Wisdom Engine

It is very simple; consensus is provided to the entire network incredibly efficiently in an ultra fast manner due to the formation of a giant component in the network that develops as a result of an ultra connected small-world system. As such, the primary element and aspect required to run a node are network conductivity and propagation.

The present paper deals with one component of that system, namely the establishment and execution of such a contract, i.e. the flow of information between the different (computer) agents which will effectively implement the contract. Although the detailed specification of such a computer system is of obvious practical relevance as well, it is not the topic of this paper; an example of such a system has been presented elsewhere, see [2] and references therein. Very generally, we will refer to this system as a Botman (agent), often without specifying which agent actually carry out the actions described, this could be one of the lower-level bots, a bot manager or any other appropriate entity as, for example, those specified in [2].

I did a master’s degree in statistics, in part to learn what I know now and also to understand propagation methodologies. It was during my studies that I first read a paper called “Ultrafast Consensus in Small-World Networks” [1]. Following the discovery, I spent years going down the rabbit hole of Newman and Watts [3]. The node structure in Bitcoin is linked to the ledger. Blacknet was a dead end not because it didn’t work but because some of the earlier methodologies that are completely separate to Bitcoin now worked anonymously. An anonymous system will never be scaled to the world. At best, an anonymous system forms a methodology for black markets and illicit and illegal trade. I was never interested in creating a dark-web money.

Rajasekaran et al. (2022) demonstrate the problem when researchers focus on papers published within the last 3 to 5 years, compared to incorporating an analysis of terminology and data from earlier times. In doing so, the authors take material built upon blog posts and papers that have not been peer-reviewed and integrate them into an analysis of blockchain technologies while ignoring earlier research into digital payment and peer-to-peer network systems. For example, the structure of Bitcoin follows a small-world network design (Watts & Strogatz, 1998). Such a structure is now well known and documented, but is depreciated based on the age of the paper and when referencing alternative descriptions of decentralisation, based on alternative descriptions of the word, such as those from Marx and which lie outside of network science.

It is necessary to note that the hype given to blockchain-based solutions can lead to false claims of solving problems that are structured differently than the researcher notes. For instance, Zhao et al. (2023) argue that blockchain technology will solve fraud within supply chains. While Zhao et al. (2023, p. 2) note that “it is possible to fraud [sic] by informational deviation, recording false, or others, which dues to not accurate or timely verify the financing information,” they overemphasize the immutability of data, ignoring the ability to enter false information. The paper falsely notes that an unalterable log source will mitigate all fraud, while not noting that significant frauds are currently committed using blockchain-based technology (Corbet, 2022).

Chawla et al. (2019) proposed �?Velocity’, a new protocol to improve block propagation in blockchain networks through rateless erasure coding. Their idea emerges from recognizing block propagation as a vital factor influencing blockchain performance and scalability. Yet, their assumption of blockchain networks as vast, mesh-based systems is a critical point of contention. It contradicts the operational realities of networks like Bitcoin, which operate more as small-world networks where most nodes are interconnected, reducing the hops necessary for block propagation. Thus, while the �?Velocity’ protocol presents an academic progression, its practical relevance may be limited because of the disparity in network structure assumptions.

A colleague from nChain and myself published a proof of the Small World nature of bitcoin [1]. This is important in demonstrating the propagation method used within bitcoin. The so-called Sybil attacks are modelled falsely on the notion of being able to inject additional hops within the bitcoin network. Unfortunately, the pseudo-academics behind this notion never bothered to test their limited hypothesis.

Many think that coins will be able to just fork and act in a “permission-less” manner. We have seen this with ABC’s move to promote WormHole and bucket shops using OP_DataSigVerify (DSV), a poorly thought-out, new OP_Code that was added to ABC (changing it from Bitcoin to a speculative gambling system).

Registration and KYC. An entity (such as a private company) that wishes to become a Automata-Management SP will need to establish interfaces for interacting with their clients and with the hosts on the hostnet. This will involve common practices such as maintaining KYC (Know Your Client) databases including login and password protocols. For a Automata-Management implementation these databases should record information important for the operation of the system. For example, the SP might wish to keep a record of the hosts’ available computer resources (i.e. their computer specifications and data storage capacity, etc.) in order to ensure that any bots to be executed by the host are able to run effectively. In addition, the hosts’ preferences may be recorded to ensure that only ‘suitable’ bots are executed by them. As part of the SP’s registration process for both clients and hosts, the SP may wish (or be required by regulation) to vet them based on (for example) reputation; credit rating, or other criterion.

To securely encrypt a session, we have techniques that have already been developed. The use of symmetric-key encryption and one-time pads provide the ability for an organisation to set access policies and controls that maintain confidentiality and allow the data to be maintained privately, whether inside a firewall or on the web.

In the paper “On Red Balloons and Bitcoin,” [1] the authors provide proof of the theorem saying: Suppose that H ≥ 3. There is no Sybil-proof reward scheme in which information propagation and no duplication are dominant strategy for all nodes at depth 3 or less. They go on to develop a Hybrid propagation scheme. The authors did not test the Bitcoin network and, as most do, assumed that it is a distributed mesh as we see in Fig. 1 [c]. In the chart, the distance is an average of d>5 for only a few hops and nodes.

None of the researchers have studied Bitcoin enough to see that it is none of the ones in the chart, but rather it forms a small-world [2] network (Fig. 2). As such, as the hosts become more connected, they can come closer and closer to forming a semi-complete graph. If you read the original Bitcoin white paper, it is clearly and distinctly defined.

To be compliant, “crypto” exchanges require an immutable archiving system capable of archiving all necessary ESI. And not just capable — one that is in fact capturing all of the information. The mere archiving of data is not sufficient; it must be archived in an immutable format to meet compliance standards.

It was a rather surreal experience; the poor guy at the counter of the tourist refund centre did not know what to do. The computer had a field in the database that had a maximum value of $9,999,999.99, and he could not enter the amount that I was taking. The purpose of such an exercise was not to get a refund. It worked exactly as I’d hoped. It’s not always good to poke a bear, but it needed to be done; the imposition of GST on Bitcoin was ridiculous.

- Step 1 : Question. The “thing” that you want to know. - Step 2 : Research. Conduct research. - Step 3 : Hypothesis. Educated guess or prediction of the outcome experiment. - Step 4: Experiment. Test the hypothesis. - Step 5: Observations. Data you collect during the experiment. - Step 6: Results/Conclusion. - Step 7: Communicate.

If Bitcoin catches on on a big scale, it may already be the case by that time. Another way they can become more practical is if I implement client-only mode and the number of network nodes consolidates into a smaller number of professional server farms. Whatever size micropayments you need will eventually be practical. I think in 5 or 10 years, the bandwidth and storage will seem trivial.

The existence of databases and ledgers precedes Bitcoin. Interestingly enough, distributed databases have existed for decades. The distributed nature of Bitcoin is such that it allows unrelated entities to compete in maintaining the ledger. As such, if a single entity becomes bankrupt or goes out of business for some other reason, it is unnecessary to be concerned about the state of the ledger. In other words, even if individual parties involved in the management of the system suffer a disaster or catastrophic loss, Bitcoin continues to operate.

The distributed ledger in Bitcoin is “a collection of independent works, data or other materials which are arranged in a systematic or methodical way and are individually accessible by electronic or other means” [15]. The database right protects the collated information itself. Under the same regulation, the initial owner of the database right is the maker of the database [16]. Bitcoin and any blockchain-based system would be covered for the publication period of at least 15 years. Retrospectively, Bitcoin itself, the database was published formally in mid-January 2009.

Some things changed with the advent of computerised ledger systems. Accounting databases became easy to copy and easy to alter. Although high-end specialist accounting systems, including Oracle-based solutions, allow organisations to ensure that such scenarios are not possible, many fraudulent organisations have found simple ways of bypassing controls using technology. Bitcoin can solve all of the prevalent issues.

As explained, the primary nodes are all highly connected in a near-complete graph. Here, we see that over 98% of the network CPU power is directly connected. That is, it is connected by a single hop. As such, any transaction sent by a user to even a single node will be with almost every other network node in one further hop. Such commercial servers pay for high bandwidth, high-capacity routers, and network equipment. In all events, the connectivity between network nodes exceeds the connectivity of all client nodes.

Nodes in the Bitcoin network are what I, at first, called network nodes. When I was referring to them as systems that would end up in data centres, I was not referring to single machines. A node does not need to be an individual computer. Even now, an individual computer is made of multiple cores and separated into a variety of highly linked systems. In effect, even a local desktop computer or a laptop really consists of multiple computers. Having said so, a network node, a node on the Bitcoin network, would be made up of many systems. It will include the routers, the databases, and all the different equipment, systems, and networks necessary for handling the creation and propagation of blocks.

As Williamson (2020) reports, Sowell has been diligent in collecting a wealth of empirical data to support his case—overwhelmingly. Statistics can be used and misused (Spirer, 1998), but when correctly categorised, the information reveals a fascinating story: “White students in Texas outperform white students in Iowa, Hispanic students in Texas outperform Hispanic students in Iowa, and black students in Texas outperform black students in Iowa. But Iowa is very, very white, and Texas is not”. Many charter schools have been founded in traditionally poverty-ridden areas where the students had been failing. The contrast between states is not correctly categorised when averaged, because of the difference in composition based on location. Still, it is preferably rendered when you take the schools and analyse them against the structured categorisation of the data. As Williamson notes, when Sowell does so, the consequence of employing new teaching methods may be readily seen. The evidence as obtained through analysing the numbers leads to a proverbial “bloodbath”—counter to the position of those opposing charter schools.

Yet, the concept of distributed networks also applies to small-world networks. A small-world network encapsulates the benefits attributed to centralised and distributed networks described by Baran (1964). Consequently, the use of the paper by those in the ‘cryptocurrency’ industry in referring to the political decentralisation of Bitcoin may be demonstrated to be aligned with the original concepts of the work on communication networks. The author noted how distributed networks had better survivability. The features within blockchain networks integrate such benefits, providing a more secure network than those offered by traditional centralised systems, including banks.

The research presented by Cimini et al. documents the statistical physics and algorithmic analysis of network modelling and analysis as it has been developed, in the past two decades, in association with complex networks and related phenomena. The primary focus of the paper is associated with a combination of information theory and statistical physics. Such methods can be applied to analyse complex real-world networks, including blockchain-based systems. The weakest contribution the authors present is the approach that allows for creating null models of complex networks and hence the ability to analyse and study networks through experimentation. Such null models can aid in analysing existing networks, and provide frameworks that help explain complex network systems.

The research presented in this paper demonstrates the fundamental disconnect between the global financial industry, the mobile payment industry, and the original concept of micropayments over the internet. Such an approach fails to integrate the benefits of micropayments and provide information concerning the lack of research and development in the micropayment space. Equally, the papers researched fail to comprehend the benefits that can be achieved through small-scale data processing and sales across geographically dispersed distances.

The authors argue that integrating blockchain systems with algorithmic control through what is termed a “smart contract” enables the shifting nature of code that has the effect of law associated with the new concept of law being developed as code. While such an argument extends the crypto-anarchist concept of ‘code as law’ presented by Lessig (2000), the subjects of law and contractual control remain misunderstood. The argument presented by the authors creates a false dichotomy of issues by misrepresenting contract law and the nature of contracting. Most critically, systems including electronic data interchange (EDI) have already existed and allowed the direct machine-to-machine exchange of information for decades (Dearing, 1990).

Bodó et al. (2021a) present an analysis of decentralisation, looking at the advantages and disadvantages reported within the industry. Unfortunately, their approach fails to capture the underlying scientific nature of the system and delivers a report that captures the belief or aspirations of individuals within an industry. Unfortunately, it further compounds the misunderstanding of distributed and diverse networks, making claims that are provably false in assuming that the cost of maintaining nodes and providing bandwidth was higher in a distributed network than in a more centralised system. This assumption is important to be considered in my research, as demonstrating that decentralisation leads to cost reductions, and not an increase in maintenance costs, will change the existing narrative and lower the cost of ownership of information systems for many businesses.

Next, the input and output values for opening and closing channels were recorded. Where the total transaction was over 0.1 BTC for either the opening or the closing of transactions to start or close a channel on the Lightning network, a 1 was recorded in the database. Where the value was under 0.1 BTC, a 0 was recorded. The information was limited to February 2023, and where none of the entity information was captured, the information was excluded. A total of 363 transactions with reused and referenced BTC addresses were extracted for the analysis.

Zhao and Huang (2020) are junior professors in the department of geography at the University of Washington and at the School of Geography at Nanjing Normal University, China. As with earlier studies of distributed networks, including the internet (Lindsay, 2006), many changes in global demographic interactions can be attributed to network effects (Chen et al., 2019). In addition, Zhao researches human geography as it intersects with technology, looking at concepts such as location spoofing. Other papers by the same author include the integration of contact tracing systems with the migration of COVID-19 (Yu et al., 2022) and work on labor relations and automation and how they will transform capital allocation (Zhao, 2023).

The development of small-world networks and giant-node structures has been featured in a series of previous analyses of social networks (Goto et al., 2018). Consequently, the focus on an inverse distance law by Levy (2010, p. 4915) would be the strength of testing alternative network structures, either statistically rejecting the hypothesis of alternative network types or accepting that there could be an overlap or integration beyond a power-law fit.

The topic of energy consumption, as it is associated with digital currency, has been a hotly debated one over the last decade (Greenberg & Bugden, 2019). While digital currencies are transferred in cyberspace, the electricity associated with the transfer and verification of transactions is produced in physical locations and will be associated with energy use in a geographically defined area. In addition, creating data centres requires energy, high-speed network access, and political stability (Shuja et al., 2016). As such, digital currency is a system within virtual geography while also being constrained by the physical world.

The papers analyzed here offer a varied perspective on blockchain technology, supply-chain resilience, and innovative idea propagation in multi-agent networks. Each contributes to its respective field, while inviting further scrutiny and exploration.

Stoykovet et al. (2017) similarly ventured into blockchain network simulations with their tool VIBES. Designed for large-scale P2P networks, VIBES aspires to overcome the computational limitations that traditional simulators grapple with. Yet, like Chawla et al. (2019), the VIBES model assumes a mesh network structure, diverging from the small-world configuration of real-world blockchain networks. Moreover, the utility of VIBES in effective and accurate blockchain simulation could be compromised because of its failure to accurately represent actual network dynamics.

Finally, Shekfeh and Minai (2021) provided a fresh perspective on the propagation of innovative ideas within a multi-agent network model. Based on implicit learning and cognitive diversity, their model presents a compelling framework for understanding how novel ideas emerge and spread. Yet, the authors could delve deeper into how modern technologies like AI and blockchain could influence this process, a topic that remains relatively unexplored.

[[21]](file:///D:/Data/Publishing/2010%20PhD/2011%20PhD%2011%20-%20SECAU%201/#_ftnref21_5031) Dixon J elucidated how a “special relationship” of this variety may occur in Smith v Leurs (1945) 70 CLR 256. This case was derived from an indication of occurrences that entail a special danger and the control or of actions or conduct of the third person; See also [2000] HCA 61, para 140.

The main advantage to a system’s engineering approach is the ease with which it can be automated. Various inputs and formula can become inputs into a neural network algorithm (Fig. 1). Equations for insurance, risk, TSPs (Travelling Salesman problems), and more could be modelled in three layers (Fig 2).

- is not controlled by a central organisation or authority as it utilises a decentralised public computer network (i.e. the Bitcoin network); - is not a packet of data stored on a computer that is transferred to a new owner as payment. Rather payment involves a reallocation of Bitcoin balances / value in the public ledger [[14]](#_ftn14); and - is used solely as a means of payment by businesses and consumers for real world transactions.

- uses a .com domain; - accepts USD; - holds or trades against USD or USD equivalent (and such means USDT); or - has any network communications that pass a US server at any point in time.

Here is the thing: There is no other way that it can work in a small-world network. There is no other way that it can work in the Bitcoin node structure. Bitcoin is merely secure if the network distance for the miners, that is the nodes, remains at a level of D<3 or, in other words, the hop count is always under three hops. To achieve such an end, a number of large competing organisations will be created. I was incredibly specific in my point, and yet people seem not to understand me, and you wonder why I get so frustrated.

The simple end is that we don’t end up with an honest distributed system using any proof-of-stake model. More importantly, the consensus structure of the network does not evolve. In any model, proof of stake fails to form a consensus based on a small-world network, and the result of it is that it becomes simple to attack. I don’t expect you to take my word for it, but you have to wait till I publish; and very very simply put, I have no interest in saving the people going down such a trail.

In May 2016, I came to the conclusion that the best I could hope for in signing publicly and doing everything that would be needed would be the exact opposite of proof. I would start by signing; and then there would be other questions. The ones more greedy and undeserving individuals such as Ira Kleiman would come out expecting much more and saying that somehow I had stolen keys that I never had access to (it does not matter that it is not actually possible let alone feasible on Bitcoin). It would no longer be enough to try and blackmail me into making them instantly rich, but to see a long-term gravy train.

Hal Finney was an amazing man in many ways. Without him, Bitcoin would not exist today. Hal is a far better coder than I will ever hope to be. You see, I’m not a specialist. The initial versions of Bitcoin had a lot of problems. To put it simply, they fell over and crashed repeatedly.

It is going to be painful for someone to discover how simple it really is, and more importantly, it is absolutely critical for the scaling of the network. Other people’s loss.

If Alice and Bob deal directly, it is but one hop. Where Alice and Bob and Charlie interact, we have two hops. The existing Lightning Network expands to up to 10 or 11 hops — while it is a minimal small size. The fact of the matter is that there are four or five layers of intermediaries between people who are engaged in trade when using the Lightning Network. Yet, no interaction or payment is made in a manner that allows the recording of the transaction. As such, Lightning acts as a mixer network to confuse and obfuscate payments.

The solution to the problem is to commercialise everything. Doing so will actually benefit everyone. Right now, many thousands of adverts are sent back and forth mostly unread to earn mere cents. Your data is sold, and you have little control over your information.

It wasn’t actually the first problem, but it was the biggest. All of the machines weren’t running at block one. There were what I hoped to be enough. Bitcoin didn’t run on Linux at the time. I had Centos, Redhat, and Solaris machines on my network to handle DNS and sendmail, but Bitcoin ran on Windows.

Unfortunately, at least for them, this isn’t going to happen. It’s not going to happen now. It’s not going to happen in the decade. It’s not going to happen in the next 20 years. You see, I’m here to stay. What people fail to understand is that I do not write patents covering bitcoin. What (IP) we giveaway on BSV is protected by patents that equally apply to any other system… but are no longer close to being free. The distinction is that other systems will need to pay. By the end of this year I hope that we will have around 1,000 patents published. More importantly, the initial patent families should place us in advance of any other player in the industry. You see, we don’t publish straightaway. Others do, but we don’t because that would give away what we’re doing.

I foresee a large distributed database that is operated as an economically secure system. It will become a global ledger — not because individuals run it, as such isn’t the way Bitcoin was designed, but because individuals can operate a peer-to-peer network that is settled and secure without facing an economically significant risk of double spending.

PII stands for personally identifiable information. Right now, I see and hear many people talking about just how easy it would be to take and use PII. That it would sell for cents in the dollar.

Author’s note: We shall not be responsible for any errors, omissions, or claims for damages, including exemplary damages, arising out of use (or inability to use) or with regard to the accuracy or sufficiency of the information contained in the publication.