Basisis in the Business Intelligence Industry

Basis

basis

USA v. Samuel Bankman-Fried Court Filing, retrieved on March 15, 2024 is part of . You can jump to any part in this filing . This part is 30 of 33. HackerNoon’s Legal PDF Series here I. Applicable Law As the Court is well aware, “[c]riminal forfeiture statutes empower the Government to confiscate property derived from or used to facilitate criminal activity. Such statutes serve important governmental interests such as separating a criminal from his ill-gotten gains, returning property, in full, to those wrongfully deprived or defrauded of it, and lessen[ing] the economic power of criminal enterprises.” Honeycutt v. United States, 581 U.S. 443, 447 (2017) (citation and internal quotation marks omitted). Forfeiture is mandatory in cases involving fraud and money laundering. United States v. Torres, 703 F.3d 194, 204 (2d Cir. 2012); 28 U.S.C. § 2461(c) (“If the defendant is convicted of the offense giving rise to the forfeiture, the court shall order the forfeiture of the property as part of the sentence in the criminal case.”). Where forfeiture is sought in the form of a personal money judgment, the district court “must determine the amount of money that the defendant will be ordered to pay.” Fed. R. Crim. P. 32.2(b)(1)(A). The court’s determination “may be based on evidence already in the record,” Fed. R. Crim. P. 32.2(b)(1)(B), including evidence from trial. United States v. Capoccia, 503 F.3d 103, 109 (2d Cir. 2007). The “calculation of forfeiture amounts is not an exact science. ‘[T]he court need not establish the loss with precision but rather need only make a reasonable estimate of the loss, given the available information.’” United States v. Treacy, 639 F.3d 32, 48 (2d Cir. 2011) (quoting United States v. Uddin, 551 F.3d 176, 180 (2d Cir. 2009)). A court “may make reasonable extrapolations from the evidence established by a preponderance of the evidence at the sentencing proceeding.” Treacy, 639 F.3d at 48. As “an aspect of sentencing,” Libretti v. United States, 516 U.S. 29, 49 (1995), forfeiture amounts are determined by a preponderance of the evidence, Capoccia, 503 F.3d at 116. The purpose of forfeiture is “punitive rather than restitutive.” United States v. Roberts, 660 F.3d 149, 166 (2d Cir. 2011). Absent Eighth Amendment concerns, the defendant’s ability to pay a money judgment is irrelevant. United States v. Awad, 598 F.3d 76, 78-79 (2d Cir. 2010); United States v. Viloski, 814 F.3d 104, 114-15 (2d Cir. 2016) (upholding forfeiture money judgment exceeding $1 billion as consistent with defendant’s future ability to “earn[] a living upon his release from prison.”); United States v. Bonventre, 646 F. App’x 73, 92 (2d Cir. 2016) (upholding forfeiture money judgment exceeding $19 billion in Madoff Ponzi scheme). There are two bases for the underlying forfeiture here. First, under 18 U.S.C. § 981(a)(1)(C), any property “which constitutes or is derived from proceeds traceable” to wire fraud or securities fraud, among other offenses, is forfeitable. 18 U.S.C. § 981(a)(1)(C); see also 18 U.S.C. §§ 1956(c)(7), 1961(1); see also 28 U.S.C. § 2461(c) (allowing forfeiture for any crime “for which the civil or criminal forfeiture of property is authorized”). Whether the proceeds subject to forfeiture include all property obtained from the offense or whether the proceeds subject to forfeiture are limited to the net gain or profit depends on whether the conduct involves “illegal goods, illegal services, [and] unlawful activities.” See 18 U.S.C. § 981(a)(2). “[E]mbezzlement, soliciting funds as part of a Ponzi scheme,” among other types of conduct, are “inherently unlawful.” United States v. Milton, 21 Cr. 478 (ER), 2024 WL 779210, at *3 (S.D.N.Y. Feb. 26, 2024) (citations omitted). For such “inherently unlawful” acts, the term “proceeds” is defined as “property of any kind obtained directly or indirectly, as the result of the commission of the offense giving rise to forfeiture, and any property traceable thereto, and is not limited to the net gain or profit realized from the offense.” 18 U.S.C. § 981(a)(2)(A). In other words, “[p]roceeds” are “property that a person would not have but for the criminal offense.” United States v. Daugerdas, No. 09 Cr. 581 (WHP), 2012 WL 5835203, at *2 (S.D.N.Y. Nov. 7, 2012) (quoting United States v. Grant, No. 05 Cr. 1192 (NRB), 2008 WL 4376365, at *2 n.1 (S.D.N.Y. Sept. 25, 2008)). There is a second basis for forfeiture, which does not involve proof that the funds are “proceeds.” Under 18 U.S.C. § 982(a)(1), for a money laundering “offense in violation of section 1956,” a court “shall order that the person forfeit to the United States any property, real or personal, involved in such offense, or any property traceable to such property.” Besides seeking a personal money judgment, the Government can also seek forfeiture of specific property. The Court “must determine whether the government has established the requisite nexus between the property and the offense.” Fed. R. Crim. P. 32.2(b)(1)(A). The applicable law to determine if the requisite nexus is shown is the same as the underlying forfeiture law: here, 18 U.S.C. § 981(a)(1)(C) and 18 U.S.C. § 982(a)(1). See, e.g., Capoccia, 503 F.3d at 115. Once again, to determine whether specific property is forfeitable, the court may consider “evidence already in the record,” or “any additional evidence or information submitted by the parties and accepted by the court as relevant and reliable.” If forfeiture of specific property is contested, the court must conduct a hearing. Fed. R. Crim. P. 32.2(b)(1)(A). Continue Reading . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on March 15, 2024, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. storage.courtlistener

Exploring the Legal Basis for Criminal Forfeiture

This is an introductory article explaining the basic intuition, mathematical idea & scope of radial basis functions in the development of predictive machine learning models. Table of Contents Introduction Basic intuition of a Radial Basis Function Types of Radial Basis Function The concept of the RBF Network Scope & Advantages of RBF Conclusion References Introduction In machine learning, problem-solving based on hyperplane-based algorithms heavily depends upon the distribution of the data points in the space. However, it is a known fact that real-world data rarely follows theoretical assumptions. There are a lot of transformation functions that can convert the natural shape of the data points into theoretically recommended distributions persevering the hidden patterns of the data. Radial Basis is one such renowned function which is discussed in a lot of machine learning textbooks. In this article, we will learn about basic intuition, types and usage of the Radial basis function. The Basic Intuition of a Radial Basis Function The radial basis function is a mathematical function that takes a real-valued input and outputs a real-valued output based on the distance between the input value projected in space from an imaginary fixed point placed elsewhere. This function is popularly used in many machine learning and deep learning algorithms such as Support Vector Machines, Artificial Neural Networks, etc. Let us understand the concept and the usage of this mathematical function. In real-time, whenever we solve complex machine learning problems using algorithms such as SVM, we need to project all of our data points in an imaginary multidimensional space where each feature will be a dimension. Let's assume we have a classification problem to predict whether a student will pass or fail the examination. We have the following features as independent variables: Marks in internal exams Marks in projects Attendance percentage So, these 3 independent variables become 3 dimensions of a space like this- Let’s consider that our data points look like this where- The green colour represents the students who passed the examination The red colour represents the students who failed the examination Now, SVM will create a hyperplane that travels through these 3 dimensions in order to differentiate the failed and passed students- So, technically now the model understands that every data points which falls on one side of the hyperplane belong to the students who passed the exams and vice versa. In our example, it was easy to create the hyperplane because a linear and straight hyperplane was enough to discriminate the 2 categories. But in real-time complex projects, these relations may get violated in many scenarios. Especially when you have hundreds of independent variables, there is no possibility of getting a linear relationship between data points such that it will be difficult to create an optimal hyperplane. In such scenarios, researchers usually apply the Radial basis function to each of the data points so that they will be able to pass a linear hyperplane across the data points to easily solve the problem. Consider that our data points are looking like this in the space- It is clear that we cannot use a linear hyperplane such that it can group the data points according to their classes. RBF will help us in these kinds of scenarios. Some researchers will usually project these data points in much higher dimensions so that the distance between the data points will be increasing so that they can apply some function (RBF or any other function) to build a hyperplane. But it is not necessary to build high dimensions since it is always the decision of the statistician/researcher who understands the patterns in the data. Next, we have to mark an imaginary point in the space like this wherever we need. After that, we need to draw some concentric circles based on this imaginary point. The distance between the centre and any data point positioned in the boundary of the circle is called the radius. After calculating the radius, we need to pass this value inside a mathematical function (RBF) that will return a real value. The returned value will be the transformed magnitude of a particular data point used for further proceedings. Types of Radial Basis Functions There are multiple types of radial basis functions. Each of them will transform the input value in a different way. Some of them are- Radial Basis Function Multiquadratic Where, r is the radius ε is a constant The function will look like this with respect to time, Radial Basis Function Inverse Multiquadric Where, r is the radius ε is a constant Radial Basis Function Gaussian Where, r is the radius ε is a constant I will explain intuitively what these functions will do intuitively in the space. There are 2 different processes that are done by these functions- Expanding the data points across the horizontal direction Compressing the data points across the vertical direction The process of expansion will visually somewhat look like this- The process of compression will visually somewhat look like this- After the expansion and compression, the data points would have been transformed like this- Now, we can easily construct a linear hyperplane that can classify the data points like this- The Concept of the RBF Network Sometimes, RBF is also used along with artificial neural networks with one hidden layer. In such types of networks, RBF will be used as activation functions in the hidden layers. Apart from the hidden layer, there will be an input layer that contains several neurons where each one of them represents a feature variable and the output layer will be having a weighted sum of outputs from the hidden layer to form the network outputs. Such networks are called RBF networks. Scope & Advantages of RBF With the help of the RBF function, it is possible to solve the problems in datasets that have complex non-linear distributions. RBF function has a strong tolerance to input noise In RBF neural network, there will be only one hidden layer which is very easy to handle. Hidden patterns in the distribution can be generalized better after applying the RBF function. In RBF neural network,  we can easily interpret what is the meaning/function of each node in the hidden layer of the RBNN. This is difficult in Multi-layer perception. Some of the hyperparameters present in Multi-layer perceptron such as the number of nodes in the hidden layer, number of hidden layers etc. are difficult to optimise. But these are not found in RBF neural networks. Conclusion In this article, we discussed one of the most useful transformation functions in machine learning. I have tried to explain this complicated concept without many in-depth mathematical calculations in a lucid manner targeting beginners in the AIML learning space. This function is available as an inbuilt library in most data science-oriented programming languages such as Python or R. Hence, it is easy to implement this once you understand the theoretical intuition. I have added the links to some of the advanced materials in the references section where you can deep dive into the complex calculations if you are interested. References Radial Basis Functions - Wikipedia 2014-04-23 at the Radial Basis Function networks Archived Wayback Machine Broomhead, David H.; Lowe, David (1988). (PDF). . : 321–355. Archived from (PDF) on 2014-07-14. "Multivariable Functional Interpolation and Adaptive Networks" Complex Systems 2 the original (1977). "Restart procedures for the conjugate gradient method". . (1): 241–254. : . . Michael J. D. Powell Mathematical Programming 12 doi 10.1007/bf01593790 S2CID 9500591 Sahin, Ferat (1997). (M.Sc.). . p. 26. : . Radial basis functions were first introduced by Powell to solve the real multivariate interpolation problem. A Radial Basis Function Approach to a Color Image Classification Problem in a Real-Time Industrial Application Virginia Tech hdl 10919/36847

Radial Basis Functions: Types, Advantages, and Use Cases

Funciones de base radial: tipos, ventajas y casos de uso

Fonctions de base radiales : types, avantages et cas d'utilisation

रेडियल बेसिस फ़ंक्शंस: प्रकार, लाभ और उपयोग के मामले

放射基底関数: タイプ、利点、および使用例

Funções de base radial: tipos, vantagens e casos de uso

Các chức năng cơ sở xuyên tâm: Loại, Ưu điểm và Trường hợp sử dụng

径向基函数：类型、优点和用例

What is Happening? The DeFi version of tokenized stocks which reflect AMZN stock on the crypto market, has long been influenced by the stock market, but Amazon’s move of the stock directly affects these DeFi tokenized stocks. Each existing share of AMZN stock is divided into 20 separate units as part of the 20 for one stock split which became effective on June 6. This provides new investors with additional investment options because, before the split, most small buyers couldn’t afford to buy Amazon stock. splitting The dAMZN, the tokenized version of the DeFi stock, split similarly to the AMZN stock mirroring its market movement and change in fundamentals. The dAMZN tokens are minted and traded on DeFiChain, which tracks the price of Amazon shares but does not have ownership of the underlying stocks. With the use of oracle feeds and other DeFiChain features, the dAMZN attempts to imitate the price movements of real-world stocks by mirroring the market movement through the feeding of live data. Due to this, buyers will have the identical amount of dAMZN they had before the split since DeFiChain will refresh the price from the oracles based on the input received ~ talk about the future of finance! What is DeFi Chain? DeFiChain is a decentralized blockchain-based platform dedicated to enabling decentralized financial services that are efficient, efficient, and transparent by building technologically, providing unparalleled high transaction throughput and reduced risk of errors.  The ultimate purpose of this project is to provide the infrastructure based on the Bitcoin network with complete DeFi capabilities with a focus on scaling. Every few blocks, the network anchors to the Bitcoin blockchain (through Merkle root) and uses a hybrid Proof of Stake/Proof of Work consensus process. to Messari, there are reduced smart contract flaws on DeFiChain since it is non-Turing complete, allowing transactions to move swiftly at minimal gas costs and reducing the chance of smart contract failures. According Why are Tokenized Stocks Important for the Future of Finance? Tokenized stocks or equities are the same as a share of equity in a publicly listed corporation, like equities on the Nasdaq or S&P 500, depending upon their underlying legal structure. Tokenized stocks are represented by digital tokens that reflect or mirror the price movement of the traditional stock in the market. Investors normally get their shares in their account through a brokerage after purchasing a standard stock on an exchange or in an initial public offering (IPO). It’s the same approach for tokenized stocks, where the tokenized stocks can be exchanged on a cryptocurrency market as they are issued and traded on the blockchain. The process of generating a tokenized stock generally involves a custodian and an investment or brokerage institution. The custodian receives the underlying stock, which the institution purchases and deposits. Tokens are created on a blockchain, based on the custodian’s reserves based on the amount of the shares held by the custodian. Tokenized stocks can then be listed on a cryptocurrency exchange, where they can be purchased and sold just like any other kind of cryptocurrency. It is almost like owning the underlying stock, with dividends being paid out in some cases depending upon the type of tokenized stocks. Tokenized stocks are revolutionary in nature as the token transactions can be settled in a couple of minutes, whereas the settlement of regular stock is based on T+2 settlement. Further, tokenized stocks provide exposure to US financial markets to crypto and international investors who may not have any exposure to US securities due to regulations or jurisdictional constraints. Understanding Why Crypto Investors Should Care About DeFi-based Tokenized Stocks One of the reasons why dAMZN and other DeFiChain-based tokenized stocks are seeing adoption is because the typical investing method does not provide exposure to the stock market to crypto investors if the investor does not liquidate their position to buy that particular stock. Further, tokenized stocks have lesser compliance hassle in contrast to traditional securities, with a long processing time and compliances, making the process slow and cumbersome. Furthermore, many investors cannot invest in their favourite US equities due to regional limitations, trading restraints and local regulations. These traders and investors now have global price exposure to these assets via DeFiChain’s dTokens (tokenized stocks). For example, the tokenized stock of Twitter, the social media firm, a mirror of TWTR, over the previous three months, the token’s price has fluctuated between $41.23 and $67.77, in line with the market trends in the traditional financial markets giving exposure to crypto investors on the Elon musk bid to buy Twitter. Final Thoughts on Splitting of Tokenized Amazon Stock Tokenized stocks are novel instruments which, in my opinion, serve a larger purpose of providing exposure to US-based stocks to international investors because, in various jurisdictions, it is difficult to buy and hold US-based technology stocks directly. Gaining exposure to US tech companies via tokenized stocks is an excellent tool for investors who can invest and trade such instruments without liquidating their crypto assets portfolio to fiat. Don’t forget to like and share the story! Image credits: , , and ANIRUDH. Christian Wiediger Meriç Dağlı Aditya Vyas

Tokenized Stock Representing Amazon on DeFiChain Splits on a 20-for-1 Basis 

The pursuit of calculating cost basis for cryptocurrency is one that has been hindered by obstacles from three separate external factors; a gap in guidance for crypto regulation; a lack of legally approved best practices for crypto accounting and taxation; and smart technology to automate and increase accuracy and remove human error out of cost basis results. To help the crypto community, tax professionals and to keep the world informed on how to calculate cryptocurrency cost basis, here are the most important questions and answers that crypto owners must know. What is the difference between traditional and crypto cost basis? Cost basis is a traditional accounting term that refers to the purchase price + fees + other associated purchase costs. The core of “basis” is the same for cryptocurrency cost as it is for traditional cost basis for calculating gains & losses. Essentially, anyone and everyone that makes a profit is expected to pay annual taxes on capital gains. Traditionally, when calculating gains and losses, professionals will rely on general ledger software such as Quickbooks, accompanied by spreadsheets, calculators and lots of manual data entry and calculations. Additionally, traditional cost basis has clear regulations for tax obligations and compliance, while also having a more understandable financial ecosystem. This makes calculations more simple and predictable to calculate. To describe crypto cost basis more easily, if Jack purchased a Bitcoin in 2015 for , the basis on that Bitcoin is . If Jack sold his Bitcoin one-year later for , he would owe taxes based on his gains of . (Fees & other difficult factors are removed for this example) $400 $400 $2000 $1600 Jack’s Original Purchase 2015:	$400 Jack’s Basis with Fees 2016: 	        $400 Jack’s Sale Price of Bitcoin:	        $2000 Jack’s Taxable Gains:		        $1600 For calculating cryptocurrency cost basis, the process becomes far more complex. There are thousands of different types of cryptocurrencies that operate in different ways. Crypto also contains far more variables such as gas fees for fueling transactions within a crypto network, exchange or transfer fees, mining profits, soft and hard forks, airdrops and dozens of intricate taxable nuances. It's simple to see that crypto can be far more perplexing. Why is cost basis important to me? Cost basis is used to calculate a company or investors total gains or losses on an annual basis, usually for auditing or tax purposes. In the U.S, the government requests and requires all holders of cryptocurrencies to disclose their entire financial portfolio and have it reported annually for capital gain taxes. For the IRS to properly audit and assess an investor or businesses financials, they will require a complete overview of asset and transaction history to understand how much or how little a company or individual earned in crypto annually, By effectively and accurately reporting cryptocurrency holdings, gains or losses, in adherence to the tax obligations issued by the IRS, cryptocurrency investors that report their earnings not only remain legally safe, but can also see exemptions and other possible benefits of reporting promptly and properly. What happens if I don’t calculate or report my crypto cost basis? While the regulation and legal framework are still being built, the consequences of neglecting to disclose a complete history of a digital asset portfolio can be punished by the federal tax arm of the government, the Internal Revenue Service. It is essential for cryptocurrency owners, investors, businesses and any operations that transacts with crypto to report and pay their annual taxation requirements. New tax forms now officially include sections to disclose your cryptocurrency earnings for the year. While the issue of disclosing personal crypto portfolio information has been disputed by many in the crypto community, this is an official law approved by the American federal government, making it unequivocally legal and enforceable. There is destined to be edge cases where no legal framework exists, such as if an exchange is defunct and investors lost access to their transaction history. Every case is different, but reporting honestly and proactively, as well as staying informed is the best way to stay on the right side of the law. How do I calculate my crypto cost basis? Calculating cost basis for crypto is exceptionally difficult due to the secure nature and wild web of complex transactions and taxable financial events. is by noting down all wallets, exchanges, accounts and portfolios to ensure investors have the full picture of their crypto portfolio. The best place to start Investors and businesses alike may rely on third party accounting services to help calculate crypto cost basis, while small investors will look for software and more feasible solutions. It is not recommended to manually calculate cost basis due to the extreme complexities of transaction activity and the behavior of the ecosystem. Moreover, calculating gains and losses on 100 transactions manually can take hundreds of hours, pouring over spreadsheets, documents and hoping for an accurate result. Unless your are a well-trained finance professionals, leveraging technology, or accounting firms is usually the safest best for investors and businesses. Are there tools to help me calculate my crypto gains and losses? For investors and businesses of any size, there are of calculating cryptocurrency gains and losses easily. Blox, a leading platform for crypto accounting, tax and asset management has developed the industry’s first automated and accurate technological solutions capable cryptocurrency cost basis tool. Other software of startups such as TokenTax exist with the goal of helping crypto businesses and investors with the day-to-day and back office software solutions for managing their crypto or calculating gains and losses. Tech and software can work together to help keep investors and professionals more organized and connected to their crypto with full control and management of assets. It is always important to investigate the right platform for each business and individuals, and leveraging technology on a day-to-day basis. This will ultimately help to keep track, organize and prepare for tax season, auditing, financial accounting and other tax obligations. What is next for cost basis? The dominance of bitcoin, despite its epic price fluctuations, has made it more important than ever, to begin calculating gains and losses for investors, businesses and institutions. In the eyes of the IRS, anyone and everyone is entitled and liable to pay taxes on crypto earnings. The evolving landscape of crypto taxation is slowly changing everyday, and creating new rules and regulations for how to calculate gains and losses and navigate the financial world of cryptocurrencies. For businesses, they may already have an internal finance team, or hire external accounting firms to handle bookkeeping and taxation. But for small individual investors, they must rely on more localized and cost effective means for calculating cost basis. Regardless, businesses and investors of all shapes, sizes and networth are all governed by the same tax laws. ( : ) Disclaimer The Author is a co-Founder at Blox.io

Questions On Crypto Cost Basis That You Need to Ask

First and foremost I want to say that we have a ton of respect for the Basis team. We’ve always viewed them as one of the more intellectually impressive and credentialed teams in the stablecoin space and they have done more than most other groups to drive the conversation forward and advance the crypto industry as a whole. All this being said, while we understand that Basis felt that outside regulatory agencies made their plan untenable and less promising to investors than they originally intended, we feel that there are lessons to be learned and we are certainly trying hard to absorb them. We also understand how they might have came to the conclusion that they needed to fold up shop, but we disagree that the SEC’s guidance was somehow a “surprise”. As a company we have made many contrarian choices. One of the most difficult choices was to not pursue a token sale last spring. (We have actually spent a fair amount of time trying to figure out how Basis was navigating securities laws). While we are committed to eventually going algorithmic if the market will eventually support that, we weren’t comfortable with how vulnerable any non fiat-collateralized system at this point in time or their ability to effectively compete for liquidity. On a very high level for Basis’s system to remain robust, Baseshares needs to trade at a very healthy price. The system’s ability to survive drops in demands correlates to the liquidity of the bond market. The bonds would never be traded at a premium over shares as shares have no upside cap (there is a scenario in which the payout order on the bonds could command a premium but this would only happen when the system was exposed to existential risk). The pricing of Baseshares depends entirely on aggregated expected demand for the stablecoin discounted based on both system confidence and capital lock up costs. Consequentially the systems robustness was tied directly to the pricing of Baseshares. The the lower the price, the higher the probability of total collapse. Having close a billion dollar valuation likely would have lead to a substantial sell off on launch which would have further reduced partner and investor confidence. Most investors are chosen based off their ability to support projects and poor performance on launch would significantly reduce supporters willingness to help drive adoption. Like most networks, the challenge is getting it to scale. Being dubbed a security, having credible competitors, and the market contraction substantially increase the risk of the system failing to achieve enough scale to become robust. Basis failed at least in part because of their inability to effectively navigate evolving market conditions. We laud the humility demonstrated by the Basis team through their decision to return investor funds. We strongly encourage other projects in the space that raised with tokens to assess the viability of their respective visions, and, if it makes sense, follow in Basis’s footsteps. We fully expect the SEC to continue to pursue groups that sold unregistered securities and believe good faith actions on the behalf of projects is the best way to navigate this risk.

Our thoughts on the Demise of Basis

Reserve’s Analysis of the Basis Protocol

Looking to Provide the Stability Crypto Needs You may not have heard of the year-old startup known as . But the company based out of Hoboken, New Jersey has roared out of the ICO gates and raised over $133 million in the past year to go toward creating a new stablecoin for the masses. The token (formerly known as Basecoin) is a that is programmed to maintain its value closely to the value of one US dollar at all times. Basis works to solve this problem. We at the investing platform, , recently spoke with them to better understand their intended and expected purpose for the future of cryptocurrency. The Basis team explains, Basis cryptocurrency stablecoin In cryptocurrency, it is not always a practical or available option to simply trade Bitcoin for dollars and vice versa. Level “Cryptocurrencies have been too volatile for mainstream use. Loans, salaries, and other basic financial contracts are poorly served by volatile currency.” The soon to be public non-collateralized stable token, founded by , utilizes an algorithmic bank embedded in its code. This algorithm sets out to: Nader Al-Naji Buy back Basis tokens when demand falls in order to shrink its supply Sell off Basis tokens when demand rises in order to inflate its supply By doing both of the above, the algorithm can optimally maintain that one Basis token is equal to one US dollar at all times. Although Basis will peg itself to the US dollar, it has plans to peg to a consumer price index once mass adoption is achieved and it is (hopefully) being regularly used to make real life purchases of goods and services. In a discussion with Josh Chen, a co-founder at Basis, he stated, “Basis is designed to offer a fully-decentralized, counterparty-free system to users, independent from any centralized source of value in the long term. has shown that users find real value in the safety of a decentralized cryptocurrency. We think users will find similar value in Basis, but with added stability regulated by its algorithmic central bank.” Bitcoin Founder Nader Al-Naji, a former Bitcoin miner during the early years of cryptocurrency in 2012, has received tremendous backing for his revolutionary idea to create a coin that algorithmically adjusts its own supply as needed. The coin is intriguing not only for its uniqueness among other stablecoins, but also for its designed purpose of being a consistent force in such a volatile market. To give an idea of the excitement surrounding Basis, a large chunk of their money raised came from the likes of GV (previously known as Google Ventures), Bain Capital Ventures, fed reserve governor Kevin Warsh, and Lightspeed Venture Partners. Investors know there is a major market opportunity for a coin like Basis, which offers a stable store of value in an otherwise heavily turbulent field. According to the , Basis website “Basis is designed to maintain a stable value and serve as a medium of exchange accessible to anyone with an internet connection.” Theoretically, this means that the only thing separating it from that green paper money sitting in your wallet is having an active connection to the world wide web. If the coin actually establishes itself as a relied upon currency that can be used without significant fluctuations from its intended value, then this will be a big deal for the future and mainstream usage of cryptocurrency as a whole. With one Basis coin equalling one US dollar, it has the potential to be used as an alternative to purchase goods and services. Trust Issues The designed purpose of Basis (pegging its value to the dollar) is the same as other already existing popular stablecoins like Tether (USDT) and True USD (TUSD). These coins have been circulating through exchanges as relatively easy ways to convert one’s Bitcoin or other altcoin holdings into something stable while circumventing FIAT central banks. However, there has been a lack of proof in fund backing for USDT, as well as slightly wavering values that stray away from the dollar in both coins’ histories. As a result, exchanges have seen many traders avoid these coins as options to stabilize their portfolios. There has instead been an increased demand for regular USD trading pair options on popular trading sites. But is this really what is best for the future of cryptocurrency? Cryptocurrency may eventually rest on the viability of stablecoins like Basis. This lack of trust in the relatively new existence of stablecoins is precisely what is holding back cryptocurrency from separating itself from the Federal Reserve and central banks as a viable alternative to traditional currency. The struggles and controversies other stablecoins like Tether (USDT) have experienced in trying to make a name for themselves have if they can accomplish what they hope to do. And if Basis does succeed, it will be a concern for the Federal Reserve’s monetary policy. opened up the door for Basis to become the first reliable dollar-pegged coin Andrea O’Sullivan, an analyst at CoinCenter, points out that there is: “fear that if cryptocurrencies are adopted on a wide enough scale, it could have a negative externality, or spillover effect, on the economy as a whole in the form of monetary instability.” goes on to explain that $100 billion of Bitcoin’s market cap only accounts for 1.3% of the world’s actual hard Fiat currency. Therefore, it is fairly unlikely that Bitcoin or another cryptocurrency coin actually makes a dent in the US dollar, Euro, or another major currency any time soon. However, 1.3% is not nothing. And as more people eventually adopt crypto as a means for making legitimate transactions, there will come a time where the Fed will need to actually take Bitcoin and others seriously. Stablecoins such as Basis could be the ones to eventually stir the pot, as their coinciding values with the dollar will give it appeal as a direct alternative. Her article Threat to the Fed It will be very intriguing to see how Basis will coincide and interact with the Federal Reserve’s monetary policy. The Fed currently manages its monetary policy based on the economy’s need to achieve stable prices in the dollar. They can contract their policies when unemployment is too low, and they can conversely expand monetary policy when interest rates are high and economic growth is needed. However, they often These decisions are made and announced on a quarterly basis through press conferences that do not always include all details in how they came to their conclusions. lack transparency in their decision making and there is significant lag time in their decision making. Basis and other stablecoins, on the other hand, adjust to its demand virtually immediately. And with the assumption that they will live up to the transparency they promise, it may ultimately force the Fed to be much more accountable and transparent with their actions. A truly decentralized stable currency will either: Be taken as a legitimate threat by the Fed. They can address their own monetary policies to become more honest, proactive, and fair in dealing with public and economic needs. Be ignored and scoffed at as a non-serious threat. The Fed can shrug their shoulders at the presence of the decentralized alternatives that are offered to users. This may backfire if stablecoins like Basis enjoy mass adoption and become a more intriguing and trustworthy option for Americans. Randal Quarles, who is a vice chair for the Federal Reserve, made national headlines when he addressed the threat that digital assets were posing to the Fed in the midst of the crypto boom on November 30, 2017. During , he went over the threat of cryptocurrency overall to their reserve banking system. He stated, his speech “While these digital currencies may not pose major concerns at their current levels of use, more serious financial stability issues may result if they achieve wide-scale usage.” Quarles and the Fed understand that under the currently stable economic conditions the US is in, there is not a great deal of fear that people will abandon the dollar. However, the Fed also understands that if the economy begins to slip into another recession or crisis situation, Once people find an alternate space they can trust to store their funds, it may self-perpetuate the dollar’s demise. the existence of an attractive space like cryptocurrency (and particularly stablecoins) will make it that much harder for the dollar and economic state to recover. Many suggestions have been tossed around regarding how the Fed may be able to address the threat of cryptocurrency diluting the need for mainstream currency. One suggestion is for the Fed to actually develop its own cryptocurrency, theoretically known as a “FedCoin”. Kevin Warsh, a former U.S. Fed Reserve governor, believes there could be merit to conduct monetary policy after the next U.S. crash. Their own cryptocurrency would hypothetically allow them to hedge themselves in case of crisis, and with the assumption that a growing number of the population continues adopting cryptocurrencies. However, this has not seemed to garner much serious consideration with others currently within the Fed. to the notion of the hypothetical Federal Reserve run cryptoasset idea by stating, Quarles responded “I am particularly concerned that a central-bank-issued digital currency that’s held widely around the globe could be the subject of serious cyberattacks and could be widely used in money laundering and terrorist financing,” This would certainly be a real concern, as the creation of this coin, which would be intended as a safety precaution for crisis, could have real potential of causing more harm for the Fed than good. There is a risk of the Fed’s version of a crypto token being completely counterintuitive to what they are trying to accomplish, thus there is not a strong push for it currently. Creating a “FedCoin” does open up the risk of their currency being used for immoral purposes. So how does the threat of cryptocurrency to the Fed relate specifically to Basis? Well, a coin that can function off of its own centralized bank can efficiently do everything that the Fed can with its flawed, often criticized monetary policies. And if Basis can improve upon this and allow for more precise levers to dictate the purchasing power the US and other countries have, and doing so through the inclusion of their own real-time central bank that is sustainable, there will be less and less need for the Fed and central banks to dominate the decisions pertaining to when our economy is supposed to “heat up” and “cool down”. Probably the most obvious reason that Bitcoin is not currently taken seriously as a threat to the Fed’s monetary policies is because it is just far too volatile. But a coin that intends to be the same value as the Fed’s dollar and has its own policies? That can and should be taken a bit more seriously. Shifting Away From Traditional Currency Al-Naji and the Basis team believe they can actually replace fiat currency for every day purchases of goods and services. He has recently stated, “I think the fact that the value is stable and not expected to appreciate really solves almost a perverse incentive with spending it that makes it much more useful as a medium of exchange.” Indeed, the large swings in Bitcoin and other tokens often dissuade users from utilizing them as actual currencies for making transactions. Basis can solve this problem and become a pioneer for mainstream crypto adoption as a regular mean of exchange for goods and services for the first time. If this is accomplished, it would be a savior for many coins that have great, real world use cases, yet are struggling due to the lack of mass adoption they covet. The team behind the token truly believe a coin can be created to emulate and accomplish the same goals as the Federal Reserve. According to their , Basis blog “Central banks apply monetary policy to mitigate currency volatility. Until now, there’s been no way to create a cryptocurrency with comparable benefits. And no way for cryptocurrencies to become true currencies.” With a coin that does not have the looming threat of major volatility that Bitcoin and others coins have, or the delayed, often inaccurate monetary needed adjustments that are implemented by the Fed a handful of times a year at most, we may have a currency that meets the standard of what we hope a currency can be. Even if it does not become a household name or a commonly used coin for real-world transactions, Basis can at least accomplish the task of raising the bar for the Fed and forcing them to improve upon the policies they currently have in place. When even a small percentage of people are aware of better alternatives like Basis and other stablecoins, central banks will wake up and rise to the occasion with the threat of having their monopolization on monetary policy usurped from them. I write in depth cryptocurrency analysis at Level , the passive investing tool for crypto. See what we’re doing at Lvl.co and see our other analysis at our magazine . If you love what you see, give this article 50 claps! If you hate it, show your displeasure with 49. This article and related content is for informational purposes only. It should not be considered investment advice, and you should consult a financial advisor and do your own research and due diligence prior to making any investments. Where securities or commodities are referenced, it is only for illustrative purposes only, and does not imply any position on securities or commodities classification. To the extent that Level services are offered or discussed, those services are available only for Level whitelisted assets only.

Cryptocurrency’s New Stablecoin On the Block — Basis

Introduction: Ever since the buzz about GenAI and ChatGPT, I have been trying to understand the space and leveraging it into my day-to-day activities as a Data Engineer. No doubt it has been useful for debugging with respective programming and documentation. Personally, it played a significant role in helping me plan my Dubai itinerary. It even contributed to naming my friend’s daughter. However, it works pretty well if you give appropriate and precise requirements. There is a lot of anxiety among people that AI is going to take our jobs as they feel almost everything will be automated through AI. Is LLM as good as everyone claims? In this article, we will look into the specifics of Gen AI’s role in data engineering and see where it flourishes, where it requires enhancement, and where human expertise remains irreplaceable. Areas of Strength: Basic Data Querying: 100% the human necessity is going to get disrupted, but the severity based on the complexity is high. Even the SQL practitioners won’t feel much difference here, and self-serve analytics will catch fire in this area which is something phenomenal! Again, to quote positively, data engineers won’t need to guide the stakeholders nearly as much! Troubleshooting Pipeline Failures: LLMs coupled with agents will slash on-call load massively. LLMs processing stack traces/quality failures can recommend the built-in remedies and nudge the ball down the field to address the problem, presumably even over Slack. And that is a fantastic percentage of data engineering hours saved! To be clear, some hard failures require manual troubleshooting. Anomaly Detection: Regardless of the structure, format, source, complexity, timeliness, or even natural play of data, large language models can identify anomalies. LLMs are well-suited to anomaly identification because they can work across a variety of data sources, identify subtle patterns, and distinguish when data isn’t behaving as expected. This will help data engineers to identify and fix data quality problems in advance. Areas for Enhancement: Data Cleansing: Our results suggest that Language Models (LLMs) are highly effective in data cleansing due to their high performance in unstructured data management and semantic error identification and correction, as well as high scalability. Furthermore, our review of the current state-of-the-art suggests that even more substantial improvements are possible, including fine-tuning of LLMs to specific domains or even organization data. In addition, various interactive mechanisms as well as coupling with data quality frameworks can significantly increase the efficiency of LLMs. Overall, LLMs allow for organizing and improving the whole process of data cleansing, helping to obtain high-quality datasets, and, consequently, valuable insights. Visualization and Report Generation: Language Models (LLMs) excel in visualization and documentation tasks by automating the creation of reports, summarizing data insights, and generating narrative-driven reports. Enhancements needed include improving document organization and categorization, data-driven storytelling capabilities integrating with version control systems and visualization tools for seamless output generation, and enhancing interpretability features to ensure clarity and coherence in reports. Writing Pipeline Code in SQL, Spark, or Flink LLM can be a helpful starting point, and for our work, it is a good boilerplate. Still, the generated material is hard to debug — or often not, worth the trouble. Prompt-driven content is still far from being able to turn out a nice, optimized, and absolutely accurate data pipeline. Optimization By providing suggestions on efficient query structures and detecting problems that slow performance, LLMs are especially powerful when it comes to SQL optimization. They can even make recommendations for optimizations on the basis of historical query data. Things for improvement include integrating database-specific optimization techniques into the training of LLM, bridging with query execution plans in order to give context-oriented advice and feedback mechanisms so that one can modify strategies for optimization according to what users prefer as well as performance metrics. Physical Data Model As soon as the logical model is finalized, LLM will be efficient in moving and upgrading this logical (or conceptual) data model into the targeted architecture. The problem that LLM encounters with all the examples is that it’s hard for most people to understand the pipeline, table, and its relationship. Areas Where Human Expertise Remains Irreplaceable: Logical Data Model Data modeling is a very soft skills-focused task. You have to communicate with different stakeholders to understand the business context in detail. Understanding what data is needed, the relationship between entities, and considering different scenarios are human-oriented tasks that LLMs must continue to struggle with. Building Pipeline and Framework Once they reach a certain level of complexity, LLMs begin to give up. Imagine if someone asked ChatGPT, “Can you provide me the source code of Android’s next version?” While LLMs can help with routine data engineering tasks, they do not have the insight or inventiveness unique to humans that allows for new solutions to complex challenges, unlocking creativity in technical terms. Domain Expertise and Intuition: Human data engineers bring a unique blend of domain expertise and intuition to their work that often surpasses what conventional software isn’t able to achieve through automation. This intuition allows them to find subtle patterns in data that no fully rigorous automated system can. Based on their knowledge of this field and their experiences in it, they can predict future trends. They can also make decisions in light of a broader context, including corporate or government needs, ethical considerations, and potential future scenarios. This holistic approach to data engineering surpasses what LLMs have achieved. Although LLMs have great power, they are typically restricted to the patterns and relationships they have been trained to recognize. Conclusion: On the whole, Gen AI can certainly automate trivial procedures such as looking for information, launching programs that don’t work properly, repeatedly correcting faults, and anomaly detection. My gut tells me that Gen AI will win out and excel at tasks such as Data Cleansing, Optimization, and Writing Pipelines — once the team understands gaps and missing patterns. But it can not learn purely human soft skills that are important for building logical data models or a framework. I believe that these skills, which cannot be automated, are also essential for stakeholders to ask for innovation in the first place. After all, no one ever asked Steve Jobs if they needed anything like an iPhone; he just thought up what would become its invention. References: https://barrmoses.medium.com/will-genai-replace-data-engineers-no-and-heres-why-708b0a27da6b ​​__https://www.linkedin.com/pulse/navigating-data-governance-challenges-era-large-fnq5e__ https://www.dataversity.net/navigating-the-risks-of-llm-ai-tools-for-data-governance/ https://www.skyflow.com/post/why-ai-governance-requires-data-governance https://coreykeyser.medium.com/you-cant-govern-ai-without-governing-data-27bb88d8f9ea https://www.ankursnewsletter.com/p/gpt-4-gpt-3-and-gpt-35-turbo-a-review https://towardsdatascience.com/from-chaos-to-clarity-streamlining-data-cleansing-using-large-language-models-a539fa0b2d90 https://medium.com/@wangshally11/data-cleaning-warm-up-before-training-large-language-models-74ed1edceead Introduction: Ever since the buzz about GenAI and ChatGPT, I have been trying to understand the space and leveraging it into my day-to-day activities as a Data Engineer. No doubt it has been useful for debugging with respective programming and documentation. Personally, it played a significant role in helping me plan my Dubai itinerary. It even contributed to naming my friend’s daughter. However, it works pretty well if you give appropriate and precise requirements. There is a lot of anxiety among people that AI is going to take our jobs as they feel almost everything will be automated through AI. Is LLM as good as everyone claims? In this article, we will look into the specifics of Gen AI’s role in data engineering and see where it flourishes, where it requires enhancement, and where human expertise remains irreplaceable. Areas of Strength: Basic Data Querying: 100% the human necessity is going to get disrupted, but the severity based on the complexity is high. Even the SQL practitioners won’t feel much difference here, and self-serve analytics will catch fire in this area which is something phenomenal! Again, to quote positively, data engineers won’t need to guide the stakeholders nearly as much! Troubleshooting Pipeline Failures: LLMs coupled with agents will slash on-call load massively. LLMs processing stack traces/quality failures can recommend the built-in remedies and nudge the ball down the field to address the problem, presumably even over Slack. And that is a fantastic percentage of data engineering hours saved! To be clear, some hard failures require manual troubleshooting. Anomaly Detection: Regardless of the structure, format, source, complexity, timeliness, or even natural play of data, large language models can identify anomalies. LLMs are well-suited to anomaly identification because they can work across a variety of data sources, identify subtle patterns, and distinguish when data isn’t behaving as expected. This will help data engineers to identify and fix data quality problems in advance. Areas for Enhancement: Data Cleansing: Our results suggest that Language Models (LLMs) are highly effective in data cleansing due to their high performance in unstructured data management and semantic error identification and correction, as well as high scalability. Furthermore, our review of the current state-of-the-art suggests that even more substantial improvements are possible, including fine-tuning of LLMs to specific domains or even organization data. In addition, various interactive mechanisms as well as coupling with data quality frameworks can significantly increase the efficiency of LLMs. Overall, LLMs allow for organizing and improving the whole process of data cleansing, helping to obtain high-quality datasets, and, consequently, valuable insights. Visualization and Report Generation: Language Models (LLMs) excel in visualization and documentation tasks by automating the creation of reports, summarizing data insights, and generating narrative-driven reports. Enhancements needed include improving document organization and categorization, data-driven storytelling capabilities integrating with version control systems and visualization tools for seamless output generation, and enhancing interpretability features to ensure clarity and coherence in reports. Writing Pipeline Code in SQL, Spark, or Flink LLM can be a helpful starting point, and for our work, it is a good boilerplate. Still, the generated material is hard to debug — or often not, worth the trouble. Prompt-driven content is still far from being able to turn out a nice, optimized, and absolutely accurate data pipeline. Optimization By providing suggestions on efficient query structures and detecting problems that slow performance, LLMs are especially powerful when it comes to SQL optimization. They can even make recommendations for optimizations on the basis of historical query data. Things for improvement include integrating database-specific optimization techniques into the training of LLM, bridging with query execution plans in order to give context-oriented advice and feedback mechanisms so that one can modify strategies for optimization according to what users prefer as well as performance metrics. Physical Data Model As soon as the logical model is finalized, LLM will be efficient in moving and upgrading this logical (or conceptual) data model into the targeted architecture. The problem that LLM encounters with all the examples is that it’s hard for most people to understand the pipeline, table, and its relationship. Areas Where Human Expertise Remains Irreplaceable: Logical Data Model Data modeling is a very soft skills-focused task. You have to communicate with different stakeholders to understand the business context in detail. Understanding what data is needed, the relationship between entities, and considering different scenarios are human-oriented tasks that LLMs must continue to struggle with. Building Pipeline and Framework Once they reach a certain level of complexity, LLMs begin to give up. Imagine if someone asked ChatGPT, “Can you provide me the source code of Android’s next version?” While LLMs can help with routine data engineering tasks, they do not have the insight or inventiveness unique to humans that allows for new solutions to complex challenges, unlocking creativity in technical terms. Domain Expertise and Intuition: Human data engineers bring a unique blend of domain expertise and intuition to their work that often surpasses what conventional software isn’t able to achieve through automation. This intuition allows them to find subtle patterns in data that no fully rigorous automated system can. Based on their knowledge of this field and their experiences in it, they can predict future trends. They can also make decisions in light of a broader context, including corporate or government needs, ethical considerations, and potential future scenarios. This holistic approach to data engineering surpasses what LLMs have achieved. Although LLMs have great power, they are typically restricted to the patterns and relationships they have been trained to recognize. Conclusion: On the whole, Gen AI can certainly automate trivial procedures such as looking for information, launching programs that don’t work properly, repeatedly correcting faults, and anomaly detection. My gut tells me that Gen AI will win out and excel at tasks such as Data Cleansing, Optimization, and Writing Pipelines — once the team understands gaps and missing patterns. But it can not learn purely human soft skills that are important for building logical data models or a framework. I believe that these skills, which cannot be automated, are also essential for stakeholders to ask for innovation in the first place. After all, no one ever asked Steve Jobs if they needed anything like an iPhone; he just thought up what would become its invention. References: https://barrmoses.medium.com/will-genai-replace-data-engineers-no-and-heres-why-708b0a27da6b https://barrmoses.medium.com/will-genai-replace-data-engineers-no-and-heres-why-708b0a27da6b https://barrmoses.medium.com/will-genai-replace-data-engineers-no-and-heres-why-708b0a27da6b ​​__ https://www.linkedin.com/pulse/navigating-data-governance-challenges-era-large-fnq5e __ https://www.linkedin.com/pulse/navigating-data-governance-challenges-era-large-fnq5e https://www.dataversity.net/navigating-the-risks-of-llm-ai-tools-for-data-governance/ https://www.dataversity.net/navigating-the-risks-of-llm-ai-tools-for-data-governance/ https://www.dataversity.net/navigating-the-risks-of-llm-ai-tools-for-data-governance/ https://www.skyflow.com/post/why-ai-governance-requires-data-governance https://www.skyflow.com/post/why-ai-governance-requires-data-governance https://www.skyflow.com/post/why-ai-governance-requires-data-governance https://coreykeyser.medium.com/you-cant-govern-ai-without-governing-data-27bb88d8f9ea https://coreykeyser.medium.com/you-cant-govern-ai-without-governing-data-27bb88d8f9ea https://coreykeyser.medium.com/you-cant-govern-ai-without-governing-data-27bb88d8f9ea https://www.ankursnewsletter.com/p/gpt-4-gpt-3-and-gpt-35-turbo-a-review https://www.ankursnewsletter.com/p/gpt-4-gpt-3-and-gpt-35-turbo-a-review https://www.ankursnewsletter.com/p/gpt-4-gpt-3-and-gpt-35-turbo-a-review https://towardsdatascience.com/from-chaos-to-clarity-streamlining-data-cleansing-using-large-language-models-a539fa0b2d90 https://towardsdatascience.com/from-chaos-to-clarity-streamlining-data-cleansing-using-large-language-models-a539fa0b2d90 https://towardsdatascience.com/from-chaos-to-clarity-streamlining-data-cleansing-using-large-language-models-a539fa0b2d90 https://medium.com/@wangshally11/data-cleaning-warm-up-before-training-large-language-models-74ed1edceead https://medium.com/@wangshally11/data-cleaning-warm-up-before-training-large-language-models-74ed1edceead https://medium.com/@wangshally11/data-cleaning-warm-up-before-training-large-language-models-74ed1edceead

LLMs: An Assessment From a Data Engineer

It's currently 14:30, February 28th, 2023, while I'm writing this update to the challenge. I'm going to make it short. We didn't make it. We actually didn't even get anywhere close to making it. It was a complete failure of a challenge. Okay, okay, that's properly a bit too gloomy. It was kind of expected that we wouldn't make any money after the month was over. But what we didn't receive in terms of monetary gains we got in (quoting the great (scam) entrepreneur Tai Lopez) knowledge. We also decided to make some adjustments to the challenge to keep it going, let's break it down. What Went Wrong First thing first, if you attempt to do this challenge, don't select the shortest month of the year to do a 1 Month 1 Dollar challenge. That's just shooting yourself in the foot. Additionally, don't pick the same month when you've planned holidays with your girlfriend, thinking you can just do a little bit of work. Especially, don't plan two holidays in the shortest month of the year for this challenge. I'm only half joking here, but seriously, we didn't give this challenge the focus and energy it required. We should have picked another month when we both could focus, at least 40 hours a week fully on the project. Next up, and this is the biggest one, we started outreach too late. We did get some early promising results by doing (personalized) outreach on LinkedIn. I think we might have reached out to around 50 people in total which resulted in ~8 getting back to us, and out of those ~8 people, 1 wanted to jump on a call with us, showing some interest in the product. The excitement quickly died down when we discovered that the person didn't really get our value proposition. Both good and bad, we have new information we can react to, and it helps point us in the right direction. However, we didn't get any new calls or follow-ups after this. It could be due to people just being busy but I would guess more that we didn't pursue this aggressively enough. What Did We Learn There is something about learning a new skill where it only really manifests itself in your mind when you try to actually do that skill. Most of this advice is already flooded on the internet, in start-up/bootstrapping forums, etc. But, basically, it can be boiled down to: Get a landing page out there quickly | Forces you to describe your product and makes it more concrete.


Write down your assumptions from the beginning | Continuously test and adjust them to new information.


Reach out to people even when you have a half-baked notion of your product. The first two points are pretty self-explanatory; if you're not sure what is meant by point 2, check out the original post. I do think the third point is the main learning from this challenge. You got to focus on what actually moves the needle and pushes you towards a profitable product, which means getting people to give you money. It's extremely comfortable to just build build build (especially as software engineers) while having wet dreams about all the monthly reoccurring revenue you're going to receive in the end. But that is, on average, not really a productive strategy even though it might feel like it. Sure, all your assumptions could be spot on and your big-bang release is going to be a raving success. Most are just not. So, speak to more people, look up people in relevant positions/groups on LinkedIn, find people following your competitors on Twitter, scour those Facebook groups, and write to people. Also, make sure to read The Mom Test. A Blank Piece of Paper Was it all bad and with no successful experiences? Not at all, one process that really helped us kick this off was the habit of continuously writing down ideas each day. There is something strange about the blank page effect; it can stare about at you for hours on end, almost paralyzing your ability to get started. Should I start with X? Should I include Y? But what about that incredibly important Z? It's seriously frustrating, and it was something that both Rasmus and I were feeling a bit anxious about before starting the project. For the past ~2 months, we have been meeting up once a week to discuss ideas, problems, businesses, and everything under the sun related to bootstrapping companies. I myself had been trying to (and somewhat succeeding) write down 10 ideas a day, and you quickly come to realize: ideas are not that hard to get. It's definitely a muscle that can be trained with consistency just like, well, pretty much anything. Most of that comes out as dog shit, like my brilliant idea of uber but for walking dogs - list where you want to go, and a dog will walk there with you, not exactly a Zero to One idea. It did give us a list of 200+ ideas to start from, which means, 200+ ideas that can be combined, modified, thrown away, or lead you down new paths to even better ideas. The tiniest bit of exploration sparked new ideas which led us to ask new questions that we hadn't considered before. You do see this a lot on forums like indiehackers where people, on a quite consistent basis, will be asking how people generate ideas. And every time, you will see the same (more or less) generic advice: solve your own problems
look for problems at work/with clients or what issues are your friends having These never worked well for me, mainly because I forgot to actually think about these things while doing my work. So, it felt like nothing was actually occurring to me, and I was left with no viable product ideas, and therefore, didn't really build anything. Making a habit out of writing down 10 ideas a day did work, however, so if you're struggling with this give it a try. You'll soon start thinking about potential products consistently. Change of Direction Is it over? No, but we're making some adjustments. It will no longer be a 1 Month 1 Dollar challenge but instead: 1 Year 1 Noodle. This is basically just to say that the challenge will continue in the sense that we will keep trying to get our hands on that sweet magical internet money. And then post an update once in a while. We'll continue working on the product for the foreseeable future until we either get some traction or kill it; it's definitely too early to kill it. If you want to check it out, it can be found here databayz. Outside of the challenge, I have also been working on another project to help do customer discovery on Reddit: This Week On Reddit. The process for this is going to be roughly the same as described above, outreach outreach outreach. But more on that in a later post. It's currently 14:30, February 28th, 2023, while I'm writing this update to the challenge . I'm going to make it short. We didn't make it. We actually didn't even get anywhere close to making it. It was a complete failure of a challenge. challenge Okay, okay, that's properly a bit too gloomy. It was kind of expected that we wouldn't make any money after the month was over. But what we didn't receive in terms of monetary gains we got in (quoting the great (scam) entrepreneur Tai Lopez) knowledge . We also decided to make some adjustments to the challenge to keep it going, let's break it down. knowledge knowledge What Went Wrong First thing first, if you attempt to do this challenge, don't select the shortest month of the year to do a 1 Month 1 Dollar challenge. That's just shooting yourself in the foot. Additionally, don't pick the same month when you've planned holidays with your girlfriend, thinking you can just do a little bit of work. Especially, don't plan two holidays in the shortest month of the year for this challenge. two I'm only half joking here, but seriously, we didn't give this challenge the focus and energy it required. We should have picked another month when we both could focus, at least 40 hours a week fully on the project. Next up, and this is the biggest one, we started outreach too late. We did get some early promising results by doing (personalized) outreach on LinkedIn. I think we might have reached out to around 50 people in total which resulted in ~8 getting back to us, and out of those ~8 people, 1 wanted to jump on a call with us, showing some interest in the product. The excitement quickly died down when we discovered that the person didn't really get our value proposition. Both good and bad, we have new information we can react to, and it helps point us in the right direction. However, we didn't get any new calls or follow-ups after this. It could be due to people just being busy but I would guess more that we didn't pursue this aggressively enough. What Did We Learn There is something about learning a new skill where it only really manifests itself in your mind when you try to actually do that skill. Most of this advice is already flooded on the internet, in start-up/bootstrapping forums, etc. But, basically, it can be boiled down to: Get a landing page out there quickly | Forces you to describe your product and makes it more concrete. Write down your assumptions from the beginning | Continuously test and adjust them to new information. Reach out to people even when you have a half-baked notion of your product. Get a landing page out there quickly | Forces you to describe your product and makes it more concrete. Get a landing page out there quickly | Forces you to describe your product and makes it more concrete. Write down your assumptions from the beginning | Continuously test and adjust them to new information. Write down your assumptions from the beginning | Continuously test and adjust them to new information. Reach out to people even when you have a half-baked notion of your product. Reach out to people even when you have a half-baked notion of your product. The first two points are pretty self-explanatory; if you're not sure what is meant by point 2, check out the original post . I do think the third point is the main learning from this challenge. You got to focus on what actually moves the needle and pushes you towards a profitable product, which means getting people to give you money. original post It's extremely comfortable to just build build build (especially as software engineers) while having wet dreams about all the monthly reoccurring revenue you're going to receive in the end. But that is, on average, not really a productive strategy even though it might feel like it. Sure, all your assumptions could be spot on and your big-bang release is going to be a raving success. Most are just not. So, speak to more people, look up people in relevant positions/groups on LinkedIn, find people following your competitors on Twitter, scour those Facebook groups, and write to people. Also, make sure to read The Mom Test . The Mom Test A Blank Piece of Paper Was it all bad and with no successful experiences? Not at all, one process that really helped us kick this off was the habit of continuously writing down ideas each day. There is something strange about the blank page effect; it can stare about at you for hours on end, almost paralyzing your ability to get started. Should I start with X? Should I include Y? But what about that incredibly important Z? It's seriously frustrating, and it was something that both Rasmus and I were feeling a bit anxious about before starting the project. For the past ~2 months, we have been meeting up once a week to discuss ideas, problems, businesses, and everything under the sun related to bootstrapping companies. I myself had been trying to (and somewhat succeeding) write down 10 ideas a day, and you quickly come to realize: ideas are not that hard to get. It's definitely a muscle that can be trained with consistency just like, well, pretty much anything. Most of that comes out as dog shit, like my brilliant idea of uber but for walking dogs - list where you want to go, and a dog will walk there with you , not exactly a Zero to One idea. uber but for walking dogs - list where you want to go, and a dog will walk there with you It did give us a list of 200+ ideas to start from, which means, 200+ ideas that can be combined, modified, thrown away, or lead you down new paths to even better ideas. The tiniest bit of exploration sparked new ideas which led us to ask new questions that we hadn't considered before. You do see this a lot on forums like indiehackers where people, on a quite consistent basis, will be asking how people generate ideas. And every time, you will see the same (more or less) generic advice: indiehackers solve your own problems look for problems at work/with clients or what issues are your friends having solve your own problems look for problems at work/with clients or what issues are your friends having These never worked well for me, mainly because I forgot to actually think about these things while doing my work. So, it felt like nothing was actually occurring to me, and I was left with no viable product ideas, and therefore, didn't really build anything. Making a habit out of writing down 10 ideas a day did work, however, so if you're struggling with this give it a try. You'll soon start thinking about potential products consistently. Change of Direction Is it over? No, but we're making some adjustments. It will no longer be a 1 Month 1 Dollar challenge but instead: 1 Year 1 Noodle . Year 1 Noodle This is basically just to say that the challenge will continue in the sense that we will keep trying to get our hands on that sweet magical internet money. And then post an update once in a while. We'll continue working on the product for the foreseeable future until we either get some traction or kill it; it's definitely too early to kill it. If you want to check it out, it can be found here databayz . databayz Outside of the challenge, I have also been working on another project to help do customer discovery on Reddit: This Week On Reddit . The process for this is going to be roughly the same as described above, outreach outreach outreach. But more on that in a later post. This Week On Reddit

One Month One Dollar - Part 2: What Went Wrong

High-Stakes Cash Games in Vegas When I was a younger and slightly dumber man, I was captivated by the allure of online poker and high-stakes No-limit Hold ‘em. Going to Vegas and battling it out for millions of dollars with all the high-rollers, was a big dream of mine. I would watch all the tutorials I could get my hands on, read whatever poker book was available to me, and binge every poker show out there. Now, this was a few years after the golden age of online poker which was kicked off by Chris, I shit you not, Moneymaker. An accountant from Nashville and hobby poker player who is said to be responsible for online poker exploding, after he won the WSOP Main Event, gaining entry based on a satellite tournament he played online. For the unfamiliar with online poker, a satellite tournament is basically a (often much) lower-priced tournament that gives the winner(s) entry to a higher-stakes tournament. I'm getting a bit sidetracked here, anyway. In this post-chris-money maker-winning-wsop-main-event environment, a lot of young people (i.e. nerdy white guys, try and guess why it was appealing to me) started printing money online. This laid the basis for a show called 2 Months 2 Million which was centered around this bunch of young poker pros who pooled their bankrolls (money) and gave themselves two months to make a net profit of 2 million dollars. They failed. Well, sort of failed, they made a bunch of money just not the two million dollars. I never made it into professional poker nor did I go to Las Vegas. I did, however, go into Software Engineering and happily forgot about poker and that show. That is until I came across this article about a guy who challenged himself to start from zero and, after one month, built a product that some stranger on the internet would pay money for. I loved the idea and was immediately reminded of that show a long time ago. The difference now being that I actually have acquired a skill set that would allow me to have a real shot at completing this challenge. Even better, I also have a business partner to do the challenge with me. So, from the 1st of February 2023, Rasmus and I will be attempting to start completely from scratch and after 30 days of work, have a product that will have made more than 1 dollar. A million seemed to bit too ambitious. Isn't This Just 12 Month 12 Start-ups but Shorter Maybe, yes, kind of, the chance that an idea is completely original is absolutely minuscule. I've tried to (mentally, at least) do the challenge made famous by Pieter Levels but never really got it kicked off. I started the preparations, loaded up on some ideas, and picked a date, but then, excuses got in the way (work, family, friends, take your pick), and it didn't go anywhere. Taking potentially 12 months off, or building 12 new projects on the side while working full-time just seems really exhaustive to me. But, dedicating one month to try and kick-start a project is way more manageable; both financially and risk-of-burn-out-wise. I used to build a lot of side-projects in my spare time when I just started as a software engineer, which was incredibly fun, but as I've gotten older, I just don't want to spend my time coding for 12+ hours a day. This limited-time scope seems to be a much better fit. Wait, But Why? Wantrepreneur: A person who aspires to be an entrepreneur, especially one who never realizes this ambition At the beginning of January, I wrote about Wantrepreneurship and how I've been wanting to break into this for quite some time now. I must have read every single book under the sun about entrepreneurship, creating micro-saas businesses and start-ups. Yet, I haven't even launched anything always holding back because I lack a good idea or because it's not the right time or insert-other-common-excuse (actually, it's not entirely true. I did launch something called ByGourmand intended to provide subscribers with a wide variety of recipes. If you're currently thinking "So, a shittier version of HelloFresh?", you've got the right idea). But, I seemed to have forgotten an important lesson; one I learned straight after uni having made the jump into software: you don't really learn anything until you take action. I.e., you need to do that thing you're consistently talking about and you will get better at it. I've spent long evenings on YouTube learning to program but equally long evenings building and writing software. And the last step, that's what actually makes the difference. One of my favorite Twitch streamers, theprimeagen, has a perfect acronym for this: TITS (time in the saddle, Elon Musk would love it - spend more time doing that thing. Having set an optimistic deadline while also making a public announcement is hopefully going to be the combination that really pushes this into gear. Additionally, teaming up with Rasmus for this project, I think it creates a situation that will push me to take a real stab at this. So, what's the plan? I'm glad you asked. The Plan This is quite an ambitious deadline, so we're going to be cutting quite a few corners wherever possible. Since we're starting from zero, we can't really have an already researched idea ready to go from day one; we need to start out doing some good old-fashioned brainstorming. No more than 2 days have been put aside for this, along with preliminary research into potential customers and the market. On the third day, we're taking a pick, putting maybe one or two ideas in reserve, and then starting to create a landing page and doing outreach. Based on the feedback, we will start building, do more outreach, and do more building. Rinse and repeat until we either run out of time or, make our first dollar. Honestly, it's a fairly simple approach, but given that this is mostly a learning experience, I would argue it's the ideal way forward. The thing about planning for an activity, that you are unfamiliar with in practice, is that it quickly turns into a big soup of postulates. In the famous words of Mark Hanna: Fugayzi, fugazi. It's a whazy. It's a woozie. It's fairy dust. It's not fucking real, but two people can quickly convince themselves about X hypothesis being very real because the world would be so much sweeter if it was. The plan can be summed up to be hypothesis-driven entrepreneurship if you will. We have a problem, think up potential experiments that could solve said problem, run them, and evaluate them. Continue what works, and stop what doesn't. It's worked for old Greeks; I'm sure it can work for a couple of Danish guys. Speaking for myself here, reaching out to strangers on the internet has always been an Achilles heel for me. I'm not sure why; the thought of it has always made me imagine myself as the human form of a spam email. I fucking hate spam; Escobar had burner phones, I have burner emails. But I've also slowly come to accept the fact that this is going to be a necessity if I ever want to move forward in this process. My first job at Uni was as a phone salesman where I made a sell in my very first phone call, and then never made one again. Hopefully, this month goes a bit better. Likely Outcome Most likely, this project will not make much money within this month. A firm rule is that we cannot beg friends and family to buy the product/service, so we, unfortunately, have to take the long route. Additionally, we could go the cash-grab route and do AI profile pictures, but that just seems boring at this point. Saas businesses have never been easy, and even though we might get lucky and strike gold; the takeaway here is hopefully going to be a lot of learnings that will push both of us into the next step in our entrepreneurial journey. Update You can read about the outcome here. High-Stakes Cash Games in Vegas When I was a younger and slightly dumber man, I was captivated by the allure of online poker and high-stakes No-limit Hold ‘em. Going to Vegas and battling it out for millions of dollars with all the high-rollers, was a big dream of mine. I would watch all the tutorials I could get my hands on, read whatever poker book was available to me, and binge every poker show out there. Now, this was a few years after the golden age of online poker which was kicked off by Chris, I shit you not, Moneymaker. An accountant from Nashville and hobby poker player who is said to be responsible for online poker exploding, after he won the WSOP Main Event, gaining entry based on a satellite tournament he played online. For the unfamiliar with online poker, a satellite tournament is basically a (often much) lower-priced tournament that gives the winner(s) entry to a higher-stakes tournament. I'm getting a bit sidetracked here, anyway. In this post-chris-money maker-winning-wsop-main-event environment, a lot of young people (i.e. nerdy white guys, try and guess why it was appealing to me) started printing money online. This laid the basis for a show called 2 Months 2 Million which was centered around this bunch of young poker pros who pooled their bankrolls (money) and gave themselves two months to make a net profit of 2 million dollars. They failed. Well, sort of failed, they made a bunch of money just not the two million dollars. I never made it into professional poker nor did I go to Las Vegas. I did, however, go into Software Engineering and happily forgot about poker and that show. That is until I came across this article about a guy who challenged himself to start from zero and, after one month, built a product that some stranger on the internet would pay money for. I loved the idea and was immediately reminded of that show a long time ago. The difference now being that I actually have acquired a skill set that would allow me to have a real shot at completing this challenge. Even better, I also have a business partner to do the challenge with me. So, from the 1st of February 2023, Rasmus and I will be attempting to start completely from scratch and after 30 days of work, have a product that will have made more than 1 dollar. A million seemed to bit too ambitious. Rasmus Isn't This Just 12 Month 12 Start-ups but Shorter Maybe, yes, kind of, the chance that an idea is completely original is absolutely minuscule. I've tried to (mentally, at least) do the challenge made famous by Pieter Levels but never really got it kicked off. I started the preparations, loaded up on some ideas, and picked a date, but then, excuses got in the way (work, family, friends, take your pick), and it didn't go anywhere. Pieter Levels Taking potentially 12 months off, or building 12 new projects on the side while working full-time just seems really exhaustive to me. But, dedicating one month to try and kick-start a project is way more manageable; both financially and risk-of-burn-out-wise. I used to build a lot of side-projects in my spare time when I just started as a software engineer, which was incredibly fun, but as I've gotten older, I just don't want to spend my time coding for 12+ hours a day. This limited-time scope seems to be a much better fit. Wait, But Why? Wantrepreneur: A person who aspires to be an entrepreneur, especially one who never realizes this ambition Wantrepreneur: A person who aspires to be an entrepreneur, especially one who never realizes this ambition At the beginning of January, I wrote about Wantrepreneurship and how I've been wanting to break into this for quite some time now. I must have read every single book under the sun about entrepreneurship, creating micro-saas businesses and start-ups. Wantrepreneurship Yet, I haven't even launched anything always holding back because I lack a good idea or because it's not the right time or insert-other-common-excuse (actually, it's not entirely true. I did launch something called ByGourmand intended to provide subscribers with a wide variety of recipes. If you're currently thinking "So, a shittier version of HelloFresh?", you've got the right idea). But, I seemed to have forgotten an important lesson; one I learned straight after uni having made the jump into software: you don't really learn anything until you take action. I.e., you need to do that thing you're consistently talking about and you will get better at it. I've spent long evenings on YouTube learning to program but equally long evenings building and writing software. And the last step, that's what actually makes the difference. One of my favorite Twitch streamers, theprimeagen , has a perfect acronym for this: TITS (time in the saddle, Elon Musk would love it - spend more time doing that thing. theprimeagen love it Having set an optimistic deadline while also making a public announcement is hopefully going to be the combination that really pushes this into gear. Additionally, teaming up with Rasmus for this project, I think it creates a situation that will push me to take a real stab at this. So, what's the plan? I'm glad you asked. The Plan This is quite an ambitious deadline, so we're going to be cutting quite a few corners wherever possible. Since we're starting from zero, we can't really have an already researched idea ready to go from day one; we need to start out doing some good old-fashioned brainstorming. No more than 2 days have been put aside for this, along with preliminary research into potential customers and the market. On the third day, we're taking a pick, putting maybe one or two ideas in reserve, and then starting to create a landing page and doing outreach. Based on the feedback, we will start building, do more outreach, and do more building. Rinse and repeat until we either run out of time or, make our first dollar. Honestly, it's a fairly simple approach, but given that this is mostly a learning experience, I would argue it's the ideal way forward. The thing about planning for an activity, that you are unfamiliar with in practice, is that it quickly turns into a big soup of postulates. In the famous words of Mark Hanna: Fugayzi, fugazi. It's a whazy. It's a woozie. It's fairy dust. Fugayzi, fugazi. It's a whazy. It's a woozie. It's fairy dust. It's not fucking real, but two people can quickly convince themselves about X hypothesis being very real because the world would be so much sweeter if it was. The plan can be summed up to be hypothesis-driven entrepreneurship if you will. We have a problem, think up potential experiments that could solve said problem, run them, and evaluate them. Continue what works, and stop what doesn't. It's worked for old Greeks; I'm sure it can work for a couple of Danish guys. Speaking for myself here, reaching out to strangers on the internet has always been an Achilles heel for me. I'm not sure why; the thought of it has always made me imagine myself as the human form of a spam email. I fucking hate spam; Escobar had burner phones, I have burner emails. But I've also slowly come to accept the fact that this is going to be a necessity if I ever want to move forward in this process. My first job at Uni was as a phone salesman where I made a sell in my very first phone call, and then never made one again. Hopefully, this month goes a bit better. Likely Outcome Most likely, this project will not make much money within this month. A firm rule is that we cannot beg friends and family to buy the product/service, so we, unfortunately, have to take the long route. Additionally, we could go the cash-grab route and do AI profile pictures, but that just seems boring at this point. Saas businesses have never been easy, and even though we might get lucky and strike gold; the takeaway here is hopefully going to be a lot of learnings that will push both of us into the next step in our entrepreneurial journey. Update You can read about the outcome here . here

One Month One Dollar - Part One: The Beginning

Table of Links Abstract and I. Introduction II. Expectations of Blockchain Accessibility III. Approach I: Maintain a Ledger Locally - Run a Full Node IV. Approach II: Query a Third-Party Ledger-Node-As-A-Service (NAAS) V. Approach III: Light Node - External Query & Local Verification VI. Concluding Remark and References II. EXPECTATIONS OF BLOCKCHAIN ACCESSIBILITY The process for a blockchain user to retrieve information from blockchains is similar to using any web service, such as browsing websites (retrieving information from a web server), checking e-mails (retrieving information from a mail server), etc. Therefore, the security expectations match the standard security triad: integrity, availability, and privacy. A. Integrity For blockchain accessibility, integrity means that the user can obtain the correct information on blockchains under the given security model. Much of the existing research focuses on the integrity of the blockchains from the perspective of full nodes, guaranteeing integrity if the user has access to a trusted (e.g. self-owned) full node. However, as more and more users turn to third-party service providers for information on blockchains, we notice that integrity may not be achieved if these service providers are untrusted. While some client protocols, such as Flyclient [10], ensure data integrity without much overhead, such techniques are not universally deployed on every blockchain or adopted by every service provider. B. Availability For blockchain accessibility, availability means that the user can freely access information on blockchains. Most incidents on third-party service providers revolve around availability [36] [39], and at least one vulnerability that creates a denial-of-service has been studied [35]. These cases of empirical evidence suggest that fully relying on a single third-party service may create availability issues. While it is industry practice to diversify and use several thirdparty services as backups of each other, it may also help if the user can employ a solution that does not rely on a single service but utilizes a group of nodes to ensure maximum availability. C. Privacy Privacy encompasses a broad range of cases available in this context: some users may want to conceal their queries from specific eavesdroppers to prevent frontrunning [17], while others may not want to be found using blockchains at all, with Bitcoin being illegal in some countries. These different concerns require drastically different security models that cannot be summarized in a nonspecific way. Therefore, we devote our discussion of privacy in this paper strictly to the problems specific to blockchain accessibility rather than general Internet anonymity needs: an untrusted server of the network should have no information about the users’ queries and the results. While existing Internet protocols such as HTTPS largely realize end-to-end confidentiality between the user and the trusted server, we note that if resolving the user’s query for information involves untrusted parties such as miners and third-party service providers, privacy is not trivially guaranteed and must be discussed on a case-by-case basis. For example, ConsenSys, the company that developed Infura and MetaMask, has claimed that when users use Infura as the default RPC provider in MetaMask, Infura will collect their IP address and Ethereum wallet address they send a transaction [15]. Authors:
(1) Zhongtang Luo, Purdue University (luo401@purdue.edu);
(2) Rohan Murukutla, Supra (r.murukutla@supraoracles.com);
(3) Aniket Kate, Purdue University / Supra (aniket@purdue.edu). This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Table of Links Abstract and I. Introduction Abstract and I. Introduction II. Expectations of Blockchain Accessibility II. Expectations of Blockchain Accessibility III. Approach I: Maintain a Ledger Locally - Run a Full Node III. Approach I: Maintain a Ledger Locally - Run a Full Node IV. Approach II: Query a Third-Party Ledger-Node-As-A-Service (NAAS) IV. Approach II: Query a Third-Party Ledger-Node-As-A-Service (NAAS) V. Approach III: Light Node - External Query & Local Verification V. Approach III: Light Node - External Query & Local Verification VI. Concluding Remark and References VI. Concluding Remark and References II. EXPECTATIONS OF BLOCKCHAIN ACCESSIBILITY The process for a blockchain user to retrieve information from blockchains is similar to using any web service, such as browsing websites (retrieving information from a web server), checking e-mails (retrieving information from a mail server), etc. Therefore, the security expectations match the standard security triad: integrity, availability, and privacy. A. Integrity A. Integrity For blockchain accessibility, integrity means that the user can obtain the correct information on blockchains under the given security model. Much of the existing research focuses on the integrity of the blockchains from the perspective of full nodes, guaranteeing integrity if the user has access to a trusted (e.g. self-owned) full node. However, as more and more users turn to third-party service providers for information on blockchains, we notice that integrity may not be achieved if these service providers are untrusted. While some client protocols, such as Flyclient [10], ensure data integrity without much overhead, such techniques are not universally deployed on every blockchain or adopted by every service provider. B. Availability B. Availability For blockchain accessibility, availability means that the user can freely access information on blockchains. Most incidents on third-party service providers revolve around availability [36] [39], and at least one vulnerability that creates a denial-of-service has been studied [35]. These cases of empirical evidence suggest that fully relying on a single third-party service may create availability issues. While it is industry practice to diversify and use several thirdparty services as backups of each other, it may also help if the user can employ a solution that does not rely on a single service but utilizes a group of nodes to ensure maximum availability. C. Privacy C. Privacy Privacy encompasses a broad range of cases available in this context: some users may want to conceal their queries from specific eavesdroppers to prevent frontrunning [17], while others may not want to be found using blockchains at all, with Bitcoin being illegal in some countries. These different concerns require drastically different security models that cannot be summarized in a nonspecific way. Therefore, we devote our discussion of privacy in this paper strictly to the problems specific to blockchain accessibility rather than general Internet anonymity needs: an untrusted server of the network should have no information about the users’ queries and the results. While existing Internet protocols such as HTTPS largely realize end-to-end confidentiality between the user and the trusted server, we note that if resolving the user’s query for information involves untrusted parties such as miners and third-party service providers, privacy is not trivially guaranteed and must be discussed on a case-by-case basis. For example, ConsenSys, the company that developed Infura and MetaMask, has claimed that when users use Infura as the default RPC provider in MetaMask, Infura will collect their IP address and Ethereum wallet address they send a transaction [15]. Authors: (1) Zhongtang Luo, Purdue University (luo401@purdue.edu); (2) Rohan Murukutla, Supra (r.murukutla@supraoracles.com); (3) Aniket Kate, Purdue University / Supra (aniket@purdue.edu). Authors: Authors: (1) Zhongtang Luo, Purdue University (luo401@purdue.edu); (2) Rohan Murukutla, Supra (r.murukutla@supraoracles.com); (3) Aniket Kate, Purdue University / Supra (aniket@purdue.edu). This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. available on arxiv

Key Expectations for Blockchain Accessibility: Integrity, Availability, and Privacy

COPA v. Wright, Court Filing, retrieved on January 29, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part of this filing here. This part is 39 of 42. 37. The Tulip Trust Deed (Particulars of Claim at [66A] {A/2/10}) ({ID_001186}) / {L8/20/1}) The Fifth Pleaded Example 728. In the Kleiman Litigation, Dr Wright proffered a Deed of Trust document as evidence of the existence of a trust called the Tulip Trust. Dr Wright has claimed that the Tulip Trust held Bitcoin and/or an encrypted file with keys to that Bitcoin. The Deed of Trust document that was adduced by Dr Wright was dated 23 October 2012. (a) COPA’s Reasons for Alleging Forgery 729. The date of 23 October 2012 was false. Computer forensic analysis of this document shows that it was backdated and that it was not created until at least 22 May 2015 (over two years after the death of David Kleiman on 26 April 2013). This document was therefore forged. As to the basis on which the Claimant alleges forgery, the Claimant relies on the above matters and the fact that this Deed of Trust document was found to be backdated in the Order of Justice Reinhart dated 27 August 2019. 730. A copy of this document is at C00000560 {L8/17/1}, which was included in the Extended Disclosure served on 7 March 2023. The Re-Re-Amended Defence was served on 20 April 2023. (b) Dr Wright’s Explanations and COPA’s Rebuttal 731. The document appears as a Deed of Trust between two Seychelles companies, Wright International Investments (“WIIL”) and Tulip Trading Ltd (“TTL”) with a date of 23 October 2012. 732. In Wright11 Appendix C, Dr Wright addressed this 23 October 2012 Deed of Trust document by reference to one particular version of it. There are a number of copies disclosed which are all identical in substance: 732.1. (C00000560) / {L8/17/1} – (includes the Kleiman case reference at the top). 732.2. (ID_001186) / {L8/20/1}; 732.3. (ID_003790) / {L8/28/1}; 732.4. (ID_003982) / {L8/14/1}; and 732.5. (ID_003329) / L15/86/1} – this is the version Dr Wright refers to in Wright11. 733. Mr Madden addresses the identical nature of the above documents in PM48, {H/304/8}. In PM48, Mr Madden notes that the documents analysed indicate that WIIL was purchased as an aged shelf company in 2014, not being active prior to that date: PM48 at [29] {H/304/9}. Mr Madden also notes the effect of similar analysis in respect of other similar documents relating to TTL (PM4 [119-127], {H/29/38}). 734. In his Defence (after various amendments), Dr Wright states that, pursuant to an order of the US Court in the Kleiman proceedings, he disclosed a copy of a Deed of Trust document between two Seychelles companies, WIIL and TTL, with a date of 23 October 2012 (Defence [85A(1)] {A/3/26}. Dr Wright claims that: “The date 23 October 2012 is not a false date as the Deed of Trust was executed on 23 October 2012” (Defence [85A(5)] {A/3/27}. 735. In Wright11, Dr Wright gives the following account. He says that he set up the trust structure with the intention that he did not have any rights to see documents until 2020 (Wright11 Appendix C, [6.6] {CSW/3/14}). Dr Wright says that Dianne Pinder of Lloyds solicitors in Brisbane Australia drafted a deed of trust to replace a former trust structure that had been set up in such a way that he did not have a right to see documents until 2020 (Wright11 Appendix C, [6.6] {CSW/3/14}). Dr Wright says that, as he was not a party to the Tulip Trust Deed, he can only comment on what appears on the face of the documents, and that the version at {ID_003329} is not the trust deed for the Tulip Trust (Wright11 Appendix C, [6.11] {CSW/3/15}). The position stated in Wright11 therefore appears to be that, whilst a trust was settled on 23 October 2012 which was called the Tulip Trust, the disclosed versions set out above do not represent the deed of that trust or record its terms. 736. Dr Wright further states in Wright11 that he thinks that the version at {ID_003329} has been doctored by someone, as some of the parties acting for Savannah Ltd as noted in the document held no authority with the company, which he did not find out until after 2022 (Wright11 Appendix C, [6.12] {CSW/3/15}). 737. In his oral evidence at trial, Dr Wright at first accepted that he had sworn in the Kleiman proceedings that the Tulip Trust Deed put to him in those proceedings (which was the version at {L8/17/1}) was an authentic document {Day4/107:4} to {Day4/109:5}. However, he then went on to say that it does not record the terms of the trust. He said that this particular Tulip Trust Deed is not a real document and that it is not part of the trust. Dr Wright claimed that he told the Judge in Kleiman that it was a real document but that he did not know any different to say otherwise at that time: {Day4/109:2} to {Day4/112:2}. He claimed that he had subsequently spoken to some of the individuals whose signatures appear on this Tulip Trust Deed and they told him that they did not sign it: {Day4/113:6}. 738. Dr Wright claimed that this particular version of the Tulip Trust Deed was formed by someone merging documents together: {Day4/114:5}. Dr Wright said that it was a fake document used by Ira Kleiman, and that there had never been any agreement made between Wright International and Tulip Trading: {Day4/115:10} to {Day4/115/20}. 739. COPA submitted that Dr Wright’s explanation should be rejected for the following reasons: 739.1. On Dr Wright’s own admission, the Tulip Trust Deed is not a genuine document on the basis that (on his account) (i) there never has been any agreement between WIIL and TTL at all; (ii) the signatures are said not to be genuine; and (iii) the terms do not reflect what he understood to be the terms of the Tulip Trust Deed actually executed on 23 October 2012. It is, however, remarkable that he failed to mention this in his Re-Amended Defence. 739.2. There is no evidence of any of other version of the Tulip Trust Deed dated to 23 October 2012 with different terms. Dr Wright has not brought any of those who are said to deny signing this deed to Court as witnesses, nor has he called anyone as a witness to say what the “real” terms of the Tulip Trust are. 739.3. WIIL is purportedly a party to the Tulip Trust Deed, but that company was only first purchased as an off the shelf company by Dr Wright in October 2014. Mr Madden's findings in Appendix PM48 to the effect that alteration of documents supports that proposition {H/304/9} were not challenged in cross-examination. 739.4. Paragraph 3 of this Tulip Trust Deed {L8/17/2} refers to bitcoin having been transferred into TTL on 10 June 2011, although that company likewise was not purchased until October 2014 (as explained in relation to {ID_001421} and {ID_001930} in COPA’s original Forgeries Schedule at {A/2/91} and {A/2/101}. 739.5. There is nothing in the terms of this trust (as recorded in this Deed) to say that trust documents cannot be shown to Dr Wright. He claimed that he did not know the terms of the document, but also that those terms precluded him from talking directly to any of the individuals involved. He then said that he had spoken to them and found out that the signatures on the document were not genuine. Dr Wright's evidence about this document, and the Tulip Trust more generally, has been confused and internally inconsistent. In particular, he has invented the excuse of having been precluded from seeing the document to explain away his having sworn to its authenticity in the Kleiman proceedings and made a sworn declaration based on its terms, but then having denied its authenticity in the Granath proceedings. See generally: {Day3/105:2} to {Day3/119:5}. (c) Conclusions 740. I found Dr Wright’s contorted explanations to be wholly unconvincing and false, including his final excuse that this document was ‘doctored by someone’. 741. There is strong evidence that (and I so find) both Tulip Trading Limited and Wright International Investments Ltd were acquired by Dr Wright in 2014 as aged shelf companies, and that the ‘Tulip Trust’ itself was a fabrication designed to shield Dr Wright’s assets against possible bankruptcy. Dr Wright’s explanations of the terms of the Trust were inconsistent and did not ring true. He has never explained the plain inconsistency between his assertion that the Trust put his assets (including his IP in various documents) beyond reach, yet his continued ability apparently to reference and use all such documents to yield the large number of ‘White Papers’ which are said to have given rise to all the claimed patent filings for nChain. Continue Reading Here. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings.

This court case retrieved on January 29, 2024, judiciary.uk is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. COPA v. Wright, Court Filing, retrieved on January 29, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part of this filing here. This part is 39 of 42. COPA v. Wright, Court Filing, retrieved on January 29, 2024, is part of HackerNoon’s Legal PDF Series . You can jump to any part of this filing here . This part is 39 of 42. HackerNoon’s Legal PDF Series HackerNoon’s Legal PDF Series here here 37. The Tulip Trust Deed (Particulars of Claim at [66A] {A/2/10}) ({ID_001186}) / {L8/20/1}) The Fifth Pleaded Example 728. In the Kleiman Litigation, Dr Wright proffered a Deed of Trust document as evidence of the existence of a trust called the Tulip Trust. Dr Wright has claimed that the Tulip Trust held Bitcoin and/or an encrypted file with keys to that Bitcoin. The Deed of Trust document that was adduced by Dr Wright was dated 23 October 2012. Kleiman (a) COPA’s Reasons for Alleging Forgery (a) COPA’s Reasons for Alleging Forgery 729. The date of 23 October 2012 was false. Computer forensic analysis of this document shows that it was backdated and that it was not created until at least 22 May 2015 (over two years after the death of David Kleiman on 26 April 2013). This document was therefore forged. As to the basis on which the Claimant alleges forgery, the Claimant relies on the above matters and the fact that this Deed of Trust document was found to be backdated in the Order of Justice Reinhart dated 27 August 2019. 730. A copy of this document is at C00000560 {L8/17/1}, which was included in the Extended Disclosure served on 7 March 2023. The Re-Re-Amended Defence was served on 20 April 2023. (b) Dr Wright’s Explanations and COPA’s Rebuttal (b) Dr Wright’s Explanations and COPA’s Rebuttal 731. The document appears as a Deed of Trust between two Seychelles companies, Wright International Investments (“ WIIL ”) and Tulip Trading Ltd (“ TTL ”) with a date of 23 October 2012. WIIL TTL 732. In Wright11 Appendix C, Dr Wright addressed this 23 October 2012 Deed of Trust document by reference to one particular version of it. There are a number of copies disclosed which are all identical in substance: 732.1. (C00000560) / {L8/17/1} – (includes the Kleiman case reference at the top). 732.2. (ID_001186) / {L8/20/1}; 732.3. (ID_003790) / {L8/28/1}; 732.4. (ID_003982) / {L8/14/1}; and 732.5. (ID_003329) / L15/86/1} – this is the version Dr Wright refers to in Wright11. 733. Mr Madden addresses the identical nature of the above documents in PM48, {H/304/8}. In PM48, Mr Madden notes that the documents analysed indicate that WIIL was purchased as an aged shelf company in 2014, not being active prior to that date: PM48 at [29] {H/304/9}. Mr Madden also notes the effect of similar analysis in respect of other similar documents relating to TTL (PM4 [119-127], {H/29/38}). 734. In his Defence (after various amendments), Dr Wright states that, pursuant to an order of the US Court in the Kleiman proceedings, he disclosed a copy of a Deed of Trust document between two Seychelles companies, WIIL and TTL, with a date of 23 October 2012 (Defence [85A(1)] {A/3/26}. Dr Wright claims that: “The date 23 October 2012 is not a false date as the Deed of Trust was executed on 23 October 2012” (Defence [85A(5)] {A/3/27}. “The date 23 October 2012 is not a false date as the Deed of Trust was executed on 23 October 2012” 735. In Wright11, Dr Wright gives the following account. He says that he set up the trust structure with the intention that he did not have any rights to see documents until 2020 (Wright11 Appendix C, [6.6] {CSW/3/14}). Dr Wright says that Dianne Pinder of Lloyds solicitors in Brisbane Australia drafted a deed of trust to replace a former trust structure that had been set up in such a way that he did not have a right to see documents until 2020 (Wright11 Appendix C, [6.6] {CSW/3/14}). Dr Wright says that, as he was not a party to the Tulip Trust Deed, he can only comment on what appears on the face of the documents, and that the version at {ID_003329} is not the trust deed for the Tulip Trust (Wright11 Appendix C, [6.11] {CSW/3/15}). The position stated in Wright11 therefore appears to be that, whilst a trust was settled on 23 October 2012 which was called the Tulip Trust, the disclosed versions set out above do not represent the deed of that trust or record its terms. 736. Dr Wright further states in Wright11 that he thinks that the version at {ID_003329} has been doctored by someone, as some of the parties acting for Savannah Ltd as noted in the document held no authority with the company, which he did not find out until after 2022 (Wright11 Appendix C, [6.12] {CSW/3/15}). 737. In his oral evidence at trial, Dr Wright at first accepted that he had sworn in the Kleiman proceedings that the Tulip Trust Deed put to him in those proceedings (which was the version at {L8/17/1}) was an authentic document {Day4/107:4} to {Day4/109:5}. However, he then went on to say that it does not record the terms of the trust. He said that this particular Tulip Trust Deed is not a real document and that it is not part of the trust. Dr Wright claimed that he told the Judge in Kleiman that it was a real document but that he did not know any different to say otherwise at that time: {Day4/109:2} to {Day4/112:2}. He claimed that he had subsequently spoken to some of the individuals whose signatures appear on this Tulip Trust Deed and they told him that they did not sign it: {Day4/113:6}. 738. Dr Wright claimed that this particular version of the Tulip Trust Deed was formed by someone merging documents together: {Day4/114:5}. Dr Wright said that it was a fake document used by Ira Kleiman, and that there had never been any agreement made between Wright International and Tulip Trading: {Day4/115:10} to {Day4/115/20}. 739. COPA submitted that Dr Wright’s explanation should be rejected for the following reasons: 739.1. On Dr Wright’s own admission, the Tulip Trust Deed is not a genuine document on the basis that (on his account) (i) there never has been any agreement between WIIL and TTL at all; (ii) the signatures are said not to be genuine; and (iii) the terms do not reflect what he understood to be the terms of the Tulip Trust Deed actually executed on 23 October 2012. It is, however, remarkable that he failed to mention this in his Re-Amended Defence. 739.2. There is no evidence of any of other version of the Tulip Trust Deed dated to 23 October 2012 with different terms. Dr Wright has not brought any of those who are said to deny signing this deed to Court as witnesses, nor has he called anyone as a witness to say what the “real” terms of the Tulip Trust are. 739.3. WIIL is purportedly a party to the Tulip Trust Deed, but that company was only first purchased as an off the shelf company by Dr Wright in October 2014. Mr Madden's findings in Appendix PM48 to the effect that alteration of documents supports that proposition {H/304/9} were not challenged in cross-examination. 739.4. Paragraph 3 of this Tulip Trust Deed {L8/17/2} refers to bitcoin having been transferred into TTL on 10 June 2011, although that company likewise was not purchased until October 2014 (as explained in relation to {ID_001421} and {ID_001930} in COPA’s original Forgeries Schedule at {A/2/91} and {A/2/101}. 739.5. There is nothing in the terms of this trust (as recorded in this Deed) to say that trust documents cannot be shown to Dr Wright. He claimed that he did not know the terms of the document, but also that those terms precluded him from talking directly to any of the individuals involved. He then said that he had spoken to them and found out that the signatures on the document were not genuine. Dr Wright's evidence about this document, and the Tulip Trust more generally, has been confused and internally inconsistent. In particular, he has invented the excuse of having been precluded from seeing the document to explain away his having sworn to its authenticity in the Kleiman proceedings and made a sworn declaration based on its terms, but then having denied its authenticity in the Granath proceedings. See generally: {Day3/105:2} to {Day3/119:5}. Kleiman Granath (c) Conclusions (c) Conclusions 740. I found Dr Wright’s contorted explanations to be wholly unconvincing and false, including his final excuse that this document was ‘doctored by someone’. 741. There is strong evidence that (and I so find) both Tulip Trading Limited and Wright International Investments Ltd were acquired by Dr Wright in 2014 as aged shelf companies, and that the ‘Tulip Trust’ itself was a fabrication designed to shield Dr Wright’s assets against possible bankruptcy. Dr Wright’s explanations of the terms of the Trust were inconsistent and did not ring true. He has never explained the plain inconsistency between his assertion that the Trust put his assets (including his IP in various documents) beyond reach, yet his continued ability apparently to reference and use all such documents to yield the large number of ‘White Papers’ which are said to have given rise to all the claimed patent filings for nChain. Continue Reading Here. Continue Reading Here . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on January 29, 2024, judiciary.uk is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on January 29, 2024, judiciary.uk is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. judiciary.uk judiciary.uk

Forensic Analysis Exposes Flaws in Craig Wright's Tulip Trust Deed

Solve for the Edges and Get The Middle for Free: Innovating for Inclusivity 

How to Detect and Minimise Hallucinations in AI Models

Craig Wright's Bitcoin White Paper Document Questioned for Forgery

COPA Uncovers Manipulated Bank Statements in Wright's Claim to Be Satoshi Nakamoto

COPA v. Wright, Court Filing, retrieved on January 29, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part of this filing here. This part is 28 of 42. 26. The SSRN Submission (Particulars of Claim at [30]-[35] {A/2/10}) The Fourth Pleaded Example 489. On or about 21 August 2019, Dr Wright uploaded to the Social Science Research Network (SSRN) a document which he asserts to be the ‘final’ version of the Bitcoin White Paper, in which he is named as the author. The post claims that the document was written on 21 August 2008. Dr Wright posted two versions of what he claims to be his original version of the Bitcoin White Paper within SSRN. **(a) COPA’s Reasons for Alleging Forgery** 490. The metadata of the actual Bitcoin White Paper has a creation date of 24 March 2009. The first version Dr Wright submitted to SSRN has discrepancies in the document properties. Examination of this first version reveals that its metadata was tampered with - supplemental metadata was added to this version to superficially indicate a creation date of 24 January 2008 and a “modified” date of 21 May 2008. This added metadata displays as the creation and modified date in the user interface of standard consumer software, i.e. the tampered dates are what would appear to a layperson upon cursory examination. However, a forensic examination of the metadata of this first version reveals another “creation date” entry embedded within the metadata, specifying a creation date that corresponds exactly to the creation date of the Bitcoin White Paper, specifically “/CreationDate (D:20090324113315-06:00)". 491. The metadata of this first version includes an entry indicating that the original creation date is 29 March 2009, which is at odds with the creation date of 24 January 2008 that shows up in other parts of the metadata. In the premises, it is averred that this first version posted to SSRN is actually a copied version of the Bitcoin White Paper with alterations to its metadata (at least that the dates of 24 January 2008 and 21 May 2008 were added to the genuine metadata of the Bitcoin White Paper) to make it appear that it was created in 2008. It is averred that the dates of 24 January 2008 and 21 May 2008 were added to the genuine metadata of the Bitcoin White Paper by Wright to support his attempt to claim that he had drafted the Bitcoin White Paper. 492. The second version that Dr Wright uploaded to SSRN, which is the version he has currently uploaded there, had further changes to the metadata compared to the first version. However, the original creation date of 24 March 2009 from the actual Bitcoin White Paper still exists within the second version’s metadata. COPA allege that Dr Wright again sought to manipulate the metadata a second time but failed to remove the original creation date. 493. The genuine metadata in the actual Bitcoin White Paper and metadata contained within the two versions posted on SSRN by Dr Wright all state the 24 March 2009 date as being the creation date, with the dates/times agreeing to the millisecond. (b) Dr Wright’s Explanations and COPA’s Rebuttal 494. In his Defence, Dr Wright admits that the two versions of the Bitcoin White Paper which Dr Wright uploaded to SSRN were not created in 2008 or 2009, but in 2019. He claims that his purpose in uploading these versions was not to prove that he was the author of the Bitcoin White Paper but “to assert [his] authorship of the White Paper”: see Defence, [55-56] {A/3/16}. In his Defence, Dr Wright gives no explanation for the uploaded versions having metadata creation dates of 2008 and 2009 respectively. 495. In Appendix B to Wright11, Dr Wright repeats the account given in his Defence. However, he now adds the assertion that he prepared each document in LATEX and that he set the metadata in LATEX to refer to creation dates of 2008 and 2009 respectively. See: {CSW/3/8}. 496. COPA submitted that Dr Wright’s explanation should be rejected for the following reasons: 496.1. As established by the evidence of Mr Rosendahl (which was agreed in the joint statement by Dr Wright’s expert, Mr Lynch), Dr Wright’s account of the Bitcoin White Paper being authored in LATEX is false. There is equally no basis for saying that the versions of the White Paper uploaded to the SSRN in 2019 were created in LATEX. 496.2. Accordingly, the only conclusion to be drawn from these versions having been created by Dr Wright in 2019 (as is admitted) but containing metadata referring to 2008 / 2009 creation dates is that the metadata information was deliberately backdated. 496.3. In summary, Dr Wright in 2019 posted publicly two versions of the Bitcoin White Paper which he presented as his work and which contained metadata timestamps backdated to 2008. In the context of Dr Wright claiming to be Satoshi Nakamoto and to have written the Bitcoin White Paper, the only plausible explanation is that he was presenting these to the world as early originals of the paper written by him. (c) Conclusion 497. In addition to the points set out above, I refer also to the analysis in the main Judgment at [489]-[495] of what Dr Wright did with the pdfcreationdate command and how those commands were added to the White Paper LaTeX files in November 2023. 498. Accordingly, Dr Wright’s latest explanation, based on the assertion that the Bitcoin White Paper was created in LATEX, is plainly false. The document was deliberately backdated by Dr Wright, in an attempt to present those two versions of the Bitcoin White Paper as early originals written by him. This was all lies. Continue Reading Here. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings.

This court case retrieved on January 29, 2024, judiciary.uk is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. COPA v. Wright, Court Filing, retrieved on January 29, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part of this filing here. This part is 28 of 42. COPA v. Wright, Court Filing, retrieved on January 29, 2024, is part of HackerNoon’s Legal PDF Series . You can jump to any part of this filing here . This part is 28 of 42. HackerNoon’s Legal PDF Series HackerNoon’s Legal PDF Series here here 26. The SSRN Submission (Particulars of Claim at [30]-[35] {A/2/10}) The Fourth Pleaded Example 489. On or about 21 August 2019, Dr Wright uploaded to the Social Science Research Network (SSRN) a document which he asserts to be the ‘final’ version of the Bitcoin White Paper, in which he is named as the author. The post claims that the document was written on 21 August 2008. Dr Wright posted two versions of what he claims to be his original version of the Bitcoin White Paper within SSRN. **(a) COPA’s Reasons for Alleging Forgery ** 490. The metadata of the actual Bitcoin White Paper has a creation date of 24 March 2009. The first version Dr Wright submitted to SSRN has discrepancies in the document properties. Examination of this first version reveals that its metadata was tampered with - supplemental metadata was added to this version to superficially indicate a creation date of 24 January 2008 and a “modified” date of 21 May 2008. This added metadata displays as the creation and modified date in the user interface of standard consumer software, i.e. the tampered dates are what would appear to a layperson upon cursory examination. However, a forensic examination of the metadata of this first version reveals another “creation date” entry embedded within the metadata, specifying a creation date that corresponds exactly to the creation date of the Bitcoin White Paper, specifically “/CreationDate (D:20090324113315-06:00)". 491. The metadata of this first version includes an entry indicating that the original creation date is 29 March 2009, which is at odds with the creation date of 24 January 2008 that shows up in other parts of the metadata. In the premises, it is averred that this first version posted to SSRN is actually a copied version of the Bitcoin White Paper with alterations to its metadata (at least that the dates of 24 January 2008 and 21 May 2008 were added to the genuine metadata of the Bitcoin White Paper) to make it appear that it was created in 2008. It is averred that the dates of 24 January 2008 and 21 May 2008 were added to the genuine metadata of the Bitcoin White Paper by Wright to support his attempt to claim that he had drafted the Bitcoin White Paper. 492. The second version that Dr Wright uploaded to SSRN, which is the version he has currently uploaded there, had further changes to the metadata compared to the first version. However, the original creation date of 24 March 2009 from the actual Bitcoin White Paper still exists within the second version’s metadata. COPA allege that Dr Wright again sought to manipulate the metadata a second time but failed to remove the original creation date. 493. The genuine metadata in the actual Bitcoin White Paper and metadata contained within the two versions posted on SSRN by Dr Wright all state the 24 March 2009 date as being the creation date, with the dates/times agreeing to the millisecond. (b) Dr Wright’s Explanations and COPA’s Rebuttal (b) Dr Wright’s Explanations and COPA’s Rebuttal 494. In his Defence, Dr Wright admits that the two versions of the Bitcoin White Paper which Dr Wright uploaded to SSRN were not created in 2008 or 2009, but in 2019. He claims that his purpose in uploading these versions was not to prove that he was the author of the Bitcoin White Paper but “to assert [his] authorship of the White Paper”: see Defence, [55-56] {A/3/16}. In his Defence, Dr Wright gives no explanation for the uploaded versions having metadata creation dates of 2008 and 2009 respectively. 495. In Appendix B to Wright11, Dr Wright repeats the account given in his Defence. However, he now adds the assertion that he prepared each document in LATEX and that he set the metadata in LATEX to refer to creation dates of 2008 and 2009 respectively. See: {CSW/3/8}. 496. COPA submitted that Dr Wright’s explanation should be rejected for the following reasons: 496.1. As established by the evidence of Mr Rosendahl (which was agreed in the joint statement by Dr Wright’s expert, Mr Lynch), Dr Wright’s account of the Bitcoin White Paper being authored in LATEX is false. There is equally no basis for saying that the versions of the White Paper uploaded to the SSRN in 2019 were created in LATEX. 496.2. Accordingly, the only conclusion to be drawn from these versions having been created by Dr Wright in 2019 (as is admitted) but containing metadata referring to 2008 / 2009 creation dates is that the metadata information was deliberately backdated. 496.3. In summary, Dr Wright in 2019 posted publicly two versions of the Bitcoin White Paper which he presented as his work and which contained metadata timestamps backdated to 2008. In the context of Dr Wright claiming to be Satoshi Nakamoto and to have written the Bitcoin White Paper, the only plausible explanation is that he was presenting these to the world as early originals of the paper written by him. (c) Conclusion (c) Conclusion 497. In addition to the points set out above, I refer also to the analysis in the main Judgment at [489]-[495] of what Dr Wright did with the pdfcreationdate command and how those commands were added to the White Paper LaTeX files in November 2023. 498. Accordingly, Dr Wright’s latest explanation, based on the assertion that the Bitcoin White Paper was created in LATEX, is plainly false. The document was deliberately backdated by Dr Wright, in an attempt to present those two versions of the Bitcoin White Paper as early originals written by him. This was all lies. Continue Reading Here. Continue Reading Here . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on January 29, 2024, judiciary.uk is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on January 29, 2024, judiciary.uk is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. judiciary.uk judiciary.uk

COPA Sues Craig Wright for Forging Bitcoin White Paper Metadata

COPA v. Wright, Court Filing, retrieved on January 29, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part of this filing here. This part is 26 of 42. 24. Timecoin ODT Whitepaper (Reliance Document) {ID_000254} 446. The document purports to be a precursor draft of the Bitcoin White Paper and is presented as if written by Dr Wright. It is dated in the period 6 May 2008 to 12 December 2008 in its metadata, and Dr Wright states its approximate date to be 6 May 2008 in his Chain of Custody information. (a) COPA’s Reasons for Alleging Forgery 447. The document has been backdated. Rather than being a precursor document to the Bitcoin White Paper as it purports to be, this document has been created from the Bitcoin White Paper subsequently and edited in such a way that it appears as if it was precursor work. [PM2 60-64]]. 448. {ID_000254} has apparently been converted from the Bitcoin White Paper (which is a PDF) into a more easily editable format and has then undergone further conversions via intermediate documents [PM2 [60-64]]. Font configurations and the absence of diagrams are consistent with this conclusion [PM2 [17-28]]. No such intermediate document has been disclosed. 449. Diagrams have been omitted from this document as a result of the conversion process from PDF. The inclusion of the object replacement character ￼ within the document [a point where a diagram would be expected to appear is consistent with {ID_000254} being created by a process of conversion of a different document. [PM2 [28]]. 450. Where diagrams are absent, the document nevertheless preserves margin indentations from the Bitcoin White Paper PDF, but which do not match the content of the document. [PM2 [29-37]]. 451. The document irregularly contains words throughout in which hyphens ought to appear but are missing. This is not consistent with ordinary dictation or typing error but is as an artefact of conversion from PDF and backdating. [PM2 [38-44]]. 452. A conversion of the Bitcoin White Paper PDF to editable form would result in corruption of formulae. In each case where those formulae would have appeared corrupted, they have been deleted from {ID_000254}, leaving behind white space. [PM2 [45-48]]. 453. The document contains irregular line breaks consistent with conversion from the Bitcoin White Paper PDF into editable form and backdating. [PM2 [49-51]]. 454. The document contains text that matches the corrected text of the Bitcoin White Paper (2009 version) [PM2 [12]]. It does not match the October 2008 or November 2008 versions of the Bitcoin White Paper, even though this document purports to be earlier than both of them. 455. The document has been disclosed with irregular metadata listed in relation to its Created and Last Accessed external metadata properties. [PM2 [6-11]]. (b) COPA’s Reasons for Inferring Dr Wright’s Knowledge / Responsibility 456. The effect of the tampering is to make the document appear to be supportive of Dr Wright’s claim to be Satoshi Nakamoto (presenting as a predecessor draft of the Bitcoin White Paper and supposedly written by him in early 2008), contrary to fact. Further, the document uses the same software (OpenOffice Writer) as used by Satoshi Nakamoto. 457. Dr Wright has positively asserted in these proceedings that this is a document on which he primarily relies as supporting his claim to be Satoshi Nakamoto. 458. The document bears Dr Wright’s name and contact details. 459. The contact details included refer to Charles Sturt University. In his evidence in these proceedings, Dr Wright has claimed to have drafted and shared versions of the Bitcoin White Paper while studying at Charles Sturt University, and to have discussed the concepts with teaching staff at Charles Sturt University. [Wright1 [87], Wright4 [52]]. 460. In his evidence in these proceedings, Dr Wright positively relies upon the presence of the word “Timecoin” in documents he has disclosed as being precursor work to the Bitcoin White Paper and thus forming part of the story behind his claim to be Satoshi Nakamoto. Moreover, on the basis of his narrative, this is a detail which would have been known to him and to few, if any, others. [Wright1 [26], Wright4 [6.c.x.]]. 461. The document contains metadata that purports to pre-date the Bitcoin White Paper, indicating efforts at backdating to support Dr Wright’s claim. 462. Dr Wright claims, in his chain of custody information, that only he drafted this document. 463. Dr Wright has stated in these proceedings that this was a draft of a document under the name TimeCoin which later became bitcoin. [Exhibit CSW-5] 464. Dr Wright has not disclosed the apparent intermediate document from which this document was created. [PM2 [63]]. (c) Dr Wright’s Explanations and COPA’s Rebuttal 465. Dr Wright sought to explain away a number of the anomalous findings by saying that both this document and the Bitcoin White Paper were originally created in LATEX and that the commands in the original code accounted for such features as (a) the notes being in a font which was the same as would later be used for tables in the White Paper; (b) the OBJ character; (c) indentation in empty lines corresponding to the size of flowcharts later featuring in the Bitcoin White Paper; and (d) irregularities in hyphenation. See {CSW/2/26} to {CSW/2/28}; {Day3/139:21} to {Day3/152:8}. 466. Dr Wright sought to explain away the content of the document matching the March 2009 version of the Bitcoin White Paper rather than the earlier released versions by claiming that he does not “write things linearly”. He claimed to have used text in this early document, edited it out again in the August and October 2008 versions of the White Paper and then added it back in again for the March 2009 version. See {CSW/2/28} to {CSW/2/29}; {Day3/153:9} to {Day3/154:10}. 467. Dr Wright sought to explain away the irregular metadata by saying that his use of “Xcopy and related tools” somehow accounted for it: {CSW/2/28}. 468. COPA submitted that this explanation should be rejected as dishonest for the following reasons: 468.1. The Bitcoin White Paper was not originally created in LATEX, as convincingly established by the expert evidence of Mr Rosendahl (which was agreed by Dr Wright’s expert, Mr Lynch, in the joint statement). There is equally no basis for saying that this document was originally created in LATEX. Furthermore, no LAT EX.tex file has been provided to support Dr Wright’s account in relation to the creation of this document. 468.2. The use of LATEX to create the document would not account for the presence of the OBJ (object replacement) character, which on the expert evidence is purely and simply an artefact of conversion from PDF: see PM2 [26-28] {H/17/8}. 468.3. Neither would the use of LATEX to create the document account for Dr Wright having predicted in a precursor document precisely the size required for diagrams and having applied coding to mark out indentations for the diagrams in what would be empty space in the document. 468.4. Neither would the use of LATEX to create the document account for there being irregular hyphenation in precisely the points where line breaks appear in the text of the Bitcoin White Paper. Dr Wright could only weakly account for this as him doing “unusual things” and deliberately including irregular hyphenation {Day3/10:11}. This explanation was nonsensical. Further, it assumed that his deliberate inclusion of irregular hyphenation just happened by coincidence to fall in the places where line breaks existed in the Bitcoin White Paper. 468.5. Dr Wright’s explanation for the irregular metadata was at odds with the independent expert evidence. It also assumed that this irregularity happened by coincidence to co-exist with the other irregularities, when in fact all suggest backdating. 468.6. Dr Wright’s explanation for the content of the document including changes which were made to the Bitcoin White Paper between its 2008 and 2009 versions is inherently unlikely. It also assumes that this irregularity happened by coincidence to co-exist with all the other irregularities, when in fact all suggest backdating. (d) Conclusion 469. The explanations gathered in Appendix 1 to Dr Wright’s Closing confirm his reliance on both this document and the Bitcoin White Paper being based on earlier LATEX files and his allegation that the diagrams were created with LATEX. I find those explanations to be false, in view of my more general finding that the Bitcoin White Paper was not produced in LATEX. Other explanations (the indentations, the supposed ‘steganographic watermarking’ and formatting irregularities) are just a desperate attempt to explain away Dr Wright’s failure to be able to reproduce the Bitcoin White Paper in LATEX. The ‘non-linear’ working explanation (see [468.6] above) is ridiculous, in the light of all the other evidence which clearly indicates that this document was forged by Dr Wright. I so conclude. Continue Reading Here. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings.

This court case retrieved on January 29, 2024, judiciary.uk is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. COPA v. Wright, Court Filing, retrieved on January 29, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part of this filing here. This part is 26 of 42. COPA v. Wright, Court Filing, retrieved on January 29, 2024, is part of HackerNoon’s Legal PDF Series . You can jump to any part of this filing here . This part is 26 of 42. HackerNoon’s Legal PDF Series HackerNoon’s Legal PDF Series here here 24. Timecoin ODT Whitepaper (Reliance Document) {ID_000254} 446. The document purports to be a precursor draft of the Bitcoin White Paper and is presented as if written by Dr Wright. It is dated in the period 6 May 2008 to 12 December 2008 in its metadata, and Dr Wright states its approximate date to be 6 May 2008 in his Chain of Custody information. (a) COPA’s Reasons for Alleging Forgery (a) COPA’s Reasons for Alleging Forgery 447. The document has been backdated. Rather than being a precursor document to the Bitcoin White Paper as it purports to be, this document has been created from the Bitcoin White Paper subsequently and edited in such a way that it appears as if it was precursor work. [PM2 60-64]]. 448. {ID_000254} has apparently been converted from the Bitcoin White Paper (which is a PDF) into a more easily editable format and has then undergone further conversions via intermediate documents [PM2 [60-64]]. Font configurations and the absence of diagrams are consistent with this conclusion [PM2 [17-28]]. No such intermediate document has been disclosed. 449. Diagrams have been omitted from this document as a result of the conversion process from PDF. The inclusion of the object replacement character ￼ within the document [a point where a diagram would be expected to appear is consistent with {ID_000254} being created by a process of conversion of a different document. [PM2 [28]]. 450. Where diagrams are absent, the document nevertheless preserves margin indentations from the Bitcoin White Paper PDF, but which do not match the content of the document. [PM2 [29-37]]. 451. The document irregularly contains words throughout in which hyphens ought to appear but are missing. This is not consistent with ordinary dictation or typing error but is as an artefact of conversion from PDF and backdating. [PM2 [38-44]]. 452. A conversion of the Bitcoin White Paper PDF to editable form would result in corruption of formulae. In each case where those formulae would have appeared corrupted, they have been deleted from {ID_000254}, leaving behind white space. [PM2 [45-48]]. 453. The document contains irregular line breaks consistent with conversion from the Bitcoin White Paper PDF into editable form and backdating. [PM2 [49-51]]. 454. The document contains text that matches the corrected text of the Bitcoin White Paper (2009 version) [PM2 [12]]. It does not match the October 2008 or November 2008 versions of the Bitcoin White Paper, even though this document purports to be earlier than both of them. 455. The document has been disclosed with irregular metadata listed in relation to its Created and Last Accessed external metadata properties. [PM2 [6-11]]. (b) COPA’s Reasons for Inferring Dr Wright’s Knowledge / Responsibility (b) COPA’s Reasons for Inferring Dr Wright’s Knowledge / Responsibility 456. The effect of the tampering is to make the document appear to be supportive of Dr Wright’s claim to be Satoshi Nakamoto (presenting as a predecessor draft of the Bitcoin White Paper and supposedly written by him in early 2008), contrary to fact. Further, the document uses the same software (OpenOffice Writer) as used by Satoshi Nakamoto. 457. Dr Wright has positively asserted in these proceedings that this is a document on which he primarily relies as supporting his claim to be Satoshi Nakamoto. 458. The document bears Dr Wright’s name and contact details. 459. The contact details included refer to Charles Sturt University. In his evidence in these proceedings, Dr Wright has claimed to have drafted and shared versions of the Bitcoin White Paper while studying at Charles Sturt University, and to have discussed the concepts with teaching staff at Charles Sturt University. [Wright1 [87], Wright4 [52]]. 460. In his evidence in these proceedings, Dr Wright positively relies upon the presence of the word “Timecoin” in documents he has disclosed as being precursor work to the Bitcoin White Paper and thus forming part of the story behind his claim to be Satoshi Nakamoto. Moreover, on the basis of his narrative, this is a detail which would have been known to him and to few, if any, others. [Wright1 [26], Wright4 [6.c.x.]]. 461. The document contains metadata that purports to pre-date the Bitcoin White Paper, indicating efforts at backdating to support Dr Wright’s claim. 462. Dr Wright claims, in his chain of custody information, that only he drafted this document. 463. Dr Wright has stated in these proceedings that this was a draft of a document under the name TimeCoin which later became bitcoin. [Exhibit CSW-5] 464. Dr Wright has not disclosed the apparent intermediate document from which this document was created. [PM2 [63]]. (c) Dr Wright’s Explanations and COPA’s Rebuttal (c) Dr Wright’s Explanations and COPA’s Rebuttal 465. Dr Wright sought to explain away a number of the anomalous findings by saying that both this document and the Bitcoin White Paper were originally created in LATEX and that the commands in the original code accounted for such features as (a) the notes being in a font which was the same as would later be used for tables in the White Paper; (b) the OBJ character; (c) indentation in empty lines corresponding to the size of flowcharts later featuring in the Bitcoin White Paper; and (d) irregularities in hyphenation. See {CSW/2/26} to {CSW/2/28}; {Day3/139:21} to {Day3/152:8}. 466. Dr Wright sought to explain away the content of the document matching the March 2009 version of the Bitcoin White Paper rather than the earlier released versions by claiming that he does not “write things linearly”. He claimed to have used text in this early document, edited it out again in the August and October 2008 versions of the White Paper and then added it back in again for the March 2009 version. See {CSW/2/28} to {CSW/2/29}; {Day3/153:9} to {Day3/154:10}. 467. Dr Wright sought to explain away the irregular metadata by saying that his use of “Xcopy and related tools” somehow accounted for it: {CSW/2/28}. 468. COPA submitted that this explanation should be rejected as dishonest for the following reasons: 468.1. The Bitcoin White Paper was not originally created in LATEX, as convincingly established by the expert evidence of Mr Rosendahl (which was agreed by Dr Wright’s expert, Mr Lynch, in the joint statement). There is equally no basis for saying that this document was originally created in LATEX. Furthermore, no LAT EX.tex file has been provided to support Dr Wright’s account in relation to the creation of this document. 468.2. The use of LATEX to create the document would not account for the presence of the OBJ (object replacement) character, which on the expert evidence is purely and simply an artefact of conversion from PDF: see PM2 [26-28] {H/17/8}. 468.3. Neither would the use of LATEX to create the document account for Dr Wright having predicted in a precursor document precisely the size required for diagrams and having applied coding to mark out indentations for the diagrams in what would be empty space in the document. 468.4. Neither would the use of LATEX to create the document account for there being irregular hyphenation in precisely the points where line breaks appear in the text of the Bitcoin White Paper. Dr Wright could only weakly account for this as him doing “unusual things” and deliberately including irregular hyphenation {Day3/10:11}. This explanation was nonsensical. Further, it assumed that his deliberate inclusion of irregular hyphenation just happened by coincidence to fall in the places where line breaks existed in the Bitcoin White Paper. 468.5. Dr Wright’s explanation for the irregular metadata was at odds with the independent expert evidence. It also assumed that this irregularity happened by coincidence to co-exist with the other irregularities, when in fact all suggest backdating. 468.6. Dr Wright’s explanation for the content of the document including changes which were made to the Bitcoin White Paper between its 2008 and 2009 versions is inherently unlikely. It also assumes that this irregularity happened by coincidence to co-exist with all the other irregularities, when in fact all suggest backdating. (d) Conclusion (d) Conclusion 469. The explanations gathered in Appendix 1 to Dr Wright’s Closing confirm his reliance on both this document and the Bitcoin White Paper being based on earlier LATEX files and his allegation that the diagrams were created with LATEX. I find those explanations to be false, in view of my more general finding that the Bitcoin White Paper was not produced in LATEX. Other explanations (the indentations, the supposed ‘steganographic watermarking’ and formatting irregularities) are just a desperate attempt to explain away Dr Wright’s failure to be able to reproduce the Bitcoin White Paper in LATEX. The ‘non-linear’ working explanation (see [468.6] above) is ridiculous, in the light of all the other evidence which clearly indicates that this document was forged by Dr Wright. I so conclude. Continue Reading Here. Continue Reading Here . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on January 29, 2024, judiciary.uk is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on January 29, 2024, judiciary.uk is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. judiciary.uk judiciary.uk

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