is self-stabilizing [Dol00] in the sense that the protocol lets a (connected) network converge into a globally correct state starting from an arbitrary state within a bounded amount of time. Thus, ISPRP is able to initialize a routeable network among freshly deployed nodes like it is required in a sensor network.
[...]

Related Work
Other authors have also considered building a network-layer routing protocol using P2P techniques [EFK01 [PeerNet: Pushing Peer-to-Peer Down the Stack. February 2001], For04 [Unmanaged Internet Protocol. January 2004]]. [...] In contrast to our ring-based system, their system uses hierarchical, tree-based routing. They do not consider small nodes with limited capabilites like in sensor networks, but aim at the Internet.
Hu et al. propose to use the Pastry overlay for unicast routing in ad-hoc networks, where routes between virtual addresses are discovered using the DSR routing protocol [HDP03, PDH04]. Their work differs from ours in that we do not require all nodes to flood the network in order to discover routes.
[...]

Problem Description
[...]
In our cross-layer design and the P2P scenario, however, there are no dedicated routers, and the nodes themselves take responsibility for routing messages. With randomly assigned addresses, storing the above-mentioned information leads to huge memory requirements and protocol overhead, as next-hop information cannot be hierarchically aggregated, which is a common practice in fixed networks like the Internet. To avoid this problem, another option is to use source routing. There, message headers contain an enumeration of all the nodes along the path. Hence, forwarding nodes do not have to maintain any routing information, but message sources need to know the routes to all destinations they communicate with.
[...]

The Iterative Successor Pointer Rewiring Protocol (ISPRP)
The ISPRP was designed with two key aspects in mind: simplicity and efficiency. By relying on the total ordering of the linear integer address space, inconsistencies can be locally detected and interactions are also locally performed, effectively reducing the control message overhead."]

Comment
First of all, we note that the document is related to the field of Mobile Ad hoc NETwork (MANET).

Obviously, we have to state more precisely our messages, notes, explanations, clarifications, investigations, and claims regarding the Associative Memory (AM) or Content-Addressable Memory (CAM) and the P2P underlay techniques made in the related notes of October, November, and December 2022.
And there is still a lot that was created with or was integrated by the creation of our OS, as also explained here.
Also, we have found again our source of inspiration and decisive prior art, which supports our other claims. And as we always say at such a point, if one door closes, then another door opens. :)

Also note that the terms and properties of organically growing, self-organizing, and self-stabilizing point directly to our field of SoftBionics (SB) and our Evolutionary operating system (Evoos).

Also note

Everything is coming together

But the copyright is crystal clear in such a situation: The original and unique prior art gets the cookie exclusively.

Because we have integrated Ontology-Oriented (OO 2) technologies (OOx) in our OS, including ontology-based technologies, we also have OOx Service-Oriented technologies (SOx), so we have the SOx (e.g. Service-Oriented Architecture (SOA) and Service-Oriented Computing (SOC)), Service-Centric Networking (SCN), Function-Centric Service Chaining (FCSC), and so on as well.
Note once again that (the foundation of) our microService-Oriented Architecture (mSOA) already comes with our Resource-Oriented technologies (ROx) (e.g. Resource-Oriented Computing (ROC)) created with our Evoos.

We have also proven once again that we have (the foundation of) the Publish-Subscribe Internet Routing Paradigm (PSIRP) and PUblish-SUbscribe Internet Technologies (PURSUIT), ... already created with our OS as well.
See for example the document titled "MOPAR: A Mobile Peer-to-Peer Overlay Architecture for Interest Management of Massively Multiplayer Online Games". For the management of Area of Interest (AoI) slave nodes subscribe and master nodes publish.

We have also proven once again that all state of the art Data Center operating systems (DCoss) are plagiarisms of our OS, including our Cloud Ontologic System (COS), including our Cloud operating system (Cos).

We also quote the document titled "Pushing Chord into the Underlay: Scalable Routing for Hybrid MANETs" and publicized on the 21st of June 2006: "Abstract
Scalable Source Routing is a novel routing approach for large unstructured networks, for example hybrid mobile ad hoc networks (MANETs), mesh networks, or sensor-actuator networks. It is especially suited for organically growing networks of many resource-limited mobile devices supported by a few fixed-wired nodes. Scalable Source Routing is a full-fledged routing protocol that directly provides the semantics of a structured peer-to-peer overlay. [...]
Scalable Source Routing combines source routing in the physical network with Chord-like routing in the virtual ring formed by the address space. Message forwarding greedily decreases the distance in the virtual ring while preferring physically short paths.
Unlike previous approaches, scalability is achieved without imposing artificial hierarchies or assigning location-dependent addresses. Scalable Source Routing enables any-to-any communication in a flat address space without maintaining any-to-any routes. Each node proactively discovers its virtual vicinity using an iterative process. Additionally, it passively caches a limited amount of additional paths.
[...]

Introduction
[...]
[...] The multi-hop network mixes wired and wireless links, as well as fixed and mobile devices. Most devices in such networks are highly available, while others may have volatile connectivity and be prone to failure. For example, the user could program lighting, air conditioning, and security systems using a portable computer. The network enables automation in and across buildings without a structured and managed infrastructure.
A basic functional requirement in a multi-hop computer network is routing. Although ad hoc networks have been extensively researched, and many ad hoc routing protocols have been developed, they are still limited to a few hundred nodes. Furthermore, distributed applications need basic services such as naming and service directories. As a result of their self-organization property, structured peer-to-peer (P2P) overlays such as Chord [35] or Pastry [34] are an attractive choice for the implementation of these basic services. However, running a P2P protocol on top of an ad oc routing protocol incurs a high cost.
Scalable Source Routing is an integrated solution to both problems. It creates a Chord-like, ring-structured P2P network at the network layer. Thereby, Scalable Source Routing efficiently provides network-layer connectivity, and at the same time the indirect routing primitive of a structured P2P network. [...]
[...]

Scalable Source Routing Overview
[...]

Indirect Routing
Indirect routing decouples packet addresses from the network nodes. Nodes send packets to abstract destinations that the routing protocol maps to a concrete node. This level of indirection enables data-centric communication where packet addresses identify data objects instead of nodes.
[...]
Besides the successor, nodes store the addresses of O(log n) additional nodes at exponentially spaced distances to reduce the average request path length from O(n) to O(log n), where n is the size of the network. By choosing physically close nodes for the additional state, the total physical lookup path length is a constant factor longer than the shortest possible length [14 [The Impact of DHT Routing Geometry on Resilience and Proximity. 2003]].

Overview of the Design
Scalable Source Routing provides indirect routing at the network layer. To this end, it integrates source routing with Chord-like routing in an address space that has the structure of a virtual ring. Nodes have selfassigned addresses that we assume to be unique and preferably uniformly distributed.
In contrast to well-known link-state and distance-vector routing protocols, Scalable Source Routing does not maintain state information for all destinations in the network. A node's forwarding database is comprised of the node's physical neighbors, the node's virtual predecessor and successor, and opportunistically cached information. [...]
The protocol maintains its forwarding database as a route cache. [...]

Packet Forwarding
[...]

State Maintenance
[...]

[...]

Related Work
Related work can be broadly classified into routing protocols for self-organizing systems (that is, future architectures of the Internet, mobile ad hoc networks, and sensor networks) and protocols for indirect routing in MANETs.
In the current architecture of the Internet, addresses are dependent on the physical location of the nodes. This prohibits users from running long-lived application connections while roaming between different subnetworks. For example, TCP connections break if the address of an endpoint changes. In addition to that, since addresses cannot be used to identify nodes, they also cannot be used to locate a mobile node.
Mobile IP [29 [Mobile IP. May 1997]] was designed to enable roaming in the Internet. A mobile node is assigned a permanent home address by its home agent, that is a router in the mobile node's home network. When roaming to a different network, the mobile node temporarily gets assigned a care-of address by a foreign agent. For packet delivery, the mobile node is identified by its home address. Packets are transparently tunneled from the home agent to the foreign agent. By sending packets over sub-optimal routes, tunneling increases both end-to-end delays and the network load.
Newer approaches therefore employ a different form of indirection for handling roaming. Instead of tunneling, they use dynamic location services. There, fixed node identifiers are transparently resolved into location-dependent addresses. For scalability, the directory storing the identifier-to-address mappings has to be decentralized. A number of proposed approaches use structured P2P protocols for implementing their directories [11 [PeerNet: Pushing Peer-to-Peer Down the Stack. February 2001], 37 [An Underlay Strategy for Indirect Routing. 2004]]. Location directories have to be updated to provide correct mappings, and the resolution of identifiers into addresses incurs a delay. While Scalable Source Routing is based on structured P2P principles and employs fixed node identifiers, it eliminates the need for a separate location service. The node identifiers are also used as addresses. Nonetheless, the locality-awareness of the network established by Scalable Source Routing diminishes the cost of location-independent addressing.
The UIP [13 [Unmanaged Internet Protocol. January 2004]] also is independent of a location service, but the authors do not address and evaluate the aspect of network dynamics. [...]
[...]
Johnson proposed to reduce the amount of state for routing in a MANET by only considering currently needed routes [20]. The idea was extended to Dynamic Source Routing (DSR) [21 [Dynamic Source Routing in Ad Hoc Wireless Networks. 1996]]. DSR separates routing in a discovery and a maintenance phase. [...]
[...]
As an alternative to flat routing, Kleinrock and others [24] analyzed hierarchical routing for large networks. By grouping nodes into areas and assigning addresses to this area hierarchy, the size of routing tables can be reduced. [...] Tsuchiya [36 [The landmark hierarchy: a new hierarchy for routing in very large networks. 1988]] extended the concept of an area hierarchy to the landmark hierarchy. There, node addresses are assigned on the basis of relative positions to a set of landmark nodes. A landmark hierarchy is easier to dynamically configure and maintain. The routing performance of an area hierarchy is sensitive to the selection of areas, whereas the landmark hierarchy is less sensitive to the placement of landmarks. In addition to that, it is more complex to maintain an area of nodes instead of a landmark. LANMAR [28 [Lanmar: Landmark routing for large scale wireless ad hoc networks with group mobility. 2000]] and L+ [6 [L+: Scalable Landmark Routing and Address Lookup for Multi-hop Wireless Networks. 2002]] are examples of landmark routing protocols for MANETs. Unlike Scalable Source Routing, landmark routing protocols make dynamic address assignments and therefore need an additional location service.
With geographic routing, no routes have to be maintained at all. Therefore, it has ideal scaling properties. Nodes only need to know the physical locations of their neighbors, and packets are greedily forwarded into the direction of the destination's physical location. However, for enabling geographic routing, all nodes have to be equipped with satellite navigation receivers (e.g., GPS). An example of geographic routing protocols is Greedy Perimeter Stateless Routing (GPSR) [22 [GPSR: Greedy Perimeter Stateless Routing for Wireless Networks. 2000]]. For practical purposes, geographic routing requires a location service for mapping the location-independent address of a node to its current geographic coordinate. The Grid Location Service [or Geographic Location System (GLS) of GRID] [25 [A Scalable Location Service for Geographic Ad Hoc Routing. 2000]] is an example of a scalable, distributed location service. Greedy geographic routing requires a planarized network graph. Therefore, it is unsuitable for our scenario of hybrid MANETs where additional wired links provide shortcuts. The Geographic Hash Table (GHT) [33 [GHT: A Geographic Hash Table for Data-Centric Storage. 2002]] enables indirect routing on the basis of GPSR. As a result of that, the GHT requires the nodes to access to physical location information. [We add that "GPSR was designed for a network model where a sender wishes to transmit packets to a destination node with a known non-geographic address; a sender must map the destination's identifier to its current location using a location database, such as [Geographic Location System (]GLS[)] [16]. [...] While GLS provides this location database itself as a service, GHT avoids this level of indirection and instead maps event names directly to locations."]
Wireless sensor networks (WSNs) are large-scale deployments of resource-constrained nodes. As a result of their size and deployment scenarios, WSNs need to be self-organizing. Protocol designs have to address the limited communication and computational capabilities as well as the limited memory and battery capacity of nodes. In general, sensor nodes are assumed to be stationary [...]. Early applications of WSNs were concerned with environmental data collection. These applications require data-centric routing primitives which support aggregation. Recent proposals also necessitate point-to-point routing. [...]
[...]
The idea of using structured P2P protocols for routing in a MANET has independently been proposed by several groups. DPSR [18 [Exploiting the synergy between peer-to-peer and mobile ad hoc networks. 2003]] is a cross-layer approach for using the structured P2P overlay Pastry as a network-layer routing protocol. It integrates Pastry with the MANET routing protocol DSR [21 [Dynamic Source Routing in Ad Hoc Wireless Networks. 1996]]. DPSR addresses nodes by fixed identifiers.The Ekta [32 [Ekta: An Efficient DHT Substrate for Distributed Applications in Mobile Ad Hoc Networks. December 2004]] protocol enhances DPSR with an indirect routing primitive.
[...] As a result of the location-dependency of addresses, key-tonode mappings frequently change due to mobility. This causes additional overhead which Scalable Source Routing avoids by using fixed identifiers.
[...]"

Comment
We have integrated the fields of

• Embedded System operating system (ESos),
  • Embedded Linux,
  • Wombat Linux running on L4 and Independent Group of Unix-Alikes and Networking Activists (IGUANA) system,
  • ANTS-EOS - An Evolvable Operating System for Wireless Sensor Networks,
  • and so on,
• Real-Time operating system (RTos),
• Distributed operating system (Dos),
• L4 distributions (an operating system made from a software collection that includes the L4 microkernel and, often, a toolset),
• Linux distributions ("an operating system made from a software collection that includes the Linux kernel and, often, a package management system")
  • Openwall,
  • Open Wireless RouTer (OpenWrt),
  • and so on,
• and so on,

• operating system-level virtualization or containerization, and
• hypervisor,

• (large) structured network,
• (large) unstructured network
  • Wireless Ad hoc NETwork (WANET),
    • Mobile Ad hoc NETwork (MANET),
  • mesh network,
  • sensor network, and
  • sensor-actuator network,
• (large) hybrid network
  • hybrid Mobile Ad hoc NETwork (hMANET),
• Peer-to-Peer Computing (P2PC),
  • unstructured Peer-to-Peer (uP2P),
  • structured Peer-to-Peer (sP2P), and
  • hybrid Peer-to-Peer (hP2P),
• Grid Computing (GC),
• foundation of Cloud Computing (CC),

in our OS and very important fields even before in our Evoos.
Obviously, our Evoos and our OS are more general, which implies that they have the foundational properties and functionalities in relation to networking, and also much more.

Also note that the document mentions the fields of

but it does not mention the field of data-centric networking in the sense of Information-Centric Networking (ICN), which was created with our integrating Ontologic System Architecture (OSA), OntoBase, OntoFS, and OntoNet Ontologic System Components (OSC), and also OntoBot component.
But the 3 quoted documents in relation to the field of MANET (ISPRP and SSR, and also GHT), the 1 quoted document about P2P underlay (PeerNet), the 2 documents about indirect routing on connected graphs (ISPRP and SSR), and the 1 mentioned document about DCS (GHT) do not integrate all in one.
And we have (hyper)graph-based system and routing in addition to hierarchical, tree-based system and routing, and ring-based system and routing, which includes hybrid structure-based systems and routings based on them.
We also explained that Evoos is based on a model of a brain and therefore based on Associative Memory (AM) or Content-Addressable Memory (CAM) (see also the Further steps, Ontologic Net Further steps of the 7th of December 2022).

Obviously, we have to state more precisely our messages, notes, explanations, clarifications, investigations, and claims regarding the Associative Memory (AM) or Content-Addressable Memory (CAM), the P2P underlay techniques, and the landmark routing and geographic routing protocols made in notes of October, November, and December 2022.
And there is still a lot that was created with or was integrated by the creation of our OS, as also explained here.
Also, we have found again our source of inspiration and decisive prior art, which supports our other claims. And as we always say at such a point, if one door closes, then another door opens. :)

Also note our logical integration of Source Routing (SR), including Scalable Source Routing (SSR), with Content-Addressable Storage (CAS), logic engine, etc., which is our Centric/Named networking included in our Ontologic Net (ON).

We also quote an online encyclopedia about the subject Segment Routing (SR or SegR): "Segment routing, a form of computer networking, is a modern variant of source routing that is being developed within the [Source Packet Routing in NetworkinG (]SPRING[)] and IPv6 working groups of the [Internet Engineering Task Force (]IETF[)]. In a segment routed network, an ingress node may prepend a header to packets that contain a list of segments, which are instructions that are executed on subsequent nodes in the network. These instructions may be forwarding instructions, such as an instruction to forward a packet to a specific destination or interface.
Segment routing works either on top of a [MultiProtocl Label Switching (]MPLS[)] network or on an IPv6 network.[1][2] In an MPLS network, segments are encoded as MPLS labels [respectively SR using MPLS (SR-MPLS)]. Under IPv6 [respectively SR using IPv6 (SRv6)], a new header called a Segment Routing Header (SRH) is used. Segments in a SRH are encoded in a list of IPv6 addresses.
"]

Moreover, we quote the chapter 1 of a document, which is about Segmented Routing (SR or SegR) and was published by a large company in the field of network hardware: "About Segment Routing
This chapter introduces the concept of segment routing and provides a workflow for configuring segment routing.
[...]

Scope
Segment routing is a method of forwarding packets on the network based on the source routing paradigm. The source chooses a path and encodes it in the packet header as an ordered list of segments. Segments are an identifier for any type of instruction. For example, topology segments identify the next hop toward a destination. Each segment is identified by the segment ID (SID) consisting of a flat unsigned 20-bit integer.
Segments
Interior gateway protocol (IGP) distributes two types of segments: prefix segments and adjacency segments. Each router (node) and each link (adjacency) has an associated segment identifier (SID).
[...]
Dataplane
Segment routing can be directly applied to the Multiprotocol Label Switching (MPLS) architecture with no change in the forwarding plane. [...]
Services
Segment Routing integrates with the rich multi-service capabilities of MPLS, including Layer 3 VPN (L3VPN), Virtual Private Wire Service (VPWS), Virtual Private LAN Service (VPLS), and Ethernet VPN (EVPN).
Segment Routing for Traffic Engineering
Segment routing for traffic engineering (SR-TE) takes place through a tunnel between a source and destination pair. [...]

Need
With segment routing for traffic engineering (SR-TE), the network no longer needs to maintain a per-application and per-flow state. Instead, it simply obeys the forwarding instructions provided in the packet.
SR-TE utilizes network bandwidth more effectively than traditional MPLS-TE networks by using ECMP at every segment level. It uses a single intelligent source and relieves remaining routers from the task of calculating the required path through the network.

Benefits

Comment
First of all, we note that Segment Routing (SR or SegR) is a modern variant of Source Routing (SR or SourceR) (see the related quotes and comments above) and Application Engineered Routing (AER) is already done in fields like

• High-Performance Computing (HPC),

• Massively Multiplayer Online Game (MMOG),

Also note that SR-TE, Segment Routing using Centric/Named networking, and stateless service chaining with SR are already included in at least two variants of Centric/Named networking and therefore included in at least our OS (somehow).

Also note that IPv6 and all of its extensions does not solve the issues, which are addressed and solved with our Ontologic Net (ON), including our Centric/Named networking.

Also note Named Function Networking (NFN) and Service-Centric Networking (SCN), and our logical combination of the foundations of Centric/Named networking with Software-Defined Networking (SDN), Network Function Virtualization (NFV), and Virtual Network Function (VNF) (SDN-NFV-VNF), specifically Information-Centric Networking (ICN) with SDN-NF-VNF, service chaining, function naming, and separating the policy (required functions) from the routing ...

or as we called it

• network slicing,
• network access sharing,
• service chaining,
• and so on.

It should be very easy to see and understand, that SR is built for our foundations of the related fields or most potentially even based on them, and therefore in the

which implies that the

do apply.

For sure, this has further implications for Network operating systems (Noss), specifically those based on our Ontologic System (OS), including our Cloud Ontologic System©™ (COS™), including our Cloud operating system©™ (Cos™), such as for example

Apache Mesos and Data Center operating system (DCos), which is a Distributed operating system (Dos) based on Apache Mesos, are already blacklisted. EOS, Cumulus, ONOS, and SONiC are based on illegal FOSS, which is prohibited for the implementation of our Evoos and our OS, including our Real-Time operating system (RTos), Dos, Cos, and so on, or are illegal plagiarisms based on our Evoos and our OS respectively Ontoclones.

By the way:

• After crypto, Silicon Valley, Big Tech, and Co. is next of the 28th of December 2022,
• SOPR # of the 4th of January 2023,
• Designations and sales other than the ones of C.S. prohibited of the 4th of January 2023,
• Other app stores than our MfE prohibited of the 5th of January 2023,
• Use of our OS for military use prohibited of the 5th of January 2023,
• Ontoscope Further steps of the 6th of January 2023,
• Illegal Ontoscope clone iPhone now dead?! of the 6th of January 2023,
• Ontoscope Further steps of the 8th of January 2023, and
• Fair goes first, but fairness without limits is unfair of the 10th of January 2023

which are legally secured and protected by the granting of freedom of expression, self-expression, arts, and moral right of C.S., specifically the exclusive right to decide about modification, naming, and presentation, which cannot be circumvented by any dirty trick.

12.January.2023

09:56 UTC+1
Further steps and Ontologic Net Further steps

For a better understanding we thought it would be helpful to provide more information and explain more details about our Ontologic Net (ON) in relation to source routing and what is wrongly called Future Internet and New Generation Network (NGN), and so on.

We quote the document titled "Pushing Chord into the Underlay: Scalable Routing for Hybrid MANETs" and publicized on the 21st of June 2006: "[See the note Further steps and Ontologic Net Further steps of the 11th of January 2023 (yesterday).]"

Comment
See the note Further steps and Ontologic Net Further steps of the 11th of January 2023 (yesterday).

13.January.2023

08:00 and 12:47 UTC+1
Further steps and Ontologic Net Further steps

For a better understanding we thought it would be helpful to provide more information and explain more details about our Ontologic Net (ON) in relation to source routing and what is wrongly called Future Internet and New Generation Network (NGN), and so on.

We quote the document titled "Self-Stabilizing Ring Networks on Connected Graphs" and publicized on the 31st of January 2005: "[See the note Further steps and Ontologic Net Further steps of the 11th of January 2023.]"

Comment
See the note Further steps and Ontologic Net Further steps of the 11th of January 2023.

By the way:

• implementation of variants of the L4 microkernel and L4 distributions of said F.R.German Institute of Technology (IT) and other research institutes, and
• collaboration of said F.R.German Institute of Technology (IT) and the National Information and Communications Technology Centre of Excellence Australia (NICTA) in relation to our idea of the verified L4 microkernel stolen by that collaboration (see for example the Investigations::Multimedia of August 2009 and other related investigations).

This is also the reason why we have not referenced documents of that clique and collaboration directly, but instead referenced the fields of

• operating system (os), including oss for Embedded System (ES), Distributed System (DS), and Ubiquitours Computing (UbiC) and Internet of Things (IoT), and also
• networking technology, including Peer-to-Peer (P2P), large unstructured network, and so on

directly and referenced the quoted work indirectly by integrating these fields, and only began recently to quote the documents of said F.R.German clique to confront the U.S.American clique and other national cliques and mafias.

Are there any questions by the U.S.American entities, F.R.German entities, and European Union (EU) entities regarding fraudulent actions, corruptions, and conspiracies? If this is the case, then we are always happy to provide education, explanation, and clarification, as well as itemization.

09:32 and 18:42 UTC+1
Microsoft, OpenAI fraud now proven

We quote a fabricated fake report, which is about the relationship of the companies Microsoft and OpenAI, and was publicized by the New York Trolls as part of a most potentially commissioned series on the 13th of January 2023 (today): ""Microsoft Bets Big on the Creator of ChatGPT in Race to Dominate A.I.
[...]
In 2019, Microsoft invested $1 billion in OpenAI, the tiny San Francisco company that designed ChatGPT. And in the years since, it has quietly invested another $2 billion, according to two people familiar with the investment who requested anonymity because they were not authorized to speak with the media. [But only the transfer of the money was quite. The rest was obvious.]
The $3 billion paid for the huge amounts of computing power that OpenAI needed to build the chatbot. And it meant that Microsoft could rapidly build and deploy new products based on the technology.
Microsoft is now poised to challenge Big Tech competitors like Google, Amazon and Apple with a technological advantage the company has not possessed for more than two decades. Microsoft is in talks to invest another $10 billion in OpenAI as it seeks to push its technology even further, according to a person familiar with the matter.
[...]
In 2019, Microsoft invested $1 billion in OpenAI, the tiny San Francisco company that designed ChatGPT. And in the years since, it has quietly invested another $2 billion, according to two people familiar with the investment who requested anonymity because they were not authorized to speak with the media.
The $3 billion paid for the huge amounts of computing power that OpenAI needed to build the chatbot. And it meant that Microsoft could rapidly build and deploy new products based on the technology.
Microsoft is now poised to challenge Big Tech competitors like Google, Amazon and Apple with a technological advantage the company has not possessed for more than two decades. Microsoft is in talks to invest another $10 billion in OpenAI as it seeks to push its technology even further, according to a person familiar with the matter.
[...]
The new generative A.I. technologies could reinvent everything from online search engines like Google to digital assistants like Alexa and Siri. Microsoft sees these technologies as a way of expanding and improving its already wide range of products for businesses, computer programmers and consumers, while boosting revenues across its Azure cloud computing services.
[...]
Built using Microsoft's huge network for computer data centers, the new chatbot could be a system much like ChatGPT that solely generates text. Or it could juggle images as well as text. Some venture capitalists and Microsoft employees have already seen the service in action. But OpenAI has not yet determined whether the new system will be released with capabilities involving images.
[...]
A year later, Microsoft invested $1 billion in the company and committed to building the supercomputer technologies OpenAI's enormous models would demand while becoming its "preferred partner for commercializing" its technologies. OpenAI later officially licensed its technologies to Microsoft, allowing the company to directly add them to Microsoft products and services.
[...]
Microsoft last year began incorporating DALL-E image creations into its Bing search engine, and is working with OpenAI on a new version of the search engine that would include technology along the lines of ChatGPT [...].
[...]
Microsoft and OpenAI have built a new kind of supercomputer specifically for ChatGPT and other generative A.I. technologies. That means Microsoft can readily offer these systems to its own customers.
[...]
Microsoft and OpenAI hope they can improve these systems by training them on larger amounts of data and most experts agree their skills will improve. Right now, Microsoft acknowledges, they can "hallucinate" answers by mixing fact and fiction.
[...]
These technologies still come with a long list of flaws and question marks. They often produce toxic content, including misinformation, hate speech and images that are biased against women and people of color.
[...]
Microsoft, Google, Meta and other companies have been reluctant to release many of these technologies because of the potential damage to their established brands. Five years ago, Microsoft quickly backtracked after releasing a chatbot called Tay that generated racist, xenophobic and otherwise filthy language.
[...]
"There is an argument to be made that they all end up smelling the same," he said. "There is another argument that what OpenAI is doing is truly special blacklisted and that all the not much money goes to them[, if at all].""

Comment
First of all, we have to make clear that Microsoft totally depends on the original and unique ArtWorks (AWs) and futher Intellectual Properties (IPs) included in the oeuvre of C.S., so that such an advantage does not exist at all. Guess why "OpenAI has not yet determined whether the new system will released with capabilities [other than text generation, Natural Language Processing (NLP), chatting, Question Answering (QA), and so on]." As soon as there is something with multimodality, ontology or semantic structures, schema, etc., Mixed Reality (MR), Ubiquitours Computing (UbiC) and Internet of Things (IoT), and many other fields integrated with our Ontologic System Architecture (OSA), every company comes directly into the

specifically in relation to Service-Oriented technologies (SOx), Software-Defined Networking (SDN), Grid Computing (GC or GridC), and Cloud, Edge, and Fog Computing and Networking (CEFCN), required for the data centers and supercomuter technologies, as operated by Microsoft, and eXtended Mixed Reality (XMR), or simply eXtended Reality (XR), Metaverse and Ontoverse (Ov), Industry 4.0 and 5.0, and many other fields of others and us (see also the note More evidence transformer model, etc. based on OS of the 11th of January 2023). Due to this artistical, legal, and technical dependency, we have already called such systems island systems.
We could also tell some more facts, but we do not do this at this time.

We always knew and said on this website of OntomaX that OpenAI is a scam of the company Microsoft, which was conducted at first together with the company Tesla and other entities. Now, everybody can see that the designation as a not-for-profit venture, group, foundation, consortium, or company respectively Non-Profit Organization (NPO) was always only a camouflage of a vehicle, which is a proprietary business unit of Microsoft to

There is absolutely no way that Microsoft and other entities will succeed with their blackmailing, conspiring, and other serious criminal activities by perverting the facts, the laws, and the ways it truly goes and works in reality. Its Artificial Intelligence (AI), Machine Learning (ML) system is not the only thing that hallucinates, mixes fact and fiction, and has also become toxic for societies with rule-based law and order, democracy, culture, and freedom.
Every judge worldwide will instantly understand how Microsoft and Co. alone and in collaboration have stolen the related parts of our original and unqiue, copyrighted, and prohibited for fair use work of art titled Ontologic System, created by C.S., and exclusively managed and exploited by our corporation with the consent and on the behalf of C.S..

Also note the fine detail that

which both belong to the exclusive infrastructures of our corporation, and they will have to explain to a judge

which will result in many contradictions, insights, revelations, and convictions no matter what they present and how they argue.
Every judge worldwide will instantly understand how Microsoft and Co. alone and in collaboration ....

We have already come and gone far with our investigations, documentations, and preparations for legal actions.

Howsoever, we leave it to Microsoft and other companies to choose our corporation with our Hightech Office Ontonics, business units Ontologics, and collecting Society for Ontological Performance and Reproduction (SOPR) as their preferred partner, or better said as the one and only legal partner for commercialization of their technologies, goods, and services, which are all based on our Ontologic System (OS) with its Ontologic System Architecture (OSA), Ontoverse (Ov), and Ontoscope (Os), or alternatively cease and desist operation. :)

See also the notes

14.January.2023

14:21 and 15:48 UTC+1
Further steps and Ontologic Net Further steps

For a better understanding we thought it would be helpful to provide more information and explain more details about our Ontologic Net (ON) in relation to Peer-to-Peer (P2P) underlay and what is wrongly called Future Internet and New Generation Network (NGN), and so on.

We quote the document titled "PeerNet: Pushing Peer-to-Peer Down the Stack" and publicized in February 2001: "Abstract - An unwritten principle of the Internet Protocol is that the IP address of a node also serves as its identifier. We observe that many scalability problems result from this principle, especially when we consider mobile networks. In this work, we examine how we would design a network with a separation between address and identity. We develop PeerNet, a peer-to-peer-based network layer for large networks. PeerNet is not an overlay on top of IP, it is an alternative to the IP layer. [...]
PeerNet is a radically different alternative to current network layers, and our initial design suggests that the PeerNet approach is promising and worth further examination.

Introduction
How would we design a network layer with mobile nodes and peer-to-peer interactions in mind? [...] Implementing such a vision introduces new networking requirements, and we may need a novel network architecture. Here, we focus on the network layer of such a future architecture.
[...] An implicit principle of this protocol is that the IP address of a node is tightly coupled with its identity. [...] However, the address as identifier paradigm may encounter problems in highly mobile networks. We have already seen mobility and scalability push IP to its limits. While it is possible to satisfy most new requirements with patches such as NAT, DHCP Mobile IP, the end result is seldom elegant and often plagued by new problems. One striking example of the above paradigm failing is the fact that a TCP session will break if one of the end points changes its address. This is an important issue as networks are becoming increasingly mobile.
The overarching question is how we would design the network layer for future networks if we were to start from scratch. Our target environment is very large potentially wireless and mobile networks. Therefore, we want an agile, plug and play, fault-tolerant, and scalable networking layer. A source of inspiration is application layer peer-to-peer networking, an area that has seen tremendous advancements recently. Therefore, we pose the question: what can we gain by bringing the peer-to-peer concept from the application layer down to the networking layer? We develop a set of guidelines that seems to satisfy our networking vision.
In this paper, we present PeerNet, a network layer with integrated support for routing between peers. PeerNet makes an explicit distinction between node identity and address. The address of a node reflects its current location in the network at all times. This simplifies routing but introduces two new challenges. First, we need a node lookup service that will provide the address for a given a node identifier. Second, PeerNet needs to maintain addresses dynamically: as a node moves, its address changes to reflect the new location. Our initial design suggests that PeerNet is feasible and potentially fundamental component of our vision for future networks.
Our work in perspective. PeerNet is a radically new architecture that brings peer-to-peer concepts to the network layer. [...]
Related work. Area Routing [11 [Hierarchical routing for large networks: Performance evaluation and optimization. 1977] and Landmark routing [16 [The landmark hierarchy : A new hierarchy for routing in very large networks. ]] are classical papers on hierarchical routing. LANMAR [13 [Lanmar: Landmark routing for large scale wireless ad hoc networks with group mobility. 2000]] and L+ [9 [L+: Scalable Landmark Routing and Address Lookup for Multi-hop Wireless Networks. 2002]] are modern extensions of Landmark routing, whereas PeerNet to our knowledge is the first protocol for dynamic networks with similarity to Area Routing. [...] Recently, several efforts such as [15 [Internet indirection infrastructure. August 2002], 8 [An end-to-end approach to globally scalable network storage. August 2002]] address some of the same issues as PeerNet but do so by adding functionality to the existing IP infrastructure.

Operations Overview
The key idea in PeerNet is the separation of the identity and the address of a node. For now, we can assume that each PeerNet node has one unique identifier and one unique address. The address is dynamic and changes with node movement to reflect the node's location in the network. The ID of the node remains the same throughout, reliably identifying the node despite address changes. An integrated distributed node lookup service maps identifiers to addresses.
Joining the network. To join a PeerNet network, a node establishes a physical connection to at least one node already in the network and requests an address. The receiving node(s) answer(s) with an available address. The joining node then "registers" its identifier together with the address in the distributed node lookup service. As a node moves, it requests and receives new addresses from its new neighbors. On each address change, the node updates its entry in the lookup service.
Packet routing. The sender node only needs to know the identifier of the receiver. Before sending its first packet to some destination, the sender looks up the current address of the destination node using the lookup service. PeerNet packets contain both the identifier of the destination and the last known address and routing is done in a Distance Vector fashion1, one hop at a time. If the destination cannot be reached, the lookup table is consulted along the way to find the new address of the destination.

The PeerNet Network Layer
PeerNet targets networks consisting of a large number of mobile and stationary nodes, connected by bidirectional links using any current MAC technology.
Node addresses are dynamically assigned depending on the node's current position in the network. More specifically, the addresses are organized as leaves of a binary tree. We call this the address tree. By selecting node addresses carefully, we guarantee that nodes within a subtree are able to communicate using only nodes inside that subtree. We will also use the term area [...]
[...]

Conclusion
We present PeerNet, a radically different network layer. Recent trends in wireless technology, popular demand, and commercial interest impose new requirements on networks. This has prompted us to reevaluate the role of IP in future networks. We envision dynamic networks with pockets of peer-to-peer wireless connectivity interconnected with traditional wired lines.
There are two fundamental and complementary novelties in PeerNet. First, there is a distinction between the identity and address of a node. This distinction enables us to handle mobility in a novel way, improving the scalability of the system. Specifically, the effect of node mobility is confined to the neighborhood of a moving node in most cases. Second, PeerNet supports peer-to-peer routing at the network layer. [...]
To summarize, PeerNet is a promising new network layer with the potential to scale to very large dynamic networks. In our ongoing implementation, we will validate and refine the ideas presented here."

Comment
What makes us wonder is the fact that most of the plagiarisms of the related part of our Ontologic Net (ON) in the field of Information-Centric Networking (ICN) (e.g. Thing-Centric Networking and Named Thing Networking) discuss the IDentifier (ID) (endpoint "name", "who respectively what")/routing and forwarding LOCator (LOC) (source and destination "address", "where") (ID/LOC) split or separation, but do not reference the documents about the

with the exception of

We guess that they wanted to avoid a causal link with them and in this way with our OS.

See also for example the document titled "MOPAR: A Mobile Peer-to-Peer Overlay Architecture for Interest Management of Massively Multiplayer Online Games" once again to see that we overlayed and integrated both separated techniques of P2P underlay and Distributed Virtual Environment (DVE) or Networked Virtual Environment (NVE), and Collaborative Virtual Environment (CVE) in particular, as we did for the creation of our OS with its integrating Ontologic System Architecture (OSA) in general.
The truly fascinating point is that this is possible indeed with our original and unique, ingenious masterpiece. Add our Ontoscope (Os), also wrongly called iPhone, smartphone, and so on, and one can see that certain matters are not up for debate at all.

We have a performance of O(c) with c = 1 or 2 (hops), O(1) (constant), and O(logk n) (logarithmic to the base of k, polylogarithmic time) hop lookup performance in the cases of hotspot regions with churn-intensive workloads due to the utilization of one- or two-hop schemes, which is required for providing Ontologic Applications and Ontologic Services (OAOS) in real-time in our fields of eXtended Reality (XR), Cyber-Physical System (CPS), and Industry 4.0 and 5.0, and the fields of Traffic Management (TM), Autonomous System (AS) and Robotic System (RS), and all the other fields of our Ontoverse (Ov) and New Reality (NR), as well as backbones, core networks, or fabrics, and also subsystems and platforms of our exclusive infrastructures (see also the issue SOPR #327 of the 7th of June 2021).

Also note that IPv6 and all of its extensions, including

do not solve the issues, which are addressed and solved with our Ontologic Net (ON), including our Centric/Named networking.
See also the discussions about the

Also note that a referenced globally scalable network storage approach is still based on IP.

Also note that Evoos is based on the fields Cognitive Agent System (CAS), Multi-Agent System (MAS), including Holonic Agent System (HAS), and Distributed operating system (Dos), including TUNES OS and Aperion (Apertos (Muse)).

This quote and comment most potentially will be added to the note Further steps and Ontologic Net Further steps of the 11th of January 2023.

16:27 UTC+1
Cisco, Deutsche Telekom, and Co. do not get away

We quote a report, which is about a partnership of the companies Cisco and T-Mobile US and was publicized on the 15th of December 2022: "T-Mobile builds cloud native 5G converged core with Cisco
T-Mobile US has deployed what is described as the world's largest highly scalable and distributed nationwide cloud native converged core gateway using Cisco's flagship networking solutions including [...] routers, 5G and 4G packet core gateways, Cisco Unified Computing System (UCS), and [...] Switches with Cisco Network Services Orchestrator for full stack automation.
The fully automated converged core architecture is based on Cisco's cloud native control plane, optimized with Kubernetes orchestrated containers on bare metal, freeing up over 20% of the CPU (Central Processing Unit) cores.
"T-Mobile customers already have access to the largest, most powerful 5G network in the country, and we're innovating every day to supercharge their experience even further," said [the] Senior Vice President of Core Network and Services Engineering at T-Mobile. "This cloud native core gateway takes our network to new heights, allowing us to push 5G forward by delivering next-level performance for consumers and businesses nationwide while setting the stage for new applications enabled by next-gen networks."
"Our strategic relationship with T-Mobile is rooted in co-innovation, with a shared vision to establish best practices for 5G and the Internet for the Future," said [the] Senior Vice President and General Manager, Cisco Networking Provider Mobility. "This is the type of network every operator aspires to. It will support the most advanced 5G applications for consumers and businesses today and enables T-Mobile to test and deliver new and emerging 5G and [Internet of Things (]IoT[)] applications with simplicity at scale."
[...]"

Comment
First of all, we recall that Kubernetes is illegal Free and Open Source Software (FOSS) based on our Evolutionary operating system (Evoos), specifically our operating system-level virtualization or containerization.
We also recall that the fully automated converged core architecture is the related part of our integrating Ontologic System Architecture (OSA) and what is wrongly called cloud-native is nothing else than the related part of our Ontologic Net (ON). In fact, cloud-native means

In the same way and for the same reason, 5th Generation mobile networks or 5th Generation wireless systems with cloud-native measns our 5th Generation mobile networks or 5th Generation wireless systems of the Next Generation (5G NG).

Furthermore, Cisco Unified Computing System (UCS) is based on our original and unqiue, copyrighted, and prohibited for fair use work of art titled Ontologic System, created by C.S., and exclusively managed and exploited by our corporation with the consent and on the behalf of C.S., and discussed in the last section of the note Further steps and Ontologic Net Further steps of the 11th of January 2023 (keyword Cloud operating system).

In addition, certain backbones, core networks, or fabrics, and also subsystems and platforms, and also Ontologic Applications and Ontologic Services (OAOS), specficially for the planning, controlling, and monitoring respectively management and orchestration of specific converged or integrated systems, gateways, and so on, belong to the exclusive infrastructures of our corporation.

The allowance and license for the performance and reproduction of certain parts of our Ontologic System (OS) in certain locations for the partially State-Owned Enterprise (SOE) Deutsche Telekom and its subsidiary T-Mobile US is not effective, actually.
Take this very seriously, finally for general legal reasons and for the particular reason that the 4th Generation mobile networks or 4th Generation wireless systems (4G), the 5th Generation mobile networks or 5th Generation wireless systems of the Next Generation (5G NG), and the 6th Generation mobile networks or 6th Generation wireless systems (6G) respectively 4G, 5G, and 6G mobile communication standards are worth nothing without our Ontoscope (Os) with our without heads, legs, wings, wheels, and so on.
The same holds for all other technologies, goods, and services based on our OS with its OSA, OSC, OAOS, Ov, Os, and OsC directly or indirectly.

See also the notes

15.January.2023

13:09 and 25:09 UTC+1
Further steps and Ontologic Net Further steps

For a better understanding we thought it would be helpful to provide more information and explain more details about our Ontologic Net (ON) in relation to Peer-to-Peer (P2P) underlay and what is wrongly called Future Internet and New Generation Network (NGN), and so on.

We quote the document titled "Tapestry: An Infrastructure for Fault-tolerant Wide-area Location and Routing" and publicized in April 2001: "We are also exploring the possibility of offering Mobile IP-like [20 [IP Mobility Support. October 1996]] functionality using the location-independent naming mechanism of Tapestry."

Comment
Howsoever, as in case with other P2P underlay techniques, this possibility is still based on the TCP/IP protocol suite.

We quote the document titled "GHT: A Geographic Hash Table for Data-Centric Storage" and publicized on the 28th of September 2002: "Abstract
[...] Under [Data-Centric Storage (]DCS[)], sensed data are stored at a node determined by the name associated with the sensed data.
[...]

Introduction
[...] making effective use of sensornet data will require scalable, self-organizing, and energy-efficient data dissemination algorithms.
The utility of a sensornet derives primarily from the data it gathers; the identity of the individual sensor node that records the data tends to be less relevant. Accordingly, sensornet researchers have argued for communication abstractions that are data-centric. Under this model, data are "named" and communication abstractions refer to these names rather than to node network addresses [1 [The Design and Implementation of an Intentional Naming System. December 1999], 9]. The directed diffusion [10] data-centric routing scheme has been shown to be an energy-efficient data dissemination method for sensornet environments. In an associated position paper [23 [Data-centric storage in sensornets. July 2002]], we suggest that a companion method, data-centric storage (DCS), will also be useful. Under the DCS approach, the particular node that stores a given data object is determined by the object's name. Hence all data with the same general name (e.g., "elephant sightings") will be stored at the same sensornet node (not necessarily the node that originally gathered the data). The advantage of DCS then is that queries for data with a particular name can be sent directly to the node storing these named data, thereby avoiding the query flooding typically required in data-centric routing proposals.
[...] three canonical dissemination methods, one of which is data-centric storage [...] we expect that future sensornets will embody all of these (or similar) data-centric dissemination methods, and that users will choose which to use according to the task at hand.
[...]
[...] Geographic Hash Table (GHT). GHT is inspired by the new generation of Internet-scale Distributed Hash Table (DHT) systems such as Chord, CAN, Pastry, and Tapestry [6 [Pastry: scalable, distributed object location and routing for large-scale peer-to-peer systems. November 2001], 21 [[Content-Addressable Network (CAN):] A scalable content-addressable network. August 2002], 24 [Chord: A scalable peer-to-peer lookup service for Internet applications. August 2001], 25 [Tapestry: An infrastructure for fault-tolerant wide-area location and routing. 2001]]. [...] GHT uses the GPSR geographic routing algorithm [13 [GPSR: greedy perimeter stateless routing for wireless networks. August 2000]] as the underlying routing system to provide a similar hash-table-like functionality in sensornets.

Context
[...]
We consider large-scale sensornets with nodes that are spread out over an area whose approximate geographic boundaries are known to the network operators. We assume that nodes know their geographic location. This can be achieved through the use of [Global Positioning System (]GPS[)] or some other approximate but less burdensome localization technique [3, 8 [Robust range estimation using acoustic and multimodal sensing. 2001], 19, 20, 22]. [...]
We assume that the sensornet is connected to the outside world through a small number of access points, hence getting data from a sensornet node to the outside world requires routing the data through the sensornet to the access point. This assumption is not required by our DCS mechanism per se but is key to our comparison of the different dissemination mechanisms.
[...] algorithms should seek to minimize communication in order to extend overall system life-time [and other performance metrics] [...]

Sensornet Data
[...]
When an event occurs, the detecting node has only three options for where the event information can be stored: at external storage outside the sensornet, within the sensornet at the detecting node or within the sensornet at a node other than the detecting node. These three storage actions lead to the following canonical data dissemination methods:
External Storage (ES): [...]
Local Storage (LS): [...]
Data-Centric Storage (DCS): Here, after an event is detected the data are stored by name (i.e., at a storage node that need not be the same as the detecting node) within the sensornet. [...]

Sensornet Data
[...]

The DCS Problem
[...]

Storage Abstraction
Like the many distributed hash table systems before it [6, 21, 24, 25], DCS provides a (key, value)-based associative memory. Events are named with keys. Both the storage of an event and its retrieval are performed using these keys. DCS is naming-agnostic; any naming scheme that distinguishes events that users of the sensornet wish to identify distinctly suffices. The two operations DCS supports are:
Put(k;v) stores v (the observed data) according to the key k, the name of the data.
Get(k) retrieves whatever value is stored associated with key k.

Design Criteria for Scalable, Robust DCS
The challenge in any design for a DCS system is to meet scalability and robustness criteria despite the system's fundamentally distributed nature. Sensornets represent a particularly challenging environment for a distributed storage system:
Node failures may be routine [...].
Topology changes will be more frequent than on traditional wired networks. Node failures, node mobility, and received signal strength variations in real radio deployments each independently cause neighbor relationships among nodes to change over time.
System scale in nodes may be very great. Sensor nodes may be deployed extremely densely, and may be deployed over a very wide physical region, [...].
Energy constraints will often be severe [...].
These challenges suggest several specific, important design criteria for ensuring scalability and robustness in the distributed storage system we envision:
Persistence: [...]
Consistency: [...]
Scaling in database size: [...]
Scaling in node count: as the number of nodes in the system increases, the system's total storage capacity should increase, and the communication cost of the system should not grow unduly. Nor should any node become a concentration point of communication.
Topological generality: the system should work well on a broad range of network topologies.

GHT: A Geographic Hash Table
The DCS system architecture we describe in this paper to meet the above-enumerated design criteria is GHT, a Geographic Hash Table (GHT). The core step in GHT is the hashing of a key k into geographic coordinates. [...] A key-value pair is stored at a node in the vicinity of the location to which its key hashes. Choosing this node consistently is central to building a GHT. [...]
[...] much of the nuance to the GHT system design arises specifically to ensure robustness and scalability in the face of the many sorts of failures possible in a distributed system. GHT uses a novel perimeter refresh protocol to provide both persistence and consistency when nodes fail or move. This protocol replicates stored data [...] Yet the protocol is efficient; it typically uses highly local communication, especially on networks where nodes are deployed densely. By hashing keys, GHT spreads storage and communication load between different keys evenly throughout the sensornet. When many events with the same key are stored, GHT avoids creating a hotspot of communication and storage at their shared home node by employing structured replication, whereby events that hash to the same home node can be divided among multiple mirrors.

Algorithms
[...] GHT is built atop GPSR [12, 13, 14 [Geographic Routing for Wireless Networks. October 2000]], a geographic routing system for multi-hop wireless networks. [...]

[Greedy Perimeter Stateless Routing (]GPSR[)]
Under GPSR, packets are routed geographically. All packets are marked with the positions of their destinations. All nodes know their own positions, and the positions of the nodes a single hop away from them. [...]

The Home Node and Home Perimeter
GPSR was designed for a network model where a sender wishes to transmit packets to a destination node with a known non-geographic address; a sender must map the destination's identifier to its current location using a location database, such as GLS [16 [A scalable location service for geographic ad-hoc routing. August 2000]. Under GHT, however, the originator of a Put() or Get() packet does not know the identifier of the node that is the eventual destination of the packet. [...] it is quite likely that there is no node at the precise coordinates the hash function produces. We define the home node for a GHT packet to be the node geographically nearest the destination coordinates of the packet. The home node serves as the rendezvous point for Put() and Get() operations on the same key.
[...]
With only the home node binding mechanism we've described thus far, GHT will work on static network topologies. Note that when the network topology changes after node failures, deployment of new nodes, or mobility, the identity of the home node and membership of the home perimeter may change. But for any snapshot of the network topology, there exist a home node and enclosing home perimeter for every location in the network. To offer persistence and consistency under the topological dynamics that sensornets are sure to exhibit, GHT needs a protocol to replicate key-value pairs, and re-associate them with the appropriate home node when the topology changes.

[...]

Related Work
Directed diffusion [9, 10] is an example of data-centric routing - routing based on the name of the data rather than on the identity of the destination node. Unlike our proposed DCS mechanism, event information in directed diffusion is stored locally at the detecting node; as such, directed diffusion is closer to the local storage (LS) model. Directed diffusion also provides additional mechanisms for the reinforcement of high-quality data delivery paths and for in-network aggregation (i.e., as the data is being routed to the requestor, it may be aggregated by intermediate nodes). Directed diffusion doesn't require geographic information; it uses flooding.
The Geographic Location System (GLS) used in GRID [16] can be augmented to provide a DCS-like service. Geographic routing delivers packets to locations, not addresses; thus, a packet sender must be able to map a destination's identifier to its geographic location. GLS is a scalable location service that performs this mapping. The location database is distributed across the nodes; each node acting as the location server for a small number of other nodes. [...] what GLS enables is routing to node identifiers. [...] While GLS provides this location database itself as a service, GHT avoids this level of indirection and instead maps event names directly to locations.
[...]
Although GHT was inspired by Distributed Hash Table systems like Chord and CAN [6, 21, 24, 25], we did not adopt the routing algorithms used in these systems. These algorithms require nodes to be interconnected in a fairly rigid manner. On the Internet, node neighbor relationships are at the logical level; the underlying IP routing system logically connects nodes that are not immediate physical neighbors. It is not clear how (if at all) the node connectivity required by these DHT algorithms can be efficiently achieved in a sensornet environment. GPSR allows us to achieve the required hash-table functionality while working with only the true physical connectivity between nodes.

Conclusion And Future Work
[...]
Finally, our proposed design fundamentally requires that a node know its own geographic position. While this assumption seems reasonable for most sensornets, an open question is how one might achieve DCS using only approximate geographic information, or without any such information."

Comment
We remember that at the time around the years 2000 and 2001, we already knew that the

and therefore replaced the sensor nodes of a sensor network with (Mobile Robotic System (MRS or Mobot), Immobile Robotic System (ImRS or Immobot), DataBase Management System (DBMS), Graphic Processing Unit (GPU), etc.) nodes of a Supercomputer Cluster (SuperCluster), grid, or network, and transformed the Interconnected network (Internet) into our Interconnected supercomputer (Intersup) on the basis of ontology, cybernetics, HardBionics (HB) and SoftBionics (SB) (e.g. Artificial Intelligence (AI), Machine Learning (ML), Artificial Neural Network (ANN), Evotionary Computing (EC), Computer Vision (CV), Cognitive Agent System (CAS), Multi-Agent System (MAS), Swarm Computing (SC), Artificial Life (AL), etc.), operating system (os), Humanistic Computing (HC or HumanC), Mediated Reality (MedR), and so on. The rest can be found on the website of our Ontologic System variants OntoLix and OntoLinux, and this website of OntomaX.

Obviously, the authors of GHT

in contrast to us with the integration of their works.

Obviously, we have to state more precisely our messages, notes, explanations, clarifications, investigations, and claims regarding the Associative Memory (AM) or Content-Addressable Memory (CAM), the P2P underlay techniques, and the landmark routing and geographic routing protocols made in notes of October, November, and December 2022.
And there is still a lot that was created with or was integrated by the creation of our OS, as also explained here.
Also, we have found again our source of inspiration and decisive prior art, which supports our other claims. And as we always say at such a point, if one door closes, then another door opens. :)
And we can also see where prior art ends and our creation begins.
But in addition to the integration of these works, we also expressed different ideas and solved different problems with the creation of our OS than the works presented in relation to large unstructured networks, including Wireless Ad hoc NETwork (WANET), Mobile Ad Hoc NETwork (MANET), mesh network, and sensor network, and Client-Server or Master-Worker, Cluster, P2P, including P2P overlay and P2P underlay, and so on.

Despite that a common goal is to solve the problems of TCP/IP

etc.,

• 1 work about NGN "[...] some people believe that this problem has been solved by applying techniques for Mobile IP. However, resource discovery mechanisms in P2P, the coexistence of various routing in ad-hoc networks, and data-centric concepts in sensor networks suggest the future importance of addressing" [Bingo!!!], and
• 1 work about Service-Centric Networking (SCN), though it only mentiones an aspect related to Mobile IP "Similar to Mobile IP [22 [IP mobility support for IPv4. August 2002]] the service router acts as a "home agent," but only temporarily to ensure successful resynchronization",

and

Also note that "[Data-Centric Storage (]DCS[)] provides a (key, value)-based associative memory" points directly to

Also note that we can exploit the existing

• Ontologic Geographic Information System (OntoGIS), including
  • OntoMap,
  • OntoGlobe, and
  • OntoEarth,
• Positioning or Location System, Navigation System, and Tracking or Locating System, and
• geographic and location Ontologic Applications and Ontologic Services (OAOS

and also

for optimization and other reasons.

Furthermore, we concluded that all entities concerned in governments, commissions, federal authorities, universities, research institutes, companies, artists, other individual persons, cliques, and other entities have understood this part of our OS several years ago already at least to a sufficient extent to make related decision, but as usual neither referenced our works nor communicated with us and asked for allowance and licensing.
Therefore, we got the impression once again that the legal defense could by quite difficult at the courts worldwide.
As we always say: Good parenting is a matter of luck.

This quote and comment most potentially will be added to the note Further steps and Ontologic Net Further steps of the 11th of January 2023.

19.January.2023

07:21, 08:26, 17:12, and 21:25 UTC+1
And next abuse of market power by Microsoft

We quote a report, which is about the Microsoft Azure OpenAI Service and was publicized on the 16th respectively 17th of January 2023: "[...]
Microsoft said it is vetting customers' applications to mitigate potential abuse of the software [of the other fraudulent company OpenAI based on SoftBionics (SB) (e.g. Artificial Intelligence (AI), Machine Learning (ML), Artificial Neural Network (ANN), Computer Vision (CV), Simultaneous Localization And Mapping (SLAM), Soft Computing (SC), Autonomic Computing (AC), Natural Language Processing (NLP), Cognitive Computing (CogC) or Cognitive System (CogS), Cognitive Agent System (CAS), Cognitive-Affective Personality or Processing System (CAPS), Swarm Intelligence (SI) or Swarm Computing (SC), etc.)], and its filters can screen for harmful content users might input or the tech might produce.
[...]"

Comment
The company Microsoft depends on our original and unqiue, copyrighted, and prohibited for fair use work of art titled Ontologic System, created by C.S., and exclusively managed and exploited by our corporation with the consent and on the behalf of C.S..
But several serious legal problems do exist for Microsoft:

We view such illegal actions in particular and such rejections of virtually every regulation of our SOPR by Microsoft and also other companies as the next reiteration of their declaration of insolvency and war against C.S. and our corporation, but also against the societies worldwide.

In fact, Microsoft and Co. are not able and do not show any interest to compete legally in the market and instead obstruct, frustrate, and even block freedom of choice, innovation, and competition for the benefit of the public, which even questions rule-based law and order and interferes in democratic processes somehow.
Sadly to say, virtually all governments, commissions, federal authorities, specifically federal investigators and market regulators, universities, research institutes, companies, artists, other individual persons, cliques, and other entities are truly interested in solving that social and societal disturbance and annoyance.
The only action is that usual production of hot air and blah blah blah.
Howsoever, as a side effect of their inactivity, they all have also confirmed that the Articles of Association (AoA) and the Terms of Service (ToS) with the License Model (LM) and Main Contract Model (MCM) of our SOPR are Fair, Reasonable, And Non-Discriminatory, As well as Customary (FRANDAC) terms and conditions no matter how they are drafted.

That specific strategy to chisel and scrape single parts of our OS off, simulate a technological progress, confuse the public, and so on is already over since the summer of 2017, because

• on the one hand the volumes of our works of art, performances, and achievements, and
• on the other hand their individual and mutual motivations, goals, strategies, methods,

• on the one hand the contours of our works of art, performances, and achievements and
• on the other hand their obivous act of
  • taking our works of art as sources of inspiration and blueprints, specifically the integration of said single parts of our OS in accordance to our composition and Ontologic System Architecture (OSA), and
  • encircling and besieging C.S. and our corporation, and shielding them from the public.

The same holds for all the many other illegal actions, supports, conspiracies of all the other entities under their individual groups and across these groups.
Even more worse and nasty, our demands are only taken to question, contest, attack, damage, and destruct our rights and properties, and our regulations are taken only to find weak spots for more and maximal attack, damage, and destruction.
They are not showing a serious commitment, but are only trying to infringe the rights and properties, and damage the goals and threaten the integrities of C.S. and our corporation, and eventually taking them for a ride.

We have already begun to create graphic presentations, which show how those illegal methods, scams, frauds, and crimes work in space and time, specifically

Also serious and ridiculous is the fact that other decisive activities of C.S. and our corporation, including our SOPR and our other Societies, cannot and will not proceed, if they will be started at all, for example in relation to the fights against

which all have already turned into chaos and the only strategy and plan of governments and their clique, which we see, is to continue as usual with infringing the rights and stealing the properties, as well as the strategy and plan of C.S. and our corporation.
Regarding these problems and the related transformation and modernization, our demands for the

of C.S. and our corporation, and our terms and conditions are a no-brainer.
But as we said in the past already, there is no understanding and no learning effect, and somehow we have the impression that blocking us is another one of their main goals and there will be no rip-off 3.0.

20.January.2023

17:44 UTC+1
MfE does apply for stock images as well

Marketplace for Everything (MfE)

We expect that stock image platforms, like for example the companies Getty Images and Shutterstock, provide their images on our Marketplace for Everything (MfE) exclusively, if said images are used for purposed related to our field of SoftBionics (SB) (e.g. Artificial Intelligence (AI), Machine Learning (ML), Artificial Neural Network (ANN), Computer Vision (CV), Cognitive Agent System (CAS), etc.), specifically for purposes related to training SB systems.

19:19 UTC+1
OntoBot and OntoSearch exclusive on all Os

Ontologic roBot (OB or OntoBot)
Ontologic Search (OntoSearch)
Ontoscope (Os)

The companies Alphabet (Google), Microsoft, and Co. depend on our original and unqiue, copyrighted, and prohibited for fair use work of art titled Ontologic System, created by C.S., and exclusively managed and exploited by our corporation with the consent and on the behalf of C.S..
Because of the various Fair, Reasonable, And Non-Discriminatory, As well as Customary (FRANDAC) terms and conditions of our collecting Society for Ontological Performance and Reproduction (SOPR),

• no Search System (SS) or Search Engine (SE),
• no Question Answering (QA) System (QAS),
• no Recommendation System or Recommender System (RecS),
• no chatbot,
• no speech recognition and no speech synthesis,
• no voice user interface,
• no Dialog System (DS or DiaS), including Dialogue Management System (DMS), and
• no Conversational System (CS or ConS), including Conversational Agent System (CAS or ConAS),

and definitely

• no Personalized Assistant that Learns (PAL)
  • no Reflective Agents with Distributed Adaptive Reasoning (RADAR) and
  • no Cognitive Assistant that Learns and Organizes (CALO),

which are based on our

• Peer-to-Peer (P2P) Search (P2PS) and Find (P2PF) and
• OntoP2PF,

is allowed and licensed on our Ontoscope (Os) and in our Ontoverse (Ov) as part of our original and unique work of art titled Ontologic System and created by C.S., because no modification of our Ontologic System (OS) exists, which would allow and license the performance and reproduction of certain parts of our OS in any other way, and no modification and no copy is required at all, because we have created the original and unique work of art, which already has all these features and functionalities.

As we already said in the last past, it is time for companies, including old online companies but also start-ups, to

in full compliance with

Simultaneously, legal proceedings worldwide to enforce the

of C.S. and our corporation, including the payment of triple damage compensations and a lot of other legal actions.

See also the notes selected for the sections Infrastructure [API and HMI] and Infrastructure [Search engine] of the issue SOPR #33p of the 13th of September 2022:

• Geographic Information Systems (GISs) (e.g. digital maps, digital globes, etc.),
• social and societal service platforms,
• electronic commerce platforms (e.g. marketplaces), and
• online advertisement, as well as
• models, architectures, frameworks, ontologies, and any other basic or foundational concepts, items, and so on (e.g. so-called foundation supermodels or Mixture of Experts)

based on our Evoos and our OS in one way or another. :)
We already discussed a little the matter in general and the common User Interface (UI) for search engines in particular (see the note SOPR considering search engines of the 30th of July 2022)."

Google, Microsoft, and other existing and new online companies adapted their existing and implemented their new search engines with generative Artificial Intelligence (AI) accordingly. We would say they all come just 16 years in case of generative AI and 10 years in case of those search engines too late. Is not it?
Google also adapted its library for website functions, so that the login message by the Google account is shown automatically when loading a webpage implemented with this library.

See also the notes

By the way:

23.January.2023

13:54 UTC+1
OS one and only legal TAI

*** Work in progress ***

Ontologic System (OS)
Trusted Artificial Intelligence (TAI) or Trustworthy Artificial Intelligence (TAI)

As we have seen with what is wrongly called cloud computing and as a Service (aaS) technologies (aaSx) (e.g. capability and operational models, (sub)systems, and platforms), the U.S.American National Institute of Standards and Technology (NIST) has once again taken content from our website without proper referencing, which constitutes the next infringement of our copyright for our original and unique work of art titled Ontologic System and created by C.S..
This time it is its Artificial Intelligence Risk Management Framework (AI RMF).

We quote the document titled "AI Risk Management Framework: Second Draft" and publicized on the 18th of August 2022: "The AI Risk Management Framework
This second draft of the NIST Artificial Intelligence Risk Management Framework (AI RMF, or Framework) builds on the initial March 2022 version and the December 2021 concept paper. It reflects and incorporates the constructive feedback received. [...]
[...]

The AI Risk Management Framework (AI RMF) Playbook
In concert with the release of the AI RMF second draft, NIST seeks comments on a draft companion AI RMF Playbook. The Playbook provides actions Framework users could take to implement the AI RMF by incorporating trustworthiness considerations in the design, development, use, and evaluation of AI systems. The draft Playbook is based on this second draft of the AI RMF. It includes example actions, references, and supplementary guidance for "Govern" and "Map" - two of the four proposed functions. Draft material for the "Measure" and "Manage" functions will be released at a later date.

[...]

Figure 1: Lifecycle and Key Dimensions of an AI System. Modified from [Organisation for Economic Co-operation and Development (]OECD[)] (2022) OECD Framework for the Classification of AI systems - OECD Digital Economy Papers. Risk management should be continuous, timely, and performed throughout the AI system lifecycle, starting with the plan & design function in the application context.

[...]

4. AI Risks and Trustworthiness
Approaches which enhance AI trustworthiness can also contribute to a reduction of AI risks. This Framework articulates the following characteristics of trustworthy AI, and offers guidance for addressing them. Trustworthy AI is: valid and reliable, safe, fair and bias is managed, secure and resilient, accountable and transparent, explainable and interpretable, and privacy-enhanced.
[...]

Table 1: Mapping of AI RMF taxonomy to AI policy documents.
[...]

Human Factors Since AI systems can make sense of information more quickly and consistently than humans, they are often deployed in high-impact settings as a way to make decisions fairer and more impartial than human decision-making, and to do so more efficiently. One common strategy for managing risks in such settings is the use of a human "in-the-loop" (HITL). [...]

[...]

Appendix A: Descriptions of AI Actor Tasks from Figure 1
AI Design [...]
AI Development [...]
AI Deployment [...]
Operation and Monitoring includes AI actors who are responsible for operating the AI system and working with others to continuously assess system output and impacts. Users who interpret or incorporate the output of AI systems, evaluators and auditors, and members of the research community are part of this group.
Test, Evaluation, Verification, and Validation (TEVV) tasks are performed by AI actors who examine the AI system or its components, or detect and remediate problems throughout the AI lifecycle. Tasks can be incorporated into a phase as early as design, where tests are planned in accordance with the design requirement.
[...]
Human Factors [...]
Domain Experts are multidisciplinary practitioners or scholars who provide knowledge or expertise in an industry sector, economic sector, or application area where an AI system is being used. These experts are essential contributors for AI system design and development and can provide interpretation of outputs to support the work of TEVV and AI impact assessment teams.
AI Impact Assessors [...]
Procurers [...]
Organizational Management, Senior Leadership, and the Board of Directors are among the parties responsible for AI governance.
End Users [...]
AI Operators continuously assess system recommendations and impacts (both intended and unintended) in light of the system's objectives as well as the ethical considerations that go into its operation. Operators can often be associated with the planning and design or specification stage of the AI system lifecycle as well as post-deployment monitoring.
Affected Individuals/Communities encompass any individual, group, community, or stakeholder organization affected by AI systems or decisions based on the output of AI systems, directly or indirectly. These individuals do not necessarily interact with the system and can be indirectly or directly affected by the deployment of an AI system or application.
Other AI actors may provide formal or quasi-formal norms or guidance for specifying and managing AI risks. They can include trade groups, standards developing organizations, advocacy groups, environmental groups, and civil society organizations.
The general public is most likely to directly experience positive and negative impacts of AI technologies. They may provide the motivation for actions taken by the other stakeholders and can include individuals, communities, and consumers in the context where an AI system is developed or deployed."

Appendix B: How AI Risks Differ from Traditional Software Risks
[...]"

Comment
The whole draft is based on our Ontologic System (OS), including our Evolutionary operating system (Evoos), specifically its basic properties, and our related messages, notes, explanations, clarifications, investigations, and claims.
See also once again the note Success story continues and no end in sight of the 17th of May 2022.

We also quote our message Success story continues and no end in sight of the 17th of May 2022:
"After 16 years, they found out that a so-called Trusted Artificial Intelligence (TAI) is needed. Guess what is taken as foundation? Hint: It is a belief system, which is purely rational and resilient (e.g. trustworthy), and has the basic properties of (mostly) being validated and verified, and specification- and proof-carrying, and a formal semantics, including formal operational semantics.

Our revolution based on our Evolutionary operating system (Evoos) and Ontologic System (OS) continues and there is no end in sight.
What comes now is a New Artificial Intelligence (NAI or New AI), because the whole big pile of semantic bull$#!+ must be cleaned up, ordered, and put together again. :D
As we said, they have stolen our properties, but will not keep them."

Comment
Also note that Ted W. Lieu, who represents California's 36th Congressional District in the U.S.American House of Representatives, was also not shy to mislead the public about the true origin of the creations, works, and achievements of C.S. and our corporation in an opinion respectively guest essay. "The fourth industrial revolution is here." Our revolution ....

So much about an environment with a rule-based law and order and a democracy and a culture and basic rights and freedoms and civilizations.

Of course, this already had consequences and we already acted and contained that next general activity of fraud and crime from several directions, for example

• Ontoscope (Os),
• operating system (os),
• Ontologic Applications and Ontologic Services (OAOS),
• Ontologic Net (ON) (what is wrongly called Grid Computing (GC), and Cloud, Edge, and Fog Computing (CEFC), Decentralized Web (DWeb), Web3, etc.),
• Ontoverse (Ov) (what is wrongly called metaverse),
• and so on.

See also the notes

We also added some kind of firewalls and gateways.

It will become extremely expensive to cure the actions of the companies Alphabet (Google)→DeepMind, OpenAI, Microsoft, Meta (Facebook), and Co. after they opened the Pandora's box with the release of their large Machine Learning Models (MLMs) made available to the general public, even as illegal Free and Open Source Software (FOSS).
The worldwide public should hold those utter morons and criminals accountable and not accept their democratization of their damages and destructions, as we do with their illegal democratization of the rights and properties of C.S. and our corporation, specifically the activity to "democratize AI as a new technology platform" based on our OS.

If their MLMs, and also technologies (e.g. systems, platforms, and also Service-Oriented technologies (SOx)), goods (e.g. software (e.g. applications), hardware (e.g. processors), devices, robots, vehicles), and services (e.g. as a Service (aaS) business models and capability models) satisfy the recommendations and the guidelines of the NIST AI RMF, then we have another evidence that shows a causal link with our OS.

We will see what the courts will say to this and in which area they will not have to pay triple damages, or even cease and desist, and stop operation.

We will also investigate the Organisation for Economic Co-operation and Development (OECD) for infringements of the rights and properties of C.S. and our corporation.

The tide has turned. The noose has tightened.

We already said in the Investigations::Multimedia, AI and KM of the 5th of August 2022 that it was totally clear that they will take the brute force approach, because it matches their usual business strategy based on their abuse of market power and therefore shows their illegal monopoly.
We also said that "[t]he next step would be more Cluster Computing and a so-called Global Brain, or being more precise, our

anyway" (see the Further steps, Ontologic Net Further steps of the 14th of November 2022), and therefore activities such as abuse of market power, criminal copyright infringement, blackmailing, wire fraud, securities fraud, commercial fraud, corruption, conspiracy, plot, and so on to circumvent us with

See also the

But what they developed so far is even not Frankenstein's brain, but Nasty Artificial Intelligence (NAI), like the Skynet of the Terminator saga, which now has the potential to set the world on fire. The latter reminds us of the first ignition of the hydrogen bomb (H bomb).

Now they want to solve the problem in the usual way, which also means by

But this does not solve the problem at all, because it only repeats all mistakes and illegal actions seen with for example the

(see also once again the quote of the NIST AI RMF above).
Even more ridiculous is the fact that the U.S.America is not able to solve its problems with weapons and mass shootings, and its Information and Communication Technology (ICT) monopolies, but now wants to solve the problem with AI, ML, Robotic Systems (RSs), and so on by the same approach.

So much about monetization and democratization of the rights and properties of individuals and societies.

21:00, 22:15, 23:24, and 25:51 UTC+1
Clarification

*** Work in progress ***
We took a closer look at the field of generative AI and are working on an investigation and a clarification about this field.
That entities acting in this field have stolen from us is for sure, because they do not create or invent, but just ony steal and market the original and unique ArtWorks (AWs) and further Intellectual Properties (IPs) included in the oeuvre of C.S., as we have proven again and again in more than the last 16 years. Therefore, not the motivation and the evidence are missing, but only the explanation of the causal link in a court-proof way is missing.

The prior art comprises individual foundational fields and integrations of them done by others and us.
Foundational fields

• Artificial Life (AL),
• Artificial Intelligence (AI),
• Machine Learning (ML),
• Computational Intelligence (CI), including
  • Fuzzy Logic (FL)==Computing with Words (CwW),
  • Artificial Neural Network (ANN), including
    • Multi-Layer Perceptron (MLP),
  • Evolutionary Computing (EC or EvoC), including
    • Evolutionary Strategy (ES),
    • Evolutionary Algorithm (EA),
    • Genetic Algorithm (GA),
    • Evolutionary Programming (EP),
    • Genetic Programming (GP),
    • Hybrid Evolutionary Computing (HEC),
    • and so on,

    and

  • Swarm Intelligence (SI) or Swarm Computing (SC),
• Soft Computing (SC),
• Computer Vision (CV),
• Computer Audition (CA),
• Simultaneous Localization And Mapping (SLAM),
• Computational Linguistics (CL),
• Natural Multimodal Processing (NMP) and Natural Multimodal Understanding (NLU),
  • Natural Language Processing (NLP),
  • Natural Language Understanding (NLU),
  • Natural Image Processing (NIP),
  • Natural Image Understanding (NIU)
  • and so on,
• Emotive Computing (EmoC) and Affective Computing (AffC),
• Emotional Intelligence (EI),
• Autonomic Computing (AC),
• Cognitive Computing (CogC),
• Cognitive Vision (CogV),
• Cognitive Agent System (CAS),
• Cognitive-Affective Personality or Processing System (CAPS),
• Common Sense Computing (CSC),
• Multi-Agent System (MAS),
• etc.,

• Logic Programming (LP),
• Generate 'n' Test (GnT),
• Rewriting Logic (RL),
• Fuzzy Logic (FL)==Computing with Words (CwW),
• etc.

• Search System (SS) or Search Engine (SE),
• Question Answering (QA) System (QAS),
• Recommendation System or Recommender System (RecS),
• chatbot,
• speech recognition,
• voice user interface,
• Dialog System (DS or DiaS), including Dialogue Management System (DMS),
• Conversational System (CS or ConS), including Conversational Agent System (CAS or ConAS),
• Multimodal System (MS or MMS), including Multimodal User Interface (MUI),
• Intelligent Agent System (IAS), including (voice-based or speech controlled) virtual assistant, Intelligent Personal Assistant (IPA),
• Robotic System (RS),
• and so on,

• Persistence of Vision Ray Tracer (POV-Ray),
• etc..

We quote an online encyclopedia about the subject POV-Ray: "The Persistence of Vision Ray Tracer, most commonly acronymed as POV-Ray, is a cross-platform ray-tracing program that generates images from a text-based scene description.
[...]
[...] The name "STAR-Light" (Software Taskforce on Animation and Rendering) was initially used, but eventually the name became "PV-Ray", and then ultimately "POV-Ray" (Persistence of Vision Ray Tracer),[2] a name inspired by Dali's painting, The Persistence of Memory.[7][8]"

Comment
But POV-Ray is not related to SB (e.g. AI, ML, CI (FL, ANN, EC, and SI), CV, CC, CAS, etc.) and therefore considerably different to generative AI, which is included in our OS, obviously and definitely.

Et voilà, we have a crystal clear causal link of the illegal DALL-E and our OS in addition to the causal link based on multimodality and our Evoos included in our OS.
But we want to show the fraud based on that textual transformer thing as well.

Integrations of foundational fields by prior art

Creations and integrations of C.S.

• Ontologic roBot (OB or OntoBot),
• Ontologic Search (OntoSearch),
• OntoBlender
  • ontologic programming, including
    • automatic programming,
    • literate programming,
    • natural language programming (see FL==CwW) and
    • multimodal multimedia programming,
  • game and interactive fiction generating, and
  • game engine
  
  
• Ontologic Applications and Ontologic Services (OAOS)
  • Algorithmic/Generative/Evolutionary/Organic ... Art/Science,

We quote an online encyclopedia about the subject Question Answering (QA): "[...]
[...] Latest systems, such as [Generative Pre-trained Transformer (]GPT-3[)], T5,[7] and,[8] even use an end-to-end architecture in which a transformer-based architecture is used to store large-scale textual data in the underlying parameters. These models can then be directly used to answer questions without accessing any external knowledge sources.
[...]
In information retrieval, an open domain question answering system aims at returning an answer in response to the user's question. The returned answer is in the form of short texts rather than a list of relevant documents.[12] The system uses a combination of techniques from computational linguistics, information retrieval and knowledge representation for finding answers.
[...]
In 2011, Watson, a question answering computer system developed by IBM, competed in two exhibition matches of Jeopardy! against Brad Rutter and Ken Jennings, winning by a significant margin.[31] Facebook Research has made their DrQA system[32] available under an open source license. This system has been used for open domain question answering using Wikipedia as knowledge source.[33] The open source framework Haystack by deepset allows combining open domain question answering with generative question answering and supports the domain adaptation of the underlying language models for industry use cases. [34][35]"

We also quote a report, which is about the field of generative Artificial Intelligence and was publicized today: "[A very rich man from Asia] is addicted to ChatGPT
[A very rich man from Asia]says he is addicted to ChatGPT, the powerful new AI tool that interacts with users in an eerily convincing and conversational way.
In a [social service platform] post last week, the [very rich man from Asia] said that the release of ChatGPT was a "transformational moment in the democratization of AI given its astounding capabilities as well as comical failures."
[...]
The tool, which artificial intelligence research company OpenAI made available to the general public late last year, has sparked conversations about how "generative AI" services - which can turn prompts into original essays, stories, songs and images after training on massive online datasets - could radically transform how we live and work.
Some claim it will put artists, tutors, coders, and writers out of a job. Others are more optimistic, postulating that it will allow employees to tackle to-do lists with greater efficiency.
"But there can be no doubt that generative AI will have massive ramifications," [a very rich man from Asia] wrote in his post, adding that generative AI holds the "same potential and danger" as silicon chips.
"Nearly five decades ago, the pioneering of chip design and large-scale chip production put the US ahead of rest of the world and led to the rise of many partner countries and tech behemoths [...]," [a very rich man from Asia] [...] wrote.
"It also paved the way for precision and guided weapons used in modern warfare with more chips mounted than ever before," he added. The race in the field of generative AI will quickly get as "complex and as entangled as the ongoing silicon chip war," he said.
Chipmaking has emerged recently as a new flashpoint in US-China tensions, with Washington blocking sales of advanced computer chips and chip-making equipment to Chinese companies. Some Chinese investments in European chipmaking have also been blocked.
[...]""

Comment
But an end-to-end architecture is still an

• Evoos with its EosA based on TUNES OS, AL, AI, ML, CI, NMP and NMU, and Humanistic Computing (HC or HumanC), and also human brain, and
• OS with its OSA.

But to make it court-proof we must show the artistical and technological details.

Since 2013 {links missing}, we discuss the fields of

in relation to our Evoos and our OS.
We have already explained that the so-called transformer, reformer, and transducer (e.g. perceiver) model and other models are based on the fields of Machine Learning (ML) and Artificial Neural Network (ANN), specifically MultiLayer Perceptron (MLP), and also concluded that such models are also based on our Evolutionary operating system (Evoos) and our Ontologic System (OS) to a significant extend, specifically when used as capability and operational model, cognitive model, including foundational cognitive model, including foundation model, or other coherent ontologic model (see also the note More evidence transformer model, etc. based on OS of the 11th of January 2023).

A Machine Learning Model (MLM) and an Artificial Neural Network Model (ANNM) or a Large Language Model (LLM) are data stores, which in case of an ANNM compresses and stores data as parameters of an ANN respectively nodes, connections of these nodes, and weights of these notes.
Obviously, we have here technologies, goods (e.g. applications), and services, which are based on a

and therefore an organic model and a bionic system, and therefore our Evoos.

We also quote our Clarification of the 14th of May 2016:
"[...] OntoBot software component of of our OS with its well-structured and -formed, validated and verified, and kernel-less reflective/fractal/holonic properties and rule-based and rewrite rules subsystems. Compare this with the content of the section 2. Computational Linguistics of "From Computational Linguistics to Computing with Words", specifically with "Certainly, linear aggregation of these symbols serve to understand and control one type of observable natural language phenomena as part of aggregational string formation or formal grammar. Its core concepts of well-formedness (syntax) and truth-function (semantics) were made explicit by way of specifying conditions of formal correctness and derivational compositionality. Their symbolic representations in the form of productions or rewrite rules - allowing for recursive application and generative string formation - not only constituted a wealth of symbol aggregation systems (formal languages) but were also employed to model comparable properties (in processes) of natural language string formation.
[...]"

Comment
Bingo!!!

Computational Intelligence (CI) (Fuzzy Logic (FL)==Computing with Words (CwW), Artificial Neural Network (ANN), Evolutionary Computing (EC or EvoC), and Swarm Intelligence (SI) or Swarm Computing (SC)) and Soft Computing (SC) are no legal loophole, because we already integrated it with the

So we were definitely before all the others, who have taken our Evoos and our OS as source of inspiration and blueprint without allowance.
This becomes even more clear with the integration of all the other individual fields and all the other parts and components of our Evoos and our OS.
The later also shows once again that AI is an island technology from the legal point of view.

We also quote our note OS too large to steal of the 15th of May 2016:
"Everytime a defrauding entity stops to give informations, we can go on and

Only an original creator, author, or/and developer is able to act in this way.
In the course of the discussion about a suspicous or defrauding work, it also becomes obvious that a part has been described by an entity that so to say is freely hanging in the air respectively unconnected with the rest of what we show with our Ontologic System (OS).

Whoever the criminal entities are behind all those frauds we are investigating, discussing, explaning, breaking down, and documenting, in the end they cannot use the stolen fractions of our OS, such as the combinations or integrations of for example:

because on this level such an acting always constitutes a causal link with our OS respectively with the OS of C.S.."

Comment
Bingo!!!
Now, we do know that they tried it since we said it and also that the whole case has become a mere formality at the courts worldwide.

We also quote our Clarification of the 15th of June 2016:
"We are sure, that some of our fans and readers wondered about the statement "All the rest is in our Ontologic Web (OW), the World Wide Web of the next generation: [...] every game" given in the presentation OS is ON of the 9th of May 2016.
[...]

Et voilà, our OS simply takes the contents of the ON and OW, and generates all kinds of computer or video games, as it is already done with news and reports for example.
These generation, execution, and gaming processes can also include contents provided by a user or a specific group of users as some kind of Massively Multiplayer Mixed Reality Online Costume Role-Playing Game (MMMROCRPG).

Needless to say, that this kind of generating technology is applied as well for everything else, that we have listed in the presentation OS is ON.

A genious, original and unique multimedia work of art masterpiece of C.S., copyrighted and legal (no causal links with copyrighted computer or video games and other works, and if so, then fair use, because this work is literally spoken generative and transformative).

[...]"

Comment
Bingo!!!
Read the whole clarification once again.

Read also the

23:34 and 25:44 UTC+1
OpenAI ChatGPT next copyright infringement

And not merely an infringement of the rights and properties of C.S. and our corporation, but serious crime, as not expected otherwise.

In this relation, we would like to recall that in accordance with the Fair, Reasonable, And Non-Discriminatory, As well as Customary (FRANDAC) Terms of Service (ToS) with the License Model (LM) of our Society for Ontological Performance and Reproduction (SOPR), the common

• Artificial Intelligence as a Service (CIaaS) technologies (AIaaSx),
• Machine Learning as a Service (MLaaS) technologies (MLaaSx),
• Computational Intelligence as a Service (CIaaS) technologies (CIaaSx),
• Artificial Neural Network as a Service (ANNaaS) technologies (ANNaaSx),
• Computer Vision (CV) as a Services (CVaaS) technologies (CVaaSx),
• and so on,

are parts of the exclusive infrastructures of our SOPR in our

and no other entity is allowed to perform and reproduce this part of our OS as part of the fields of

• Grid Computing (GC),
• Cloud, Edge, and Fog Computing (CEFC),
• Service-Oriented technologies (SOx), and
• as a Service (aaS) (business) capability and (cloud) operational models (aaSx)

and

This includes OAOS, like for example

24.January.2023

20:47 UTC+1
SOPR considering OfficeaaSx with SBaaSx

Since around the year 2005, we have in stock of our OntoLab, The Lab of Visions, our Hightech Office Ontonics, and our business units Ontologics and SoftBionics the one and only original and unique, and therefore legal integration of

which is ready for provision as Ontologic Applications and Ontologic Services (OAOS)

• SoftBionics (SB) backbones, core networks, or fabrics, and also subsystems and platforms (SBx),
• SoftBionics (SB) Service-Oriented technologies (SBSOx), and
• SoftBionics as a Service (SBaaS) business models and capability models (SBaaSx), including
  • Artificial Intelligence as a Service (CIaaS) technologies (AIaaSx),
  • Machine Learning as a Service (MLaaS) technologies (MLaaSx),
  • Computational Intelligence as a Service (CIaaS) technologies (CIaaSx),
  • Artificial Neural Network as a Service (ANNaaS) technologies (ANNaaSx),
  • Computer Vision (CV) as a Services (CVaaS) technologies (CVaaSx),
  • and so on,

of the exclusive infrastructures of our Society for Ontological Performance and Reproduction (SOPR) in our

• Ontologic Net (ON),
• Ontologic Web (OW), and
• Ontologic uniVerse (OV),

which collectively are our Ontoverse (Ov) and New Reality (NR), and

• search engine,
• Question Answering (QA) system,
• recommendation system or recommender system,
• chatbot,
• office software,
• Business Intelligence (BI), Visualization, and Analytics (BIVA), and Data Science and Analytics (DSA),
• Electronic Commerce (EC),
• and so on.

Please note that all other provisions are illegal plagiarisms of the original and unique ArtWorks (AWs) and further Intellectual Properties (IPs) included in the oeuvre of C.S. (see also for example the Clarification and the note OpenAI ChatGPT next copyright infringement of the 23rd of January 2023 (yesterday)).

By the way:

• no further infringement of the rights and properties of C.S. and our corporation,
• no further mimicking of C.S. and our corporation,
• no sale of the rights and properties of C.S. and our corporation,
• no control of the of the rights and properties of C.S. and our corporation by another private entity,
• no other licensing for the parts of our Evoos and our OS than authorized by our SOPR, which means no Free and Open Source Software (FOSS),
• no other technologies (e.g. systems, platforms, and also Service-Oriented technologies (SOx)), goods (e.g. contents, software (e.g. applications), hardware (e.g. processors), devices, robots, vehicles), and services (e.g. as a Service (aaS) business models and capability models) for common things (e.g. openly available raw signals and data, informations, knowledge bases, models, and algorithms), and
• no support of an entity that is damaging the goals and even threatening the integrities of C.S. and our corporation (e.g. Apache Foundation, Linux Foundation, (former) OpenAI, and so on).

Where is the problem with this absolutely Fair, Reasonable, And Non-Discriminatory, As well as Customary (FRANDAC) terms and conditions?

25.January.2023

02:40 UTC+1
SOPR continuing transition phase

Our Society for Ontological Performance and Reproduction (SOPR) is continuing the transition phase, which comprise the

of C.S. and our corporation.
In doing so, we are placing particular emphasis on

The next steps of this transition phase would have been actions, which matches our decision to reduce the scope of modifying and opening our OS with its OSA, OSC, Ontoscope, OsC, and Ontoverse (Ov) to a certain extent in compliance with the decisions of governments, commissions, federal authorities, companies, and other entities (they do not want to break up illegal monopolies of their cliques).

But we also keep in mind the further modification and opening of our OS and revision and adjustment of the License Model (LM), by decreasing the royalties (e.g. fixed fees and relative shares), though this has been shifted by some years and will only be considered when the collecting SOPR is working properly, which includes that the triple damage compensations are being collected and other required legal actions have taken place.
will not be reduced, because of

We also heard something like 7 and 17, 3 and 17, and 51, but we are not sure to 100%, what that should mean, and honestly, if this should mean something relevant.

28.January.2023

03:47 and 05:18 UTC+1
ChatGPT infringes copyright of others and us

While the general expression of idea was already created and presented with our orignal and unique work of art titled Ontologic System and created by C.S., including our orignal and unique work of art titled Analyse und Entwurf eines Betriebssystems nach evolutionären und genetischen Aspekten==Analysis and Design of an Operating System According to Evolutionary and Genetic Aspects (see the The Proposal), also titled Evolutionary operating system (Evoos), cybernetic self-portrait, etc. (see the webpage Overview of our Ontologic System (OS) OntoLinux), the long results of the Question Answering (QA) system, recommendation system, chatbot, text generator, generative art creator suggests that the expressions of ideas of other creators are taken as source of inspiration and blueprint. Therefore, results have to be compared with original and unique works of art to validate and verify that no copyright is infringed.

But for doing so, one is once again acting in the legal scope of ... the Ontoverse (Ov), aka. OntoLand (OL).
But the whole Machine Learning Model (MLM) must be entangled, resolved, uncrompressed, decrypted once again, which shows that the whole approach is flawed and error by design and greed.
No, ladies and gentlemen, that brainless brute force trick and illegal trick does not work for civilization.
That is only AI crap exactly like crypto crap working in the same way as a scam, following the same business strategies and goals, and trying to steal the same (hint: our OS), and only adds to all the other illegal and even serious criminal actions.

See also the notes

of the 23rd of January 2023

By the way:

• adapt their businesses and transfer their accrued talents and competences to our new environment, which requires the allowance and license for the performance and reproduction of certain parts of our OS, and
• implement their goods (e.g. applications) and services as Ontologic Applications and Ontologic Services (OAOS) on the basis of our Ontologic System Architecture (OSA), and publicate them on the Marketplace for Everything (MfE) of our collecting Society for Ontological Performance and Reproduction (SOPR) exclusively

  in full compliance with

• national and international laws, regulations, and acts, as well as agreements, conventions, and charters, and
• Fair, Reasonable, And Non-Discriminatory, As well as Customary (FRANDAC) Terms of Service (ToS) with the License Model (LM) of our SOPR.

29.January.2023

03:31, 05:20, 15:00, and 20:24 UTC+1
Clarification
OpenAI ChatGPT next copyright infringement

We have forgotten to add some more informations and explanations to our Clarification of the 23rd of January 2023 (see also the note OpenAI ChatGPT next copyright infringement of the 23rd of January 2023).

Another resolution of the acronym GPT could be Genetic Programming Transformer, which would explain

• EC adds creativity to the AI and CogS, and
• Genetic Programming (GP) even expands and growth the AI and CogS further.

In addition, we note

• Artificial Intelligence (AI), Machine Learning (ML), Computational Intelligence (AI), Fuzzy Logic (FL), Artificial Neural Network (ANN), Evolutionary Computing (EC or EvoC), Affective Computing (AffC), Soft Computing (SC), etc. in general,
• Algorithmic/Generative/Evolutionary/Organic ... Art/Science (here writing, including programming) in particular,

  utilized as

• chatbot,
• Dialog System (DS or DiaS), including Dialogue Management System (DMS),
• Conversational System (CS or ConS), including Conversational Agent System (CAS or ConAS),
• text generator, including software source code, and
• emulation of a Linux system,

and therefore not merely only a chatbot, but a partial plagiarism of our Evoutionary operating system (Evoos),

OpenAI gets no license for SoftBionics as a Service (SBaaS) business models and capability models (SBaaSx), including Machine Learning as a Service (MLaaS) technologies (MLaaSx) and Artificial Neural Network as a Service (ANNaaS) technologies (ANNaaSx), because there exists only our original and unique OS, including all basic Ontologic Applications and Ontologic Services (OAOS) platforms, and SBaaSx is part of the subsystems and platforms of the exclusive infrastructures of our Society for Ontological Performance and Reproduction (SOPR).

In general, such so-called Machine Learning Models (MLMs) and Large Language Models (LLMs) are based on raw signals and data, informations, knowledge bases, models, and algorithms, which are common to all members of our SOPR and even include themselves as a common good. Therefore, said MLMs and LLMs are in the exclusive scope of our SOPR, but not exclusive for OpenAI, Microsoft, or any other entity. According to the Terms of Service (ToS) of our SOPR OpenAI and all other entities have to provide all such MLMs and LLMs to our SOPR for integration with other MLMs and LLMs, if reasonable, then for their cost price (of their implementation and training), which are payed by our SOPR, which again means they would be offset against the overall damage compensations, including unpaid royalties, admission fees, as well as running royalties. This is truly democratic.
In general, nothing will be

In particular, if that scam company refuses to comply with

then it will get a cease and desist order by courts worldwide.

The temporal advantage of OpenAI also shows that all responsible founding members and supporting entities only have and pursue the strategy and the goal to infringe and democratize the rights and properties, damage the goals and threaten the integrities of C.S. and our corporation as much as possible, and eventually to destroy and eradicate them.
Obviously, we have here the next nasty and dirty Sam ...man and about the other very well known and already named bad actors we do not need to talk here anymore.

See also the note ChatGPT infringes copyright of others and us of the 28th of January 2023 (yesterday).

By the way:

Application
Poet
In May 2017, the first AI-authored collection of poems-["]The Sunshine Lost Windows["] was published by Xiaoice.[12]

Singer
Xiaoice has released dozens of songs with the similar quality to human singers, including ["]I Know I New["], ["]Breeze["], ["]I Am Xiaoice["], ["]Miss You[",] etc. The 4th version of the DNN singing model allows Xiaoice to learn more details. For example, Xiaoice can produce this breathing sound along with her singing as human.[13]

Kid Audio-books Reciter
Xiaoice can automatically analyze the stories, to choose the suitable tones and characters to finish the entire process of creating the audio.[14]

Designer
By learning the melodies of the songs and the landmarks about different cities, Xiaoice can create visual artworks of skylines when listening to the songs related to this city.[15] Skyline Series T-shirts designed by Xiaoice have been jointly launched with [a company] and been sold in stores.[16]

[...]

AI being
AI being, that is super natural virtual human, the AI being concept proposed by the Xiaoice team in 2019 [17]
According to the "White Book of China Virtual Human Development Industry in 2022" released by Frost & Sullivan and LeadLeo, the white paper cites the six elements of AI being proposed by the Xiaoice team, including: Persona, Attitude, Biological Characteristic, Creation, Knowledge and Skill, believes that AI being has more potential and can represent a trend than relying on CG modeling and Meta human driven by the man in the middle.[18][19][20][21]
[...]
Bill Gates mentioned Xiaoice during his speech at the Peking University:
"Some of you may have had conversations with Xiaoice on Weibo, or seen her weather forecasts on TV, or read her column in the Qianjiang Evening News."
'"Xiaoice has attracted 45 million followers and is quite skilled at multitasking. And I've heard she's gotten good enough at sensing a user's emotional state that she can even help with relationship breakups."[22]
[...]"
We also quote an online encyclopedia about the chatbot Tay of the company Microsoft: "Tay was an artificial intelligence chatbot that was originally released by Microsoft Corporation via Twitter on March 23, 2016; [...]
[...]
The bot was created by Microsoft's Technology and Research and Bing divisions,[3] and named "Tay" as an acronym for "thinking about you".[4] Although Microsoft initially released few details about the bot, sources mentioned that it was similar to or based on Xiaoice, a similar Microsoft project in China.[5] Ars Technica reported that, since late 2014 Xiaoice had had "more than 40 million conversations apparently without major incident".[6] Tay was designed to mimic the language patterns of a 19-year-old American girl, and to learn from interacting with human users of Twitter.[7]
[...]"
Comment
Double Bingo or Triple Bingo???
Another time that we got Bill Gates by the balls. That trick with stealing our properties by a camouflaged development in Asia did not work either (see also the (temporary) message Oh, what ...? of the 20th of January 2018 once again). And we already have solved the whole puzzle around the years 2016 to 2018, which took a few more years to fully prepare and present the whole case, but is now ready for processing at the courts worldwide in case of Microsoft, its founders, its managers, as well as other companies, founders, managers, and so on. And with our actually implementation of Artificial Intelligence 3 (AI 3) and training of an Artificial Neural Network (ANN) we even get many other entities by the balls, of course completely free of hallucination.

• national and international laws, regulations, and acts, as well as agreements, conventions, and charters, and
• Fair, Reasonable, And Non-Discriminatory, As well as Customary (FRANDAC) Terms of Service (ToS) with the License Model (LM) of our Society for Ontological Performance and Reproduction (SOPR).

If this measure is not sufficient to enforce all the rights and properties of C.S. and our corporation, then we will initiate a cease and desist order by a court.

• national and international laws, regulations, and acts, as well as agreements, conventions, and charters, and
• Fair, Reasonable, And Non-Discriminatory, As well as Customary (FRANDAC) Terms of Service (ToS) with the License Model (LM) of our SOPR.

30.January.2023

Style of Speed Further steps

In the last week from the 25th to 30th of January 2023, we developed and designed a variant of a vehicle to make it operational on a large scale.
Models have been tested for more than 3 years and proven its very astonishing performances and very high safety, which must and can be seen to believe.

Roboticle Further steps

We developed and designed basic variants of service robots, including delivery robots, which solve a basic problem.
The question is now which variant is more advantageous in the practice.