Seven common mistakes crypto investors and traders make?


Cryptocurrency markets are volatile enough without making simple, easily avoidable mistakes.

Investing in cryptocurrencies and digital assets is now easier than ever before. Online brokers, centralized exchanges and even decentralized exchanges give investors the flexibility to buy and sell tokens without going through a traditional financial institution and the hefty fees and commissions that come along with them.

Cryptocurrencies were designed to operate in a decentralized manner. This means that while they’re an innovative avenue for global peer-to-peer value transfers, there are no trusted authorities involved that can guarantee the security of your assets. Your losses are your responsibility once you take your digital assets into custody.

Here we’ll explore some of the more common mistakes that cryptocurrency investors and traders make and how you can protect yourself from unnecessary losses.

Losing your keys

Cryptocurrencies are built on blockchain technology, a form of distributed ledger technology that offers high levels of security for digital assets without the need for a centralized custodian. However, this puts the onus of protection on asset holders, and storing the cryptographic keys to your digital asset wallet safely is an integral part of this.

On the blockchain, digital transactions are created and signed using private keys, which act as a unique identifier to prevent unauthorized access to your cryptocurrency wallet. Unlike a password or a PIN, you cannot reset or recover your keys if you lose them. This makes it extremely important to keep your keys safe and secure, as losing them would mean losing access to all digital assets stored in that wallet.

Lost keys are among the most common mistakes that crypto investors make. According to a report from Chainalysis, of the 18.5 million Bitcoin (BTC) mined so far, over 20% has been lost to forgotten or misplaced keys.

Storing coins in online wallets

Centralized cryptocurrency exchanges are probably the easiest way for investors to get their hands on some cryptocurrencies. However, these exchanges do not give you access to the wallets holding the tokens, instead offering you a service similar to banks. While the user technically owns the coins stored on the platform, they are still held by the exchange, leaving them vulnerable to attacks on the platform and putting them at risk.

There have been many documented attacks on high-profile cryptocurrency exchanges that have led to millions of dollars worth of cryptocurrency stolen from these platforms. The most secure option to protect your assets against such risk is to store your cryptocurrencies offline, withdrawing assets to either a software or hardware wallet after purchase.

Not keeping a hard copy of your seed phrase

To generate a private key for your crypto wallet, you will be prompted to write down a seed phrase consisting of up to 24 randomly generated words in a specific order. If you ever lose access to your wallet, this seed phrase can be used to generate your private keys and access your cryptocurrencies.

Keeping a hard copy record, such as a printed document or a piece of paper with the seed phrase written on it, can help prevent needless losses from damaged hardware wallets, faulty digital storage systems, and more. Just like losing your private keys, traders have lost many a coin to crashed computers and corrupted hard drives.

Fat-finger error

A fat-finger error is when an investor accidentally enters a trade order that isn’t what they intended. One misplaced zero can lead to significant losses, and mistyping even a single decimal place can have considerable ramifications.

One instance of this fat-finger error was when the DeversiFi platform erroneously paid out a $24-million fee. Another unforgettable tale was when a highly sought-after Bored Ape nonfungible token was accidentally sold for $3,000 instead of $300,000.

Sending to the wrong address

Investors should take extreme care while sending digital assets to another person or wallet, as there is no way to retrieve them if they are sent to the wrong address. This mistake often happens when the sender isn’t paying attention while entering the wallet address. Transactions on the blockchain are irreversible, and unlike a bank, there are no customer support lines to help with the situation.

This kind of error can be fatal to an investment portfolio. Still, in a positive turn of events, Tether, the firm behind the world’s most popular stablecoin, recovered and returned $1 million worth of Tether (USDT) to a group of crypto traders who sent the funds to the wrong decentralized finance platform in 2020. However, this story is a drop in the ocean of examples where things don’t work out so well. Hodlers should be careful while dealing with digital asset transactions and take time to enter the details. Once you make a mistake, there’s no going back.

Over diversification

Diversification is crucial to building a resilient cryptocurrency portfolio, especially with the high volatility levels in the space. However, with the sheer number of options out there and the predominant thirst for outsized gains, cryptocurrency investors often end up over-diversifying their portfolios, which can have immense consequences.

Over-diversification can lead to an investor holding a large number of heavily underperforming assets, leading to significant losses. It’s vital to only diversify into cryptocurrencies where the fundamental value is clear and to have a strong understanding of the different types of assets and how they will likely perform in various market conditions.

Not setting up a stop-loss arrangement

A stop-loss is an order type that enables investors to sell a security only when the market reaches a specific price. Investors use this to prevent losing more money than they are willing to, ensuring they at least make back their initial investment.

In several cases, investors have experienced huge losses because of incorrectly setting up their stop losses before asset prices dropped. However, it’s also important to remember that stop-loss orders aren’t perfect and can sometimes fail to trigger a sale in the event of a large, sudden crash.

That being said, the importance of setting up stop losses to protect investments cannot be understated and can significantly help mitigate losses during a market downturn.

Crypto investing and trading is a risky business with no guarantees of success. Like any other form of trading, patience, caution and understanding can go a long way. Blockchain places the responsibility on the investor, so it’s crucial to take the time to figure out the various aspects of the market and learn from past mistakes before putting your money at risk.

Source: https://bitcointalk.org/





Seven common mistakes crypto investors and traders make?


Cryptocurrency markets are volatile enough without making simple, easily avoidable mistakes.

Investing in cryptocurrencies and digital assets is now easier than ever before. Online brokers, centralized exchanges and even decentralized exchanges give investors the flexibility to buy and sell tokens without going through a traditional financial institution and the hefty fees and commissions that come along with them.

Cryptocurrencies were designed to operate in a decentralized manner. This means that while they’re an innovative avenue for global peer-to-peer value transfers, there are no trusted authorities involved that can guarantee the security of your assets. Your losses are your responsibility once you take your digital assets into custody.

Here we’ll explore some of the more common mistakes that cryptocurrency investors and traders make and how you can protect yourself from unnecessary losses.

Losing your keys

Cryptocurrencies are built on blockchain technology, a form of distributed ledger technology that offers high levels of security for digital assets without the need for a centralized custodian. However, this puts the onus of protection on asset holders, and storing the cryptographic keys to your digital asset wallet safely is an integral part of this.

On the blockchain, digital transactions are created and signed using private keys, which act as a unique identifier to prevent unauthorized access to your cryptocurrency wallet. Unlike a password or a PIN, you cannot reset or recover your keys if you lose them. This makes it extremely important to keep your keys safe and secure, as losing them would mean losing access to all digital assets stored in that wallet.

Lost keys are among the most common mistakes that crypto investors make. According to a report from Chainalysis, of the 18.5 million Bitcoin (BTC) mined so far, over 20% has been lost to forgotten or misplaced keys.

Storing coins in online wallets

Centralized cryptocurrency exchanges are probably the easiest way for investors to get their hands on some cryptocurrencies. However, these exchanges do not give you access to the wallets holding the tokens, instead offering you a service similar to banks. While the user technically owns the coins stored on the platform, they are still held by the exchange, leaving them vulnerable to attacks on the platform and putting them at risk.

There have been many documented attacks on high-profile cryptocurrency exchanges that have led to millions of dollars worth of cryptocurrency stolen from these platforms. The most secure option to protect your assets against such risk is to store your cryptocurrencies offline, withdrawing assets to either a software or hardware wallet after purchase.

Not keeping a hard copy of your seed phrase

To generate a private key for your crypto wallet, you will be prompted to write down a seed phrase consisting of up to 24 randomly generated words in a specific order. If you ever lose access to your wallet, this seed phrase can be used to generate your private keys and access your cryptocurrencies.

Keeping a hard copy record, such as a printed document or a piece of paper with the seed phrase written on it, can help prevent needless losses from damaged hardware wallets, faulty digital storage systems, and more. Just like losing your private keys, traders have lost many a coin to crashed computers and corrupted hard drives.

Fat-finger error

A fat-finger error is when an investor accidentally enters a trade order that isn’t what they intended. One misplaced zero can lead to significant losses, and mistyping even a single decimal place can have considerable ramifications.

One instance of this fat-finger error was when the DeversiFi platform erroneously paid out a $24-million fee. Another unforgettable tale was when a highly sought-after Bored Ape nonfungible token was accidentally sold for $3,000 instead of $300,000.

Sending to the wrong address

Investors should take extreme care while sending digital assets to another person or wallet, as there is no way to retrieve them if they are sent to the wrong address. This mistake often happens when the sender isn’t paying attention while entering the wallet address. Transactions on the blockchain are irreversible, and unlike a bank, there are no customer support lines to help with the situation.

This kind of error can be fatal to an investment portfolio. Still, in a positive turn of events, Tether, the firm behind the world’s most popular stablecoin, recovered and returned $1 million worth of Tether (USDT) to a group of crypto traders who sent the funds to the wrong decentralized finance platform in 2020. However, this story is a drop in the ocean of examples where things don’t work out so well. Hodlers should be careful while dealing with digital asset transactions and take time to enter the details. Once you make a mistake, there’s no going back.

Over diversification

Diversification is crucial to building a resilient cryptocurrency portfolio, especially with the high volatility levels in the space. However, with the sheer number of options out there and the predominant thirst for outsized gains, cryptocurrency investors often end up over-diversifying their portfolios, which can have immense consequences.

Over-diversification can lead to an investor holding a large number of heavily underperforming assets, leading to significant losses. It’s vital to only diversify into cryptocurrencies where the fundamental value is clear and to have a strong understanding of the different types of assets and how they will likely perform in various market conditions.

Not setting up a stop-loss arrangement

A stop-loss is an order type that enables investors to sell a security only when the market reaches a specific price. Investors use this to prevent losing more money than they are willing to, ensuring they at least make back their initial investment.

In several cases, investors have experienced huge losses because of incorrectly setting up their stop losses before asset prices dropped. However, it’s also important to remember that stop-loss orders aren’t perfect and can sometimes fail to trigger a sale in the event of a large, sudden crash.

That being said, the importance of setting up stop losses to protect investments cannot be understated and can significantly help mitigate losses during a market downturn.

Crypto investing and trading is a risky business with no guarantees of success. Like any other form of trading, patience, caution and understanding can go a long way. Blockchain places the responsibility on the investor, so it’s crucial to take the time to figure out the various aspects of the market and learn from past mistakes before putting your money at risk.

Source: https://bitcointalk.org/





Totalitarian Governments..

Totalitarianism is a form of government and political system that prohibits all opposition parties, outlaws individual opposition to the state and its claims, and exercises an extremely high degree of control and regulation over public and private life.

It is regarded as the most extreme and complete form of authoritarianism.

In totalitarian states, political power is often held by autocrats, such as  dictators  and absolute monarchs, who employ all-encompassing campaigns in which propaganda is broadcast by state-controlled mass media in order to control the citizenry.

It remains a useful word but the old 1950s theory was considered to be outdated by the 1980s,and is defunct among scholars.

The proposed concept gained prominent influence in Western anti-communist and McCarthyist political discourse during the Cold War era as a tool to convert pre-World War IIanti-fascism into post-war anti-communism.


Leaders who have been described as totalitarian rulers, from left to right and top to bottom in picture, include Joseph Stalin, former General Secretary of the Communist Party of the Soviet UnionAdolf Hitler, former Führer of Nazi GermanyAugusto Pinochet, former President of ChileMao Zedong, former Chairman of the Communist Party of ChinaBenito Mussolini, former Duce of Fascist Italy; and Kim Il-sung, the Eternal President of the Republic of North Korea

As a political ideology in itself, totalitarianism is a distinctly modernist  phenomenon, and it has very complex historical roots. Philosopher Karl Popper traced its roots to PlatoGeorg Wilhelm Friedrich Hegel‘s conception of the state, and the political philosophy of Karl Marx, although Popper’s conception of totalitarianism has been criticized in academia, and remains highly controversial.

Other philosophers and historians such as Theodor W. Adorno and Max Horkheimer trace the origin of totalitarian doctrines to the Age of Enlightenment, especially to the anthropocentrist idea that:

“Man has become the master of the world, a master unbound by any links to nature, society, and history.”

In the 20th century, the idea of absolute state power was first developed by Italian Fascists, and concurrently in Germany by a jurist and Nazi academic named Carl Schmitt during the Weimar Republic in the 1920s.

Benito Mussolini, the founder of Italian Fascism, defined fascism as such: “Everything within the state, nothing outside the state, nothing against the state.”

Schmitt used the term Totalstaat (lit. ’Total state’) in his influential 1927 work titled The Concept of the Political, which described the legal basis of an all-powerful state.

Totalitarian regimes are different from other authoritarian regimes, as the latter denotes a state in which the single power holder, usually an individual dictator, a committee, a military junta, or an otherwise small group of political elites, monopolizes political power.

A totalitarian regime may attempt to control virtually all aspects of social life, including the economy, the education system, arts, science, and the private lives and morals of citizens through the use of an elaborate ideology. It can also mobilize the whole population in pursuit of its goals.

Definition

Totalitarian regimes are often characterized by extreme political repression, to a greater extent than those of authoritarian regimes, under an undemocratic government, widespread personality cultism around the person or the group which is in power, absolute control over the economy, large-scale censorship and mass surveillance systems, limited or non-existent freedom of movement (the freedom to leave the country), and the widespread usage of state terrorism.

Other aspects of a totalitarian regime include the extensive use of internment camps, an omnipresent secret police, practices of religious persecution or racism, the imposition of theocratic rule or state atheism, the common use of death penalties and show trials, fraudulent elections (if they took place), the possible possession of weapons of mass destruction, a potential for state-sponsored mass murders and genocides, and the possibility of engaging in a war, or colonialism against other countries, which is often followed by annexation of their territories.

Historian Robert Conquest describes a totalitarian state as a state which recognizes no limit on its authority in any sphere of public or private life and extends that authority to whatever length it considers feasible.

Totalitarianism is contrasted with authoritarianism. According to Radu Cinpoes, an authoritarian state is “only concerned with political power, and as long as it is not contested it gives society a certain degree of liberty.”

Cinpoes writes that authoritarianism “does not attempt to change the world and human nature.”

In contrast, Richard Pipes stated that the officially proclaimed ideology “penetrating into the deepest reaches of societal structure, and the totalitarian government seeks to completely control the thoughts and actions of its citizens.”

Carl Joachim Friedrich wrote that “[a] totalist ideology, a party reinforced by a secret police, and monopolistic control of industrial mass society are the three features of totalitarian regimes that distinguish them from other autocracies.”



Visualization of the AES round function

Advanced Encryption Standard

The Advanced Encryption Standard (AES), also known by its original name Rijndael (Dutch pronunciation: [ˈrɛindaːl]), is a specification for the encryption of electronic data established by the U.S. National Institute of Standards and Technology (NIST) in 2001.

AES is a variant of the Rijndael block cipher developed by two  Belgian  cryptographers, Vincent Rijmen and Joan Daemen, who submitted a proposalto NIST during the AES selection process.

Rijndael is a family of ciphers with different key and block sizes. For AES, NIST selected three members of the Rijndael family, each with a block size of 128 bits, but three different key lengths: 128, 192 and 256 bits.

AES has been adopted by the U.S. government. It supersedes the Data Encryption Standard (DES), which was published in 1977.

The algorithm described by AES is a symmetric-key algorithm, meaning the same key is used for both encrypting and decrypting the data.

In the United States, AES was announced by the NIST as U.S. FIPS PUB 197 (FIPS 197) on November 26, 2001.

This announcement followed a five-year standardization process in which fifteen competing designs were presented and evaluated, before the Rijndael cipher was selected as the most suitable.

AES is included in the ISO/IEC 18033-3  standard. AES became effective as a U.S. federal government standard on May 26, 2002, after approval by the U.S. Secretary of Commerce.

AES is available in many different encryption packages, and is the first (and only) publicly accessible cipher approved by the U.S. National Security Agency (NSA) for top secret information when used in an NSA approved cryptographic module.



Andreas M. Antonopoulos (born 1972 in London) is a British-Greek Bitcoin advocate, tech entrepreneur, and author.

He is a host on the Speaking of Bitcoin podcast (formerly called Let’s Talk Bitcoin!) and a teaching fellow for the M.Sc. Digital Currencies at the University of Nicosia.

Antonopoulos was born in 1972 in London, UK, and moved to Athens, Greece during the Greek Junta.

He spent his childhood there, and at the age of 17 returned to the UK.

Antonopoulos obtained his degrees in Computer science and Data Communications, Networks and Distributed Systems from University College London.

Books


All Credit goes to Andreas M. Antonopoulos


Shared with 💚 & Admiration by Free Spirit

✌ & 💚


BitHouse with 💚


“THE FIAT STANDARD”




I am happy to share with you this chapter from my forthcoming book, The Fiat Standard, which will be out in November in hardcover, audio, and ebook formats.

Chapter 1: Introduction

On August 6, 1915, His Majesty’s Government issued this appeal:

“In view of the importance of strengthening the gold reserves of the country for exchange purposes, the Treasury has instructed the Post Office and all public departments charged with the duty of making cash payments to use notes instead of gold coins whenever possible.

The public generally are earnestly requested, in the national interest, to cooperate with the Treasury in this policy by

(1) paying in gold to the Post Office and to the Banks;

(2) asking for payment of cheques in notes rather than in gold;

(3) using notes rather than gold for payment of wages and cash disbursements generally”.

August 6th, 1915 – His Majesty’s Government

With this obscure and largely forgotten announcement, the Bank of England effectively began the global monetary system’s move away from a gold standard, in which all government and bank obligations were redeemable in physical gold.

At the time, gold coins and bars were still widely used worldwide, but they were of limited use for international trade, which necessitated resorting to the clearance mechanisms of international banks. 

Chief among all banks at the time, the Bank of England’s network spanned the globe, and its pound sterling had, for centuries, acquired the reputation of being as good as gold. 

Instead of the predictable and reliable stability naturally provided by gold, the new global monetary standard was built around government rules, hence its name. The Latin word fiat means ‘let it be done’ and, in English, has been adopted to mean a formal decree, authorization, or rule.

It is an apt term for the current monetary standard, as what distinguishes it most is that it substitutes government dictates for the judgment of the market.

Value on fiat’s base layer is not based on a freely traded physical commodity, but is instead dictated by authority, which can control its issuance, supply, clearance, and settlement, and even confiscate it at any time it sees fit.

With the move to fiat, peaceful exchange on the market no longer determined the value and choice of money. Instead, it was the victors of world wars and the gyrations of international geopolitics that would dictate the choice and value of the medium that constitutes one half of every market transaction.

While the 1915 Bank of England announcement, and others like it at the time, were assumed to be temporary emergency measures necessary to fight the Great War, today, more than a century later, the Bank of England is yet to resume the promised redemption of its notes in gold.

Temporary arrangements restricting note convertibility into gold have turned into the permanent financial infrastructure of the fiat system that took off over the next century.

Never again would the world’s predominant monetary systems be based on currencies fully redeemable in gold.

The above decree might be considered the equivalent of Satoshi Nakamoto’s email to the cryptography mailing list announcing Bitcoin, but unlike Nakamoto, His Majesty’s Government provided no software, white paper, nor any kind of technical specification as to how such a monetary system could be made practical and workable. Unlike the cold precision of Satoshi’s impersonal and dispassionate tone, His Majesty’s Government relied on appeal to authority, and emotional manipulation of its subjects’ sense of patriotism.

Whereas Satoshi was able to launch the Bitcoin network in operational form a few months after its initial announcement, it took two world wars, dozens of monetary conferences, multiple financial crises, and three generations of governments, bankers, and economists struggling to ultimately bring about a fully operable implementation of the fiat standard in 1971.

Fifty years after taking its final form, and one century after its genesis, an assessment of the fiat system is now both possible and necessary. Its longevity makes it unreasonable to keep dismissing the fiat system as an irredeemable fraud on the brink of collapse, as many of its detractors have done for decades. Many people at the end of their life today have never used anything but fiat money, and neither did their long-deceased parents. This cannot be written off as an unexplained fluke, and economists should be able to explain how this system functions and survives, despite its many obvious flaws.

There are, after all, plenty of markets around the world that are massively distorted by government interventions, but they nonetheless continue to survive. It is no endorsement of these interventions to attempt to explain how they persist.

It is also not appropriate to judge fiat systems based on the marketing material of their promoters and beneficiaries in government-financed academia and the popular press.

While the global fiat system so far avoided the complete collapse its detractors would predict, that cannot vindicate its promoters’ advertising of it as a free-lunch-maker with no opportunity cost or consequence. More than fifty episodes of hyperinflation have taken place around the world using fiat monetary systems in the past century. Moreover, the global fiat system avoiding catastrophic collapse is hardly enough to make the case for it as a positive technological, economic, and social development. 

Between the relentless propaganda of its enthusiasts and the rabid venom of its detractors, this book attempts to offer something new: an exploration of the fiat monetary system as a technology, from an engineering and functional perspective, outlining its purposes and common failure modes, and deriving the wider economic, political, and social implications of its use. I believe that adopting this approach to writing

The Bitcoin Standard contributed to making it the best-selling book on bitcoin to date, helping hundreds of thousands of readers across more than 20 languages understand the significance and implications of bitcoin. Rather than focus on the details of how bitcoin operates, I chose to focus on why it operates the way it does, and what the implications are. 

If you have read the Bitcoin Standard and enjoyed my exploration of bitcoin, I hope you will enjoy this exploration of the operation of fiat.

Perhaps counter-intuitively, I believe that by first understanding the operation of bitcoin, you can then better understand the equivalent operations in fiat.

It is easier to explain an abacus to a computer user than it is to explain a computer to an abacus user.

A more advanced technology performs its functions more productively and efficiently, allowing a clear exposition of the mechanisms of the simpler technology, and exposing its weaknesses.

For the reader who has become familiar with the operation of bitcoin, a good way to understand the operation of fiat is by drawing analogy to the operation of bitcoin using concepts like mining, nodes, balances, and proof of work.

My aim is to explain the operation and engineering structure of the fiat monetary system and how it operates, in reality, away from the naive romanticism of governments and banks who have benefited from this system for a century.

The first seven chapters of The Bitcoin Standard explained the history and function of money, and its importance to the economic order. With that foundation laid, the final three chapters introduced bitcoin, explained its operation, and elaborated on how its operation relates to the economic questions discussed in the earlier chapters.

My motivation as an author was to allow readers to understand how bitcoin operates and its monetary significance without requiring them to have a previous background in economics or digital currencies.

Had Bitcoin not been invented, the first seven chapters of The Bitcoin Standard could have served as an introduction to explaining the operation of the fiat monetary system.

This book picks up where Chapter 7 of “The Bitcoin Standard” left off. The first chapters of this book are modeled on the last three chapters of the Bitcoin Standard, except applied to fiat money. 

How does the fiat system actually function, in an operational sense? The success of bitcoin in operating as a bare-bones and standalone free market monetary system helps elucidate the properties and functions necessary to make a monetary system function.

Bitcoin was designed by a software engineer who boiled a monetary system down to its essentials. These choices were then validated by a free market of millions of people around the world who continue to use this system, and currently entrust it to hold more than $300 billion of their wealth.

The fiat monetary system, by contrast, has never been put on a free market for its users to pass the only judgment that matters on it. The all-too-frequent systemic collapses of the fiat monetary system are arguably the true market judgment emerging after suppression by governments.

With bitcoin showing us how an advanced monetary system can function entirely independently of government control, we can see clearly the properties required for a monetary system to operate on the free market, and in the process, better understand fiat’s modes of operation, and all-too-frequent modes of failure.

While fiat systems have not won acceptance on the free market, and though their failings and limitations are many, there is no denying the fact that many fiat systems have worked for large parts of the last century, and facilitated an unfathomably large number of transactions and trades all around the world. Its continued operation makes understanding it useful, particularly as we still live in a world that runs on fiat. Just because you may be done with fiat does not mean that fiat is done with you!

Understanding how the fiat standard works, and how it frequently fails, is essential knowledge for being able to navigate it.


This is a preview chapter from my forthcoming book, The Fiat Standard, which will be out in November in hardcover, audio, and ebook formats.

To begin, it’s important to understand that the fiat system was not a carefully, consciously, or deliberately designed financial operating system like bitcoin; rather, it evolved through a complex process of compromise between political constraints and expedience.

The next chapter illustrates this by examining newly-released historical documents on just how the fiat standard was born, and how it replaced the gold standard, beginning in England in the early twentieth century, completing the transition in 1971 across the Atlantic.

This is not a history book, however, and it will not attempt a full historical account of the development of the fiat standard over the past century, in the same way the Bitcoin Standard did not delve too deeply into the study of the historical development of the bitcoin software protocol. The focus of the first part of the book will be on the operation and function of the fiat monetary system, by making analogy to the operation of the bitcoin network, in what might be called a comparative study of the economics of different monetary engineering systems. 

Chapter 3 examines the underlying technology behind the fiat standard. Contrary to what the name suggests, modern fiat money is not conjured out of thin air through government fiat.

Government does not just print currency and hand it out to a society that accepts it as money. Modern fiat money is far more sophisticated and convoluted in its operation. The fundamental engineering feature of the fiat system is that it treats future promises of money as if they were as good as present money because the government guarantees these promises.

While such an arrangement would not survive in the free market, the coercion of the government can maintain it for a very long time. Government can meet any present financial obligations by diverting them onto future taxpayers or onto current fiat holders through taxes or inflation; and, further, through legal tender laws, the government can prevent any alternatives to its money from gaining traction.

By leveraging their monopoly on the legal use of violence to meet present financial obligations from potential future income, government fiat makes debt into money, forces its acceptance across society, and prevents it from collapsing.

Chapter 4 examines how the fiat network’s native tokens come into existence, using fiat’s antiquated and haphazard version of mining.

As fiat money is credit, credit creation in a fiat currency results in the creation of new money, which means that lending is the fiat version of mining.

Fiat miners are the financial institutions capable of generating fiat-based debt with guarantees from the government and/or central banks.

Unlike with bitcoin’s difficulty adjustment, fiat has no mechanisms for controlling issuance. Credit money, instead, causes constant cycles of expansion and contraction in the money supply with eventual devastating consequences, as this chapter examines.

Chapter 5 explains the topography of the fiat network, which is centered around its only full node, the US Federal Reserve.

The Fed is the only institution that can validate or refuse any transaction on any layer of the network.

Another 200 or so central bank nodes are spread around the world, and these have geographic monopolies on financial and monetary services, where they regulate and manage tens of thousands of commercial bank nodes worldwide.

Unlike with bitcoin, the incentive for running a fiat node is enormous.

Chapter 6 then analyzes balances on the fiat network, and how fiat has the unique feature where many, if not most, users, have negative account balances.

The enormous incentive to mine fiat by issuing debt means individuals, corporations, and governments all face a strong incentive to get into debt.

The monetization and universalization of debt is also a war on savings, and one which governments have persecuted stealthily and mostly quite successfully against their citizens over the last century.

Based on this analysis, Chapter 7 concludes the first section of the book by discussing the uses of fiat, and the problems it solves.

The two obvious uses of fiat are that it allows for the government to easily finance itself, and that it allows banks to engage in maturity-mismatching and fractional reserve banking while largely protected from the inevitable downside.

But the third use of fiat is the one that has been the most important to its survival: salability across space.

From the outset, I will make a confession to the reader. Attempting to think of the fiat monetary system in engineering terms and trying to understand the problem it solves have resulted in giving me an appreciation of its usefulness, and a less harsh assessment of the motives and circumstances which led to its emergence.

Understanding the problem this fiat system solves makes the move from the gold standard to the fiat standard appear less outlandish and insane than it had appeared to me while writing The Bitcoin Standard, as a hard money believer who could see nothing good or reasonable about the move to an easier money. 

Seeing that the analytical framework of “The Bitcoin Standard” was built around the concept of salability across time, and the ability of money to hold its value into the future, and the implications of that to society, the fiat standard initially appears as a deliberate nefarious conspiracy to destroy human civilization.

But writing this book, and thinking very hard about the operational reality of fiat, has brought into sharper focus the property of salability across space, and in the process, made the rationale for the emergence of the fiat standard clearer, and more comprehensible.

For all its many failings, there is no escaping the conclusion that the fiat standard was indeed a solution to a real and debilitating problem with the gold standard, namely its low spatial salability.

More than any conspiracy, the limited spatial salability of gold as global trade advanced allowed the survival of the fiat standard for so long, making its low temporal salability a tolerable problem, and allowing governments worldwide tremendous leeway to bribe their current citizens at the expense of their future citizens by creating the easy fiat tokens that operate their payment networks.

As we take stock of a whole century of operation for this monetary system, a sober and nuanced assessment can appreciate the significance of this solution for facilitating global trade, while also understanding how it has allowed the inflation that benefited governments at the expense of their future citizens.

Fiat may have been a huge step backward in terms of its salability across time, but it was a substantial leap forward in terms of salability across space.

Having laid out the mechanics for the operation of fiat in the first section, the book’s second section, Fiat Life, examines the economic, societal, and political implications of a society utilizing such a form of money with uncertain and usually poor inter-temporal salability.

This section focuses on analyzing the implications of two economic causal mechanisms of fiat money: the utilization of debt as money; and the ability of the government to grant this debt at essentially no cost.

Fiat increasingly divorces economic reward from economic productivity, and instead bases it on political allegiance. This attempted suspension of the concept of opportunity cost makes fiat a revolt against the natural order of the world, in which humans, and all other animals, have to struggle against scarcity every day of their lives.

Nature provides humans with reward only when their toil is successful, and similarly, markets only reward humans when they are able to produce something that others value subjectively.

After a century of economic value being assigned at the point of a gun, these indisputable realities of life are unknown to, or denied by, huge swathes of the world’s population who look to their government for their salvation and sustenance.

The suspension of the normal workings of scarcity through government dictat has enormous implications on individual time preference and decision-making, with important consequences to many facets of life.

In the second section of the book, we explore the impacts of fiat on family, food, education, science, health, fuels, and security. 

While the title of the book refers to fiat, this really is a book about bitcoin, and the first two sections build up the analytical foundation for the main course that is the third part of the book, examining the all-too-important question with which “The Bitcoin Standard” leaves the reader: what will the relationship between fiat and bitcoin be in the coming years?

Chapter 16 examines the specific properties of bitcoin that make it a potential solution to the problems of fiat.

While “The Bitcoin Standard” focused on bitcoin’s intertemporal salability, The Fiat Standard examines how bitcoin’s salability across space is the mechanism that makes it a more serious threat to fiat than gold and other physical monies with low spatial salability.

Bitcoin’s high salability across space allows us to monetize a hard asset itself, and not credit claims on it, as was the case with the gold standard.

At its most basic, bitcoin increases humanity’s capacity for long-distance international settlement by around 500,000 transactions a day, and completes that settlement in a few hours.

This is an enormous upgrade over gold’s capacity, and makes international settlement a far more open market, much harder to monopolize.

This also helps us understand bitcoin’s value proposition as not just in being harder than gold, but also in traveling much faster.

Bitcoin effectively combines gold’s salability across time with fiat’s salability across space in one apolitical immutable open source package.

By being a hard asset, bitcoin is also debt-free, and its creation does not incentivize the creation of debt. By offering finality of settlement every ten minutes, bitcoin also makes the use of credit money very difficult. At each block interval, the ownership of all bitcoins is confirmed by tens of thousands of nodes all over the world. There can be no authority whose fiat can make good a broken promise to deliver a bitcoin by a certain block time.

Financial institutions that engage in fractional reserve banking in a bitcoin economy will always be under the threat of a bank run as long as no institution exists that can conjure present bitcoin at significantly lower than the market rate, as governments are able to do with their fiat. 

Chapter 17 discusses bitcoin scaling in detail, and argues it will likely happen through second layer solutions which will be optimized for speed, high volume, and low cost, but involve trade-offs in security and liquidity.

Chapter 18 builds on this analysis to discuss what banking would look like under a Bitcoin Standard, while chapter 19 discusses how savings would work under such a system.

Chapter 20 studies bitcoin’s energy consumption, how it is related to bitcoin’s security, and how it can positively impact the market for energy worldwide.

With this foundation, the book can tackle the question: how can bitcoin rise in the world of fiat, and what are the implications for these two monetary standards coexisting?

Chapter 21 analyzes different scenarios in which bitcoin continues to grow and thrive, while Chapter 22 examines scenarios where bitcoin fails.

I hope you enjoyed this preview chapter from my forthcoming book, The Fiat Standard, which will be out in November in hardcover, audio, and ebook formats.



All the Credit goes to Saifedean Ammous


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Staking Vs. Yield Farming Vs. Liquidity Mining

staking-vs-yield-farming-vs-liquidity-mining

Staking Vs. Yield Farming Vs. Liquidity Mining – Key Differences

The DeFi space is growing, and there is no reason to deny it. Enterprises and individuals want to capitalize on the benefits of decentralized finance with the newly emerging solutions. Decentralized finance has not only opened up the possibilities for improved financial inclusion throughout the world but also strengthened the possibilities for using and managing digital assets.

The most notable factor which comes up in discussions about DeFi trading would refer to the staking vs. yield farming vs. liquidity mining differences.

All three of them are popular solutions in the domain of DeFi for obtaining plausible returns on crypto assets.

The three approaches differ in the way participants have to pledge their crypto assets in decentralized protocols or applications. 

In addition, the underlying technologies also provide further indications of differences between staking and the other two approaches.

Understanding Yield Farming

The first thing that you should take into account about yield farming is its definition. Yield generation is a popular approach for obtaining returns on crypto assets.

Basically, it offers a flexible approach for earning passive income through depositing crypto assets in a liquidity pool.

The liquidity pools in the case of yield farming could refer to bank accounts in the conventional sense.

Yield generation is the practice that involves investors locking in their crypto assets in liquidity pools based on smart contracts.

The assets locked in the liquidity pools are available for other users to borrow in the same protocol. 

Yield farming is a crucial aspect of the DeFi ecosystem as it supports the foundation of DeFi protocols for enabling exchange and lending services.

It is also essential for maintaining the liquidity of crypto assets on different decentralized exchanges or DEXs.

Yield farmers could also earn rewards in the form of APY. 

Working of Yield Generation

In order to develop a better impression of yield generation in staking vs. yield farming vs. liquidity mining, it is important to understand how to yield generation works. First of all, it is important to note that Automated Market Makers or AMMs are responsible for yield farming. 

AMMs are just smart contracts that leverage mathematical algorithms for enabling  digital asset trading.

Automated Market Makers play a highly critical role in yield farming for maintaining consistent liquidity as the transactions do not need any counterparties for the transaction.

You could find two distinct components in AMMs such as liquidity pools and liquidity providers. 

Liquidity pools are basically the smart contracts that drive the DeFi ecosystem. The pools include digital assets which can help users in purchasing, selling, borrowing, lending, and swapping tokens.

Liquidity providers are the users or investors who have locked their assets in the liquidity pool.

Yield farming also offers a plausible foundation for easier trading of tokens with low trading volume in the open market. 

Risks in Yield Farming

The understanding of staking vs. yield farming vs. liquidity mining can only get better with an awareness of risks with each.

It is important to note that yield generation offers high risk and high reward ventures for investment.

The notable risks with yield farming include impermanent loss, smart contract risk, composability risk, and liquidation risk.   

Understanding Staking

The second important entry in a debate on staking vs. yield farming vs. liquidity mining would obviously bring another notable and common consensus algorithm. Staking is basically an interesting way of pledging crypto assets as collateral in the case of blockchain networks leveraging the Proof-of-Stake algorithm. Just like miners use computational power for achieving consensus in Proof-of-Work blockchains, users with the highest stakes are selected for validating transactions on the PoS blockchains. 

Working of the Proof of Stake Consensus

You might be wondering about the potential rewards for staking your crypto assets in a PoS blockchain-based DeFi protocol. First of all, you are investing in a highly scalable blockchain consensus algorithm with staking, which also ensures improved energy efficiency. Proof-of-Stake algorithms also create new avenues of opportunities for earning rewards. 

With higher stakes in the protocol, investors could get better rewards from the network. It is important to note that rewards in the case of staking are allocated on-chain. Therefore, new tokens of the cryptocurrency are minted and distributed as staking rewards for the validation of each block. PoS blockchain does not imply the need for expensive computational equipment, thereby providing better usability. 

Risks in Staking

The risks associated with Proof-of-Stake protocols are also another highlight in discussions on staking vs. yield farming vs. liquidity mining.

Interestingly, the aspect of risk is considerably lower in the case of staking when compared to other approaches for passive investment. You should note that the safety of the staked tokens depends directly on the safety of the protocol. 

At the same time, you would still notice some prominent risks in staking cryptocurrencies, such as slashing, volatility risks, validator risks, and server risks. In addition, you might have to encounter issues of loss or theft of funds, waiting periods for rewards, project failure, liquidity risks, minimum holdings, and extended lock-up periods. 

Understanding Liquidity Mining

The final entry in the staking vs. yield farming vs. liquidity mining also deserves adequate attention when it comes to discussions on DeFi. As a matter of fact, liquidity mining serves as the core highlight in any DeFi project. Furthermore, it also focuses on offering improved liquidity in the DeFi protocols

Participants have to offer their crypto assets to liquidity pools in DeFi protocols for the purpose of crypto trading. However, it is important to note that participants do not offer crypto assets into liquidity pools for crypto lending and borrowing in the case of liquidity mining. Investors place their crypto assets in trading pairs such as ETH/USDT, and the protocol offers a Liquidity Provider or LP token to them. 

Working of Liquidity Mining

A deeper understanding of how liquidity mining works can help in anticipating its differences with the other strategies for crypto investment.

The investors would receive rewards from the protocol for the tokens they place in the liquidity pool.

The rewards in liquidity mining are in the form of native governance tokens, which are mined at every block. 

In addition, investors also have the LP token from the first stage of locking their crypto assets into the liquidity pool.

It is important to note that the reward in liquidity mining depends profoundly on the share in total pool liquidity.

Furthermore, the newly minted tokens could also offer access to governance of a project alongside prospects for exchanging to obtain other cryptocurrencies or better rewards. 

Risks in Liquidity Mining

The understanding of staking vs. yield farming vs. liquidity mining would be complete with an impression of their risks.

Just like the other two approaches, liquidity mining also presents some notable risks such as impermanent loss, smart contract risks, and project risks. In addition, liquidity miners are also vulnerable to the rug pull effect in their projects. 

Staking vs. Yield Farming vs. Liquidity Mining – Key Differences

Staking vs Yield Farming vs Liquidity Mining
Staking vs Yield Farming vs Liquidity Mining

The differences between the three players in staking vs. yield farming vs. liquidity mining would refer directly to some key pointers. Here are some of them outlined in brief for your understanding. 

Yield farming is a proven approach for investing your crypto assets in liquidity pools of protocols.

Staking involves locking your crypto assets in the protocol in return for privileges to validate transactions on the protocol.

Liquidity mining involves locking in crypto assets in protocols in return for governance privileges in the protocol.

In terms of objectives, yield farming aims to offer you the highest possible returns on the crypto assets of users. On the other hand, liquidity mining focuses on improving liquidity of a DeFi protocol. Furthermore, staking emphasizes maintaining the security of a blockchain network.

Bottom Line 

On a concluding note, it is quite clear that staking as well as yield generation and liquidity miners provide distinct approaches for investing crypto assets.

The growing attention towards crypto assets is undoubtedly opening up many new opportunities for investors.

However, investors need to understand the strategies they need to follow for the type of returns they are expecting. 

Therefore, a clear impression of staking vs. yield farming vs. liquidity mining  differences could help in making a plausible decision.

Yield generation, liquidity mining, and Proof-of-Stake blockchains also have some setbacks you should look for.

Start discovering more about yield farming and the other two crypto investment strategies now.


*Disclaimer: The article should not be taken as, and is not intended to provide any investment advice. Claims made in this article do not constitute investment advice and should not be taken as such. 101 Blockchains shall not be responsible for any loss sustained by any person who relies on this article. Do your own research!

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Smart Contracts Networks

Top upcoming Smart Contract Networks


Comparing the Top Upcoming Smart Contract Networks

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A Design For An Efficient Coordinated Financial Computing Platform

A Design For An Efficient Coordinated Financial Computing Platform

Jag Sidhu

Feb 25, 2021·41 min read

Abstract

Bitcoin was the first to attempt to offer a practical outcome in the General’s Dilemma using Crypto Economic rationale and incentives. Ethereum was the first to abstract the concept of Turing completeness within similar frameworks assumed by Bitcoin.

What Syscoin presents is a combination of both Bitcoin and Ethereum with intuitions built on top to achieve a more efficient financial computing platform which leverages coordination to achieve consensus using Crypto Economic rationale and incentives.

We propose a four-layer tech stack using Syscoin as the base (host) layer, which provides an efficient (ie, low gas cost per transaction) platform.

Some of the main advantages include building scalable decentralized applications, the introduction of a decentralized cost model around Ethereum Gas fees.

This new model proposes state-less parallelized execution and verification models while taking advantage of the security offered by the Bitcoin protocol. We may also refer to this as Web 3.0.

Table Of Contents

  • Abstract
  • Introduction
  • Syscoin Platform
  • Masternode Configuration
  • Chain Locks
  • Blockchain as a Computational Court
  • Scalability and Security
  • Efficiency
  • State Liveness and State Safety
  • Avoiding Re-execution of Transactions
  • Validity Proof Systems Overtop Proof-of-Work Systems
  • Quantum Resistance:
  • A Design Proposal for Web 3.0
  • Optimistic vs ZkRollup
  • Decentralized Cost Model
  • State-less Layer 1 Design
  • Related Works
  • Commercial Interests
  • Functional Overview
  • Give Me The Goods
  • Blockchain Foundry
  • Acknowledgements
  • References

Introduction

Syscoin is a cryptocurrency borrowing security and trust models of Bitcoin but with services on top which are conducive for businesses to build distributed applications through tokenization capabilities.

Syscoin has evolved since being introduced in 2013 where it offered a unique set of services through a coloured coin implementation on top of Bitcoin.

These services included aliases (identity), assets (tokens), offers (marketplace), escrow (multisig payments between aliases and marketplaces), and certificates (digital credentials).

In its current iteration, it has evolved to serve availability of consensus rather than data storage itself which requires some liveness guarantees better suited to systems like Filecoin and IPFS.

The recent iteration of Syscoin, version 4.0, streamlined the on-chain footprint to exclusively serve assets, a service which requires on-chain data availability for double-spend protection.

Ultimately, the only data that belongs on the blockchain are proofs that executions occurred (eg, coin transfers, smart contract executions, etc.) and information required to validate those proofs.

We introduced high-throughput payment rails for our asset infrastructure through an innovation we called Z-DAG [1]. This innovation offered real-time probabilistic guarantees of double-spend protection and ledger settlement for real-time point-of-sale. As a result, the token platform is one step closer to mass adoption by providing scalable infrastructure and speed that met or exceeded what was necessary to transact with digital tokens in real-life scenarios.

In addition, a two-way bridge to trustlessly interoperate with Ethereum. This enables Ethereum users to benefit from fast, cheap and secure transactions on Syscoin, and Syscoin users to leverage the Turing complete contract capabilities and ecosystem of Ethereum, all of which exclude custodians or third-parties.

Every decision we’ve made has been with security in mind. We believe that one of the biggest advantages of Syscoin is that it is merge-mined with Bitcoin.

Rather than expend more energy, Syscoin recycles the same energy spent by Bitcoin miners in order to solve blocks while being secured by the most powerful cryptocurrency mining network available.

With this energy efficiency we were able to reduce the subsidy to miners and increase subsidy to masternodes without raising the overall inflation; see Fig 1 for configuration.

Unlike Dashpay, these masternodes are not what you expect, as they have the specific job of running full nodes.

Fig 1: Masternode setup

Syscoin Platform

Today, Syscoin offers an asset protocol and deterministic validators as an enhancement on top of Bitcoin, as summarized below:

  • UTXO Assets
  • Compliance through Notary
  • Fungible and Non-Fungible tokens (Generic Asset infrastructure named SPT — Syscoin Platform Tokens)
  • Z-DAG for fast probabilistic onchain payments, working alongside payment channel systems like Lightning Networks
  • Deterministic validators (Masternodes) which run as Long-Living Quorums for distributed consensus decisions such as Chain Locks
  • Decentralized Governance, 10% of block subsidy is saved to pay out in a governance mechanism through a network wide vote via masternodes
  • Merged-mined with Bitcoin for shared work alongside Bitcoin miners

Masternode Configuration

With 2400+ masternodes running fullnodes, Z-DAG becomes much more dependable, as does the propagation of blocks and potential forks.

The masternodes are bonded through a loss-less strategy of putting 100000 Syscoin in an output and running full nodes in exchange for block rewards.

A seniority model incentivizes the masternodes to share long-term growth by paying them more for the longer period of service. Half of the transaction fees are also shared between the PoW miners and masternodes to ensure long term alignment once subsidy becomes negligible.

The coins are not locked at any point, and there is no slashing condition if masternodes decide to move their coins, the rewards to those masternodes simply stop.

Sharing Bitcoin’s compact block design, it consumes very little bandwidth to propagate blocks assuming the memory pool of all these nodes is roughly synchronized [2].

The traffic on the network primarily consists of propagating the missing transactions to validate these blocks. Having a baseline for a large number of full-nodes that are paid to be running allows us to create a very secure environment for users.

It proposes higher costs to would-be attackers who either have to attempt a 51% attack of Syscoin (effectively also trying to attack the Bitcoin network), or try to game the mesh network by propagating bad information which is made more difficult by incentivized full-nodes.

The health of a decentralized network consists of the following;

(a) the mining component or consensus to produce blocks, and

(b) the network topology to disseminate information in a timely manner in conditions where adversaries might be lurking.

Other attacks related to race conditions in networking or consensus code are mostly negligible as Syscoin follows a rigorous and thorough continuous development process.

This includes deterministic builds, Fuzz tests, ASAN/MSAN/TSAN, functional/unit tests, multiple clients and adequate code coverage.

Syscoin and Bitcoin protocol code bases are merged daily such that the build/signing/test processes are all identical, allowing us to leverage the massive developer base of Bitcoin.

The quality of code is reflective of taking worst case situations into account. The most critical engineers and IT specialists need confidence that value is secure should they decide to move their business to that infrastructure.

It’s true that there are numerous new ideas, new consensus protocols and mechanisms for achieving synchronization among users in a system through light/full node implementations.

However, in our experience in the blockchain industry over the last 8 years, we understand that it takes years, sometimes generations to bring those functionalities to production level quality useful for commercial applications.

Chain Locks

With a subset of nodes offering sybil resistance through the requirement of bonding 100,000 SYS to become active, plus the upcoming deterministic masternode feature in Syscoin 4.2, we have enabled Chain Locks which attempts to solve a long-standing security problem in Bitcoin [3], where Dashcore was the first project to implement this idea [4] which the industry has since widely accepted as a viable solution [5].

Our implementation is an optimized version of this, in that we do not implement Instant Send or Private Send transactions and thus Syscoin’s Chain Lock implementation is much simpler.

Because of merged-mining functionality with Bitcoin, we believe our chain coupled with Chain Locks becomes the most secure via solving Bitcoin’s most vulnerable attack vector, selfish mining.

These Chain Locks are made part of Long-Living Quorums (LLMQ) which leverage aggregatable Boneh–Lynn–Shacham (BLS) signatures that have the property of being able to combine multiple signers in a Distributed Key Generation (DKG) event to sign on decisions. In this setup, a signature can be signed on a group of parties under threshold constraints without any one of those parties holding the private key associated with that signature. In our case, the signed messages would be a ChainLock Signature (CLSIG) which represent claims on what the block hashes represent of the canonical chain [4].

This model suggests a very efficient threshold signature design was needed to be able to quickly come to consensus across the Masternode layer to decide on chain tips and lock chains preventing selfish mining attacks. See [6] to understand the qualities of BLS signatures in the context of multi-sig use cases.

Ethereum 2.0 design centers around the use of BLS signatures through adding precompile opcodes in the Ethereum Virtual Machine (EVM) for the BLS12–381 curve [7] which Syscoin has adopted.

This curve was first introduced in 2017 by Bowe [8] to the ZCash protocol. Masternodes on Syscoin use this curve and have a BLS key that is associated with each validator. There is the performance comparison to ECDSA (Secp256k1) [9] that shows its usefulness in contrast to what Bitcoin and Syscoin natively use for signature verification.

Blockchain as a Computational Court

A computational court is a way of enforcing code execution on the blockchain’s state. This was first introduced by de la Rouvier [10].

Since the inception of  Syscoin  and  Blockchain Foundry we have subscribed to the idea that the blockchain should be used as a court system rather than a transaction processor.

This debate has stemmed from the block size debate in the Bitcoin community [11]. However, with recent revelations in cryptography surrounding Zero-Knowledge Proofs (ZKP) [12] and particularly Zero-Knowledge Succinct Non-Interactive Argument of Knowledge (zk-STARK) [13], we propose a secure ledger strategy using the Bitcoin protocol as a court (ie, host layer), an EVM or eWASM (ie, operating system layer), computational scaling through ZKP (ie, SDK layer) and business verticals (ie, application layer); see Fig 2

Fig 2: Four-layer tech stack

Scalability and Security

Scalability in blockchain environments is typically measured by Total Transactions per Second (TPS).

This means full trustlessness, decentralization and liveness properties as evidenced by something like Bitcoin.

If trade-offs are made to achieve higher scale it means another property is affected.

A full node is one that creates blocks and/or fully validates every block of transactions.

For the purpose of this discussion, we will refrain on expounding on designs where light-clients are used to give semblance of higher throughput, etc.

However, if two nodes are running the same hardware and doing the same work, the one that provides more TPS performance than the other is considered more scalable. This is not to be confused with throughput which is the measure of output that can be increased by simply adding more hardware resources. Hence, more throughput does not mean more scalable.

Some blockchains require the producers of blocks to run on higher specifications, offering higher throughput but not necessarily more scale.

However, there are projects which employ parallel processing to try to achieve higher scale whilst also enforcing more capable hardware to provide a more efficient overall system [33].

As a logical experiment, the throughput of a system divided by the scalability of the system is what we define as efficiency.

In the following sections, we will outline our proposal for improved efficiency.

Efficiency

The holy grail of blockchain design resides in the ability to have a ledger that can claim to be sublinear while retaining consistency, fault tolerance and full availability (ie, CAP Theorem).

This means there are roughly constant costs for an arbitrary amount of computation performed and being secured by that ledger.

This has always been thought of as impossible and it mostly is unless acceptable trade-offs appear in application designs and they are easy to understand and work around.

Most experts make the assumption that an O(1) ledger is simply impossible and thus design blockchains and force applications to work in certain ways as a result.

We will remove such assumptions and let business processes dictate how they work by giving the ability to achieve O(logk n) for some constant k (ie, polylogarithmic) efficiency with trade-offs.

A polylogarithmic design would give the ability for almost infinite scaling over time for all intents and purposes.

The only bottlenecks would be how fast information can be propagated across the network which would improve over time as telecom infrastructure naturally evolves and increases in both capability and affordability.

Put in context, even Lightning Networks for transactional counts qualifies as a form of sublinear scaling on a transactional basis but not per user, as users must necessarily enter the main chain first before entering a payment channel.

It requires the state of the blockchain to include the users joining the system.

This state (the UTXO balances) is the single biggest factor of efficiency degradation in Bitcoin.

Users need to first start on the main chain and then move into the payment channel system to receive money, meaning that scale is at best O (N) where N is the number of users.

There are some solutions to this problem of state storage on Bitcoin by reducing it via an alternative accumulator strategy to the cost of increased bandwidth [14].

This approach would make the chain state-less, however the validation costs would remain linear to the number of transactions being done. When combined with payment channels, only the costs to get in/out are factored into the validation and this offers an interesting design for payments themselves while providing for on-chain availability.

We consider this as a good path for futuristic scalable payments.

Hence, it is not possible to employ that strategy with general computations. With this design, we are still left with the issue on how to do general computations at higher efficiency.

What we present is the ability to have a polylogarithmic chain at the cost of availability for both payments and general computations where business processes dictate availability policies, and users fully understand these limitations when using such systems.

Users may also be provided the ability to ensure availability for themselves and others at their discretion. This will be expounded upon in the following sections.

State Liveness and State Safety

While many compelling arguments can be made migrating to a state-less design [15], it is not possible to achieve sublinear efficiency without sacrificing some other desired component that we outlined above.

To achieve polylogarithmic efficiency it’s necessary to have a mix of state and stateless nodes working together in harmony on a shared ledger [15].

This should be accomplished in such a way that business processes can dictate direction, and users can choose to pay a little more for security either by using a stateful yet very scalable ledgering mechanism or by paying to ensure their own data availability amortized over the life of that user on such systems.

Presenting the ability for users to make these choices allows us to separate the consensus of such systems and reduce overall complexity.

However, in whatever solution we adopt , we need to ensure that the final implementation allow for both the liveness and safety of that state, which are defined as follows:

State Liveness — Transferring coins in a timely manner

State Safety — Private custody

It is important to adhere to these concepts; if one cannot move one’s coins, then it is as useful as if one burned their coins. Hence, if we had third party custody in place, this would give rise to custodial solutions, and lose decentralized and trustless aspects of the solution, which again is not desired.

The options as described would allow users to decide their state liveliness at their own discretion, while state safety is a required constraint throughout any system design we provide. The doorway to possibilities of sublinear design is opened by giving users the ability to decide.

Avoiding Re-execution of Transactions

In order to scale arbitrarily, independent of the number of transactions — a desired property of increasing throughput — one requires a mechanism to avoid re-executing transactions.

Further, ideally it would be able to batch these transactions together for a two-fold scaling proposition.

There are a few mechanisms in literature that attempted to solve re-execution:

(a) TrueBit; (b) Plasma; and © Arbitrum avoided re-execution.

Unfortunately, they require challenge response systems to ensure security, which leads to intricate attack vectors of unbounded risk/reward scenarios.

Multi-Party Computation (MPC) is a mechanism to have parties act under a threshold to decide on actions such as computational integrity of a smart contract. MPC is used in Syscoin for BLS threshold signatures for Chain Locks and Proof-of-Service in quorums of validators deterministically chosen using Fiat-Shamir heuristics on recent block hashes.

The problem with this approach is that validators may become corrupt, hence need to be wrapped in a consensus system along with DKG and random deterministic selection. This was an interesting topic of discovery for the Syscoin team early-on as a way to potentially scale smart contract execution but was ultimately discarded due to the incentive for risk/reward scenarios to favour attacks as the value of the transactions increases.

Hardware enclaves (eg, Intel SGX through remote attestation) were also of particular interest to the Syscoin team as a way to offload execution and avoid re-execution costs.

However, there are a myriad of attack vectors and censorship concerns on the Intel platform . We also should note that the Antarctica model was interesting but required a firmware update from Intel to support such a feature which raises concerns over censorship long term.

The theme amongst all of these approaches is that although re-execution is avoided the communication complexity is largely still linear with the number of transactions on the main chain. The security and trust models are also different from that of the layer 1 assumptions which was not desired.
Lacking solvent solutions to avoid re-execution and enable sublinear overall complexity, we were led — in the development of Syscoin 4.0 — to build a trust-minimized two-way bridge between Syscoin and the Ethereum mainchain, offloading the concerns around smart contracts to Ethereum.

With the advent of such promising technology as ZKP and the optimizations happening around them, we have re-considered the possibilities and believe this will play an important role in the development of Web 3.0. This mathematical breakthrough led us to re-test our assumptions and options related to our desired design.

ZKP allows us the desired superlinear scaling trait we had been looking to achieve but they also offer other benefits; namely privacy is very easy to introduce and will not add detectable costs and complexities to verification on the mainchain.

With users controlling their own data, the mainchain and systems may be designed such that only balance adjustments are recorded, not transaction sets (we will explain the case with full data availability below). In this scenario there is no advantage for a miner to gain to be able to collude with users to launch attacks on systems such as Decentralize Finance (DeFi) pools and provenance of transactions.

The flexibility has to be there though for application developers that need experiences consistent with those we have today with Bitcoin/Syscoin/Ethereum, and to enable the privacy use-cases without requiring extra work, knowledge or costs.

Fig 3: Host and EVM layer

Validity Proof Systems Overtop Proof-of-Work Systems

Prior to the use of Proof Systems, the only option for “Validity Proofs” in a permissionless system involved naive replay, and as such greatly limited scalability; in essence this replay is what is still done today in Layer-1 blockchain (L1) solutions, with the known penalty to scalability.

Proof Systems offer a very appealing trait known as succinctness: in order to validate a state transition, one needs to only verify a proof, and this is done at a cost that is effectively independent of the size of the state transition (ie, polylogarithmic in the size of the state transition).

For maximal financial security, the amount of value being stored should depend on the amount of security provided on the settlement side of the ledger.

Proof-of-Work offers the highest amount of security guarantees. Our next generation financial systems begin with optimal ledgering security and add proof systems on top for scaling. Block times are not as important in a world where most users and activity are on Layer-2 blockchain (L2) validity proof based systems.

This liberates engineers who are focused on scalability to define blocks better; safe block times plus the maximal amount of data bandwidth that can be safely propagated in a time sensitive manner across full nodes in the network.

In Syscoin there are incentivized full nodes (ie, deterministic masternodes), so again we can maximize the bandwidth of ledgering capabilities while retaining Bitcoin Proof-of-Work (PoW) security through merged-mining.

Quantum Resistance:

Table 1: Estimates of quantum resilience for current cryptosystems (see [20])

As seen in Table 1, hashing with the SHA256 algorithm is regarded to be quantum safe because it requires Grover’s algorithm to crack in the post-quantum world, and at best the quantum computer will offer only 50% reduction in time to break.

On the other hand, where Shor’s algorithm applies, any pair based cryptographic system will be broken in hours.

For L2, we propose to implement ZKP in the SDK Layer (see Fig 2); namely Non-Interactive Zero Knowledge Proofs (NIZKP).

Popular implementations of NIZKP include Zero-Knowledge Succinct Non-interactive ARgument of Knowledge (zk-SNARKS) and Zero-Knowledge Scalable Transparent ARguments of Knowledge (zk-STARKS).

There are some zk-STARK/zk-SNARK friendly cipher’s employed in zkRollup designs such as MiMC and Pederson hashes for which we lack certainty on classical security, yet are hopeful and would offer quantum resistance within ZKPs.

It is important to note that Bitcoin was developed with change addresses in mind exposing the hash of a public key requires a quantum computer to use Grover’s Algorithm in order to attempt stealing that Bitcoin. Each time a Bitcoin Unspent Transaction Output (UTXO) is spent, the public key is exposed and a new change address — which does not expose the public key — is used as change.

With this in mind, any scalable L2 solution should be quantum resistant because otherwise we undermine Bitcoin design as the gold standard of security.

Fig 4: zkSync Rollup design

A Design Proposal for Web 3.0

The following describes the 4-layers (see Fig 2) of Syscoin’s proposed tech stack for Web 3.0:

[Host Layer] Bitcoin’s design is the gold standard for security and decentralization.

Proof-of-work and Nakamoto Consensus settlement security are widely regarded by academics as the most hardened solution for ledgering value.

It’s possible this may change, however it’s also arguable that the intricate design encompassing Game Theory, Economics, risk reward ratios for attack, and the minimal amounts of compromising attack vectors is likely not to change for the foreseeable future.

UTXO’s (and payments with them) are more efficient than account-based or EVM-based. That said, Bitcoin itself suffers from not being expressive enough to build abstraction for general computation.

[Operating System Layer]

EVM/eWASM is the gold standard for general computation because of its wide adoption in the community.

Anyone building smart contracts are likely using this model or will continue to use it as the standard for autonomous general computation with consensus.

[SDK Layer]

Zero-knowledge proofs are the gold standard for generalized computation scaling for blockchain applications. They enable one-time execution via a prover and enable aggregate proof checking instead of re-execution of complex transactions.

zk-STARKs or zk-SNARKs using collision resistant hash functions that work with only weak cryptographic assumptions and therefore are quantum safe.

At the moment generalized smart contracts are not there yet but we are quickly approaching the day (eg, Cairo, Zinc) when there will be abstractions made to have most Solidity code trans-compile into a native zero-knowledge aware compiler similar to how .NET runtime and C# allows an abstraction on top of C/C++ as an interpretive layer on top

[Application Layer]

Verticals or applications applying the above SDK to define business goals.

Surprisingly, these ideals represent a design that is not shared with any other project in the industry, including Bitcoin or Ethereum.

We feel these ideals, fashioned together in a singular protocol, could possibly present a grand vision for a “World Computer” blockchain infrastructure.

Syscoin has already implemented Geth + Syscoin nodes in one application instance already (ie, release 4.2), we foresee that it will not prove too challenging to have them cooperate on a consensus basis working together to form a dual chain secured by Syscoin’s PoW.

Fig 5: Proposed design

Fig 5 describes a system where nodes are running two sets of software processes, the Syscoin chain protocol and an EVM/eWASM chain protocol which are kept in sync through putting the EVM tip hash into the Syscoin block. Both have their own individual mempools and effectively the Ethereum contracts, tools and processes can directly integrate as is into the EVM chain as it stands.

Note that the two chains are processes running on the same computer together. Thus a SYS NODE and EVM NODE would be operating together on one machine instance (ie, Masternode) with ability to communicate with each other directly through Interprocess Communication (IPC).

The intersection between the two processes happens in three points:

Miner of the EVM chain collects the latest block hash and places it into the Syscoin block.

When validating Syscoin blocks, nodes confirm the validity of the EVM tip by consulting the EVM chain software locally.

Fees for the EVM chain are to be paid in SYS. We need an asset representing SYS on the EVM chain, which will be SYSX.

We will enable this through a similar working concept that we’ve already established (SysEthereum Bridge).

We may also enable pre-compiles on the EVM chain side to extract Syscoin block hashes and merkle roots to confirm validity of SYS to SYSX burn transactions.

This design separates concerns by not complicating the PoW chain with EVM execution information, keeping the processes separate yet operating within the same node.

To further delineate point 1 (see above), a miner would mine both chains. With Syscoin being merged-mined, the work spent on Bitcoin would be shared to create a Syscoin block that includes the EVM chain within it as a ledgering event representing the latest smart contract execution state (composed of Chain Hash, State Root, Receipt Root, and Transaction Trie Root).

Since the EVM chain has no consensus attached, technically a block can be created at any point in time. Creation of Syscoin and EVM blocks will be near simultaneous, and occur every one minute on average.

Fig 6: Merge mining on Syscoin

As seen in Fig 6, work done on BTC is reused to create SYS blocks through the  merged-mining specification. Concurrently, the miner will execute smart contracts in the memory pool of the node running the EVM chain. Once a chain hash has been established post-execution, it will be put into the coinbase of the Syscoin block and published to the network. Upon receiving these blocks, every node would verify that the EVM chain which they would locally execute (ie, similar to the miner) matches the state described by the Syscoin block.

Technically, one would want to ensure both the latest and previous EVM block hashes inside of their respective Syscoin blocks are valid.

The block->evmblock == evmblock && block->prev == evmblock->prev is all that is needed to link the chains together with work done by Bitcoin which is propagated to Syscoin through AUXPOW and can serve as a secure ledgering mechanism for the EVM chain.

Since (a) we may use eWASM; (b) there are paid full nodes running on the network; and © the mining costs are shared with Bitcoin miners, we should be able to safely increase the amount of bandwidth available in the EVM chain while remaining secure from large uncle orphan rates.

There has been much discussion as to what the safe block size should be on Ethereum. Gas limits are increasing as optimizations are made on the Ethereum network.

However, since this network would be ledgered by the Syscoin chain through PoW, there would be no concern for uncle orphaning of blocks since the blocks must adhere to the policy set inside of the Syscoin block. We should therefore be able to increase bandwidth significantly and parameterize for a system that will scale globally yet still be centered around L2 rollup designs.

A very important distinction here is that the design of Ethereum 2.0 centers around a Beacon chain and sharding served by a Casper consensus algorithm. The needs of the algorithm require a set of finality guarantees necessitating a move towards Proof-of-Stake (PoS).1

This has large security implications for which we may not have formal analysis for a long time, however we do know it comes with big risk.

We offer similar levels of scalability on a network while retaining Nakamoto Consensus security. The simpler design which has been market tested and academically verified to work would lead to a more efficient system as a whole with less unknown and undocumented attack vectors.

The only research that would need to be made therefore is on the optimal parameterization of the gas limit taking into account an L2 centric system but also a safe number of users we expect to be able to serve before fee market mechanisms begin to regulate the barrier of entry for these users.

This proposed system should be scalable enough to serve the needs of global generalized computation while sticking to the core fundamentals set forth in the design ideals above. Our upcoming whitepaper will have more analysis on these numbers but we include some theoretical scaling metrics at the end of this article.

Optimistic vs ZkRollup

ZKP are excellent for complex calculations above and beyond simple balance transfers. For payments, we feel UTXO payment channels combined with something like Z-DAG is an optimal solution.

However, we are left with rollup solutions for generalized computation involving more complex calculations requiring consensus.

Whatever solution we adopt has to be secured by L1 consensus that is considered decentralized and secure, which we achieve via merged-mining with Bitcoin.

There are two types of rollup solutions today:

(a) Optimistic roll ups (OR); and (b) zkRollups; which offer trade-offs.

Consensus about which chain or network you’re on is a really hard problem that is solved for us by Nakamoto consensus. We build on that secure longest chain rule (supplemented by Chain Locks to prevent selfish mining) to give us the world-view of the rollup states. The executions themselves can be done once by a market of provers, never to be re-executed, only verified, meaning it becomes an almost constant cost on an arbitrarily large number of executions batched together. With OR you have the same world-view but the world-view is editable without verifying executions. The role of determining the validity of that world-view is delegated to someone watching who provides guarantees through crypto-economics. Zero-knowledge proofs remove crypto-economics on execution guarantees and replace them with cryptography.

See [26] to see  between fraud proofs (optimistic) vs validity proofs (zk)

Key takeaways from this article are as follows

  • Eliminate a nasty tail risk: theft of funds from OR via intricate yet viable attack vectors;
  • Reduce withdrawal times from 1–2 weeks to a few minutes;
  • Enable fast tx confirmations and exits in practically unlimited volumes;
  • Introduce privacy by default.

One point missing is interoperability. A generalized form of cross-chain bridging can be seen in Chain A locking tokens based on a preimage commitment by Chain B to create a zero-knowledge proof, followed by verification of that proof as the basis for manifesting equivalence on Chain B. Any blockchain with the functionality to verify these proofs could participate in the ecosystem.

Our vision here is described using a zkRollup centric world-view, yet it can be replaced with other technologies should they be able to serve the same purpose. As an infrastructure we are not enforcing one or the other; developers can build on what they feel best suits their needs. We believe we are close to achieving this, and that the technology is nearing the point of being ready for the vision set forth in this article.

Decentralized Cost Model

Decentralized cost models lead to exponential efficiency gains in economies of scale. We set forth a more efficient design paradigm for execution models reflective of user intent. This design uses the UTXO model to reflect simple state transitions and a ZKP system for complex computations leading to state transitions. This leads to better scalability for a system by allowing people to actively make their trade-off within the same ecosystem, driven by the same miners securing that ecosystem backed by Bitcoin itself.

Furthermore, a decentralized cost model contributes to scalability in that ZKP gates can generalize complex computation better than fee-market resources like gas or the CPU/memory markets of EOS, etc.

This leads to better scalability for a system by allowing people to actively make their trade-off within the same ecosystem, driven by the same miners securing that ecosystem backed by Bitcoin itself.

Furthermore, a decentralized cost model contributes to scalability in that ZKP gates can generalize complex computation better than fee-market resources like gas or the CPU/memory markets of EOS, etc. This leads to more deterministic and efficient consumption of resources maximizing efficiency in calculations, and gives opportunity for those to scale up or down based on economic incentives without creating monopolistic opportunities unlike ASIC mining.

In other words, the cost is dictated by what the market can offer, via the cost of compute power (as dictated by Moore’s law), rather than the constrained costs of doing business on the blockchain itself.

This model could let the computing market dictate the price for Gas instead of being managed by miners of the blockchain. The miners would essentially only dictate the costs of the verification of these proofs when they enter the chain rather than the executions themselves.

 happening with ZKP and with a decentralized cost model it will be much easier to understand costs of running prover services as well as know how the costs scale based on the number of users and parameters of systems that businesses would like to employ. All things considered, it will be easier to make accurate decisions on data availability policies and the consensus systems needed to keep the system censorship resistant and secure.

Rollups will be friends, that is, users of one rollup system doing X TPS and users of another doing Y TPS, with the same trust model, will in effect get us to global rates of X*Y (where X is TPS of the sidechains/rollups and Y is the number of sidechains and rollups that exist). X is fairly static in that the execution models of rollups do not change drastically (and if they do, the majority of those rollup or sidechain designs end up switching to the most efficient design for execution over time).

State-less Layer 1 Design

The single biggest limiting factor of throughput in blockchains is  and access to the global state.

More specifically, in Bitcoin it is the UTXO set, and in Ethereum it is the Account Storage and World State tries. State lookups typically require SSD in Ethereum full nodes because real-time processing of transactions of block arrivals are critical to reaching consensus, this is especially the case for newly arriving blocks (ie, every 10–15 seconds).

As state and storage costs rise, the number of full verifying nodes decreases due to the resource consumption of fully validating nodes and providing timely responses to peers. Consequently, network health suffers due to the risks of centralization of consensus amongst the subset peers running full nodes.

State-less designs are an obvious preference to solve problems using alternative mechanisms to validate the chain without requiring continuous updates to the global state.

In a rollup, smart contracts on L1 do not access the global state unless entering or exiting a rollup. Therefore smart contracts that provide full data availability on-chain (ie, zkRollup), would only require state updates to the local set of users within that L2. Under designs where data availability is kept off-chain, there is no state update on L1, unless entering and exiting.

Therefore, it classifies as purely state-less, whereas in zkRollup mode we can consider this partially state-less. Since these L1 contracts are state-less to the global state, nodes on the network can parallelize verification of any executions to the contracts which do not involve entering or exiting. This is in addition to the organic and natural parallel executions of transactions that are composing these rollup aggregated transactions posted on L1.

State-less layer 1 designs also allow for parallelizable smart contract execution verification. The parallelization of smart contracts running on L1 in the EVM model is a recent topic of research that  which involves defining “intent” for the execution of a contract (because nodes do not know ahead of time what the smart contract execution will entail in terms of accessing global state).

Adding in the intent of a transaction as supplied as part of the commitment of that transaction would allow nodes to reject if the execution of that contract did not correspond with the intent, possibly costing the user fees for invalid commitments.

Although these designs may be flexible, they come at the cost of additional complexity through sorting, filtering and general logic that may be susceptible to intricate attacks.

In our case, the transaction can include a field that is understood by the EVM to denote if it is intending to use global state in any way (for rollups typically this would be false) then we can simply reject any access to global states for those specific types of executions.

This would allow nodes to execute these specific types of transactions in parallel knowing that no global state is allowed to access executions. If a transaction is rejected due to incorrectly setting this field the fees are still spent to prevent users from purposefully setting this field incorrectly.

Related Works

The following organizations offer various open source third party L2 scaling solutions:

Starkware is built using a general purpose language (Cairo) with Solidity (EVM) in mind, as is Matter labs with the (Zinc) language. Hermez developed custom circuits tailor-suited to fast transactions and Decentralized Exchange (DEX) like capability. These will be able to directly integrate into Syscoin without modification.

As such, the optimizations and improvements they make should directly be portable to Syscoin, hence becoming partners to our ecosystem.

Aleo uses Zero knowledge EXEcution (Zexe) for zkSNARK proof creation through circuits created from R1CS constraints. The interesting thing about Aleo is that there is a ledger itself that is purpose-built to only verify these Zexe proofs for privacy preserving transactability. The consensus is PoW, while the proof system involves optimizing over the ability to calculate the verifications of these proofs efficiently.

The more efficient these miners become at verifying these proofs, the faster they are able to mine and thus the system provides sybil resistance through providing resources to verify Zexe proofs as a service in exchange for block creation.

However, these proof creations can be done in parallel based on the business logic for the systems the developers need to create. There is no direct need for on-chain custom verification as these can be done in an EVM contract, similar to what Cairo Generic Proving Service (GPS) verifier and Zinc Verification do.

The goal of Aleo is to incentivize miners to create specialized hardware to more efficiently mine blocks with verification proofs.

However, provers can also do this as we have seen with Matter Labs’ recent release of  [27]. It is a desirable property to use PoW to achieve “world-view” consensus in Aleo; however they focus on private transactions. They are typically not batched and employ a recursive outer proof to guarantee execution of an inner proof where the outer proof is sent to the blockchain to be verified. This proof is a limited 2-step recursion, consequently batching of arbitrary amounts of transactions is not supported.

However, as a result the cost of proof verification is relatively constant with a trade-off of limiting the recursion depth. Aleo is not meant to be a scalable aggregator of transactions, but mainly oriented towards privacy in their zk-SNARK constructions using Zexe.

Commercial Interests

Commercial enterprises may start to create proprietary prover technologies where costs will be lower than market in an attempt to create an advantage for user adoption. This design is made possible since the code for the prover is not required for the verifier to ensure that executions are correct. The proof is succinct whether or not the code to make the proof is available.

While the barrier of entry is low in this industry, we’ve seen the open source model and its communities optimize hardware and software and undergo academic peer review using strategies that outpace private funded corporations.

That is plausible to play out over the long term. However, an organic market will likely form on its own, forging its own path leading to mass adoption through capitalist forces.

The point here is that the privately funded vs open source nature of proving services does not change the mechanism of secure and scalable executions of calculations that are eventually rooted to decentralized and open ledgers secured by Bitcoin.

The utmost interesting propositions are the verticals that become possible by allowing infrastructure that is parameterized to scale into those economies where they are needed most, and where trust, security and auditability of value are concerns.

Smart cities, IoT, AI and Digital sovereignty are large markets that intersect with blockchain as a security blanket.

Although ZKP are tremendously useful on their own, applying them to consensus systems for smart contract executions drive them to another level due to the autonomous nature of “code-is-law” and provable deterministic state of logic. We believe a large majority of the next generation economy will depend on many of the ideas presented here.

 is working with commercial and enterprise adopters of blockchain technology. Our direct interaction with clients combined with our many collective years of experience in this field are reflected in this design.

Functional Overview

Fig 7: High-level description

For scalable simple payments, one can leverage our Syscoin Platform Token (SPT) asset infrastructure and payment channels to transact at scale.

Unique characteristics of SPTs include a generalized 8 byte field for the asset ID which is split between the upper and lower 4 bytes; the upper 4 are issued and definable (ie, NFT use cases) and lower 4 are deterministic. This enables the ability to have a generalized asset model supporting both Non-fungible Tokens (NFT) and Fungible Tokens (FT) without much extra cost at the consensus layers. 1 extra byte is used for all tokens at best case and 5 extra bytes are used for NFT at worst case.

See [28] for more information on .

This model promotes multiple assets to be used as input and consequently as outputs, suggesting that atomic swaps between different assets are possible within 1 transaction. This has some desirable implications when using payment channels for use cases such as paying in one currency when merchants receive another atomically.

A multi-asset payment channel is a component that is desired so users are not constrained to single tokens within a network. Composability of assets as well as composability across systems (such as users from one L2 to another) is a core fundamental to UX and convenience that needs to be built into our next generation blockchain components that we believe will enable mass adoption.

The Connext box shows how potentially you can  as described in [29]. This would promote seamless cross-chain L2 communication without the high gas fees. Since these L2’s are operating under an EVM/eWASM model, there are many ways to enable this cross-communication.

An EVM layer will support general smart contracts compatible with existing Ethereum infrastructure and L2 rollups will enable massive scale. The different types of zkRollups will allow businesses and rollup providers to offer ability for custom fee markets (ie, pay for fees in tokens other than base layer token SYS).

In addition, it will remove costs and thus improve scale of systems by offering custom data availability consensus modules. This design discussed here shares similarities to the  where a smart contract would sign off on data availability checks that would get put into the ZKP as part of the validity of a zkBlock which goes on chain.

The overall idea of the zkPorter design is that the zkRollup system would be called a “shard”, and each shard would have a type either operating in “zkRollup” mode or operating in “normal” mode.

Taken from the zkPorter article the essence of it is:

If a shard type is zkRollup, then any transaction that modifies an account in this shard must contain the changes in the state that must be published as L1 calldata (same as a zkRollup).

Any transaction that modifies accounts in at least two different shards must be executed in zkRollup mode.

All other transactions that operate exclusively on the accounts of a specific shard can be executed in normal shard mode (we will call them shard transactions). If a block contains some shard transactions for a shard S, then the following rules must be observed:

  1. The root hash of the subtree of the shard S must be published once, as calldata on L1. This guarantees that users of all other shards will be able to reconstruct their part of the state.
  2. The smart contract of the data availability policy of this shard must be invoked to enforce additional requirements (e.g. verify the signature of the majority of the shard consensus participants).

This concludes that shards can define different consensus modules for data availability (censorship resistance mechanisms) via separating concerns around ledgering the world-view of the state (ie, ZKP that is put on L1 and the data that represents the state. Doing so would allow shards to increase scale, offload costs of data availability to consensus participants.

A few note-worthy examples of consensus for data availability are:

  1. Non-committee, non fraud proof based consensus for data availability checks. No ⅔ online assumption; see  [30].
  2. Sublinear block validation of ZKP system. Use something like  as a data availability proof engine and majority consensus; see  [31].
  3. Use a combination of above, as well as masternode quorum signatures for any of the available quorums to sign a message committing to data availability checks as well as data validity. Using masternodes can provide a deterministic set of nodes to validate decisions as a service. The data can be stored elsewhere accessible to the quorums as they reach consensus that it is indeed valid and available.

Give Me The Goods

You may be wondering what a system like this can offer in terms of scale …

Simple payments: since payment channels work with UTXO’s and also benefit from on-chain scaling via Z-DAG, 16MB blocks (with segwit weight) assumed, we will see somewhere around 8MB-12MB effectively per minute (per block).

We foresee that is sufficient to serve 7 Billion people who may enter and exit the once a year (ie, 2 transactions on chain per person per year) for a total of 14 Billion transactions.

Let’s conservatively assume 8MB blocks and 300 bytes per transaction. Once on a payment channel, the number of transactions is not limited to on-chain bandwidth, but to network related latencies and bandwidth costs. Therefore, we will conclude that our payment scalability will be able to serve billions of people doing 2 on-chain transactions per year which is arguably realistic based on the way we envision payments to unfold; whether that is an L2 or payment channel network that will hold users to pay through instant transaction mechanisms.

On-chain, we have some  [1]; in those cases someone needs to transact for point-of-sale using the Syscoin chain. The solution for payments ends up looking like a hybrid mechanism of on-chain (Z-DAG) and off-chain (ie, payment channel) style payments.

Complex transactions such as smart contracts using zkRollups require a small amount of time to verify each proof. In this case, we assume that we will host data off-chain while using an off-chain consensus mechanism to ensure data availability for censorship resistance; so the only thing that goes on the chain are validity proofs. We will assume that we will assign 16MB blocks for the EVM chain per minute.

A proof size will be about 300kB for about 300k transactions batched together which will take about 60–80ms to verify and roughly 5 to 10 minutes to create such proofs.

These are the   using zk-STARKs which present quantum resistance and no trusted setup.

After speaking with Eli Ben-Sasson, we were made aware that proving and verifications metrics are already developed compared to what is currently presented by Starkware [34].

Hence, zk-SNARKs offer even smaller proofs and verification times at the expense of trusted setups and stronger cryptography assumptions (not post-quantum safe).

We foresee that these numbers will improve over time as the cryptography improves, but current estimates suggest a rough theoretical capacity of around 1 Million TPS.

Starkware was able to process 300k transactions over 8 blocks with a total cost of 94.5M gas; final throughput was 3000 TPS (see Reddit bake-off estimates). As a result, or the following calculations, let’s assume one batch-run to be 300k transactions.

Ethereum can process ~200kB of data per minute, with a cost limit of 50M gas per minute. Therefore, considering the Starkware benchmark test, and assuming a block interval of 13 seconds, we would achieve ~ 3000 TPS (ie, 300 k transactions per batch-run / (8 blocks per batch-run * 13 seconds per block))

It is estimated that Syscoin will be able to process ~16MB of data per minute on the EVM layer (ie, SYSX in Fig 3), which is ~80x gain over Ethereum; thus a cost limit of 4B gas (ie, 80*50M) per minute.

Therefore, if the Starkware benchmark test was run on Syscoin, it is estimated that Syscoin could run the equivalent of 42 batch-runs per minute (ie, 4B gas per minute / 94.5 M gas per batch-run).

That would result in an equivalent of 210 k TPS (ie, 42 batch-runs per minute * 300 k transactions per batch-run / 60 seconds per minute).

If we were to consider using Validum on the Syscoin EVM layer, we estimate that we could achieve 800 batch-runs per minute (ie, 4B gas per minute / 5 M gas per batch-run). That would equate to an equivalent of 4M TPS (ie, 800 batch-runs per minute * 300 k transactions per batch-run / 60 seconds per minute).

Table 2: Gas costs and Total throughput

* Because all transactions are on-chain, which would include state lookups and modifications, it would likely result in a smaller total throughput depending on the node. This would be on average somewhere between 50–150 TPS total due to the state lookup bottlenecks, which are not an issue in a rollup design and can be done in a state-less way on-chain (meaning the throughput can instead be bounded by computational verification of the ZKPs)

**Rollups post the transitions on-chain and Validium does not, but note that the transitions on chain are account transitions and not transactions and so if some accounts interact within the same batch it will be just those account transitions recorded to the chain regardless of how many actual transactions are done between them.This is the minimum TPS with full layer 1 decentralized security. The amortized cost per Tx thus drops as accounts are reused within the This is the minimum TPS with full layer 1 decentralized security. The amortized cost per Tx thus drops as accounts are reused within the batch and the total TPS would subsequently rise.

Optimizations to the verification process are likely and would be required to get to those numbers, but the bandwidth would allow for such scale should those optimizations come to fruition.

For example 800 zk-STARK verifications at roughly 80ms per zk-STARK would take around 64 seconds, however these proofs can be verified in parallel so with a 32-core machine. It would take ~2–3 seconds total spent on these proofs, and likely decrease further with optimizations (note that TPS includes total account adjustments).

Because of the higher throughput capabilities of baseline EVM, we may look to  [32] to thwart DOS attacks.

The aforementioned calculations demonstrate the full State Safety of the mainchain secured by Bitcoin, and no asynchronous network assumptions which make theoretical calculations impractical in many other claims of blockchain throughput due to execution model bottlenecks.

These results were extrapolated based on real results with constant overhead added that becomes negligible with optimizations. It is imperative to note that transactions in this strategy are not re-executable; there is little to no complexity in this model other than verifying succinct proofs. The proof creation strategy is parallelized organically using this model. The verifications on the main chain can also be parallelized as they are executed on separate shards or rollup networks. Dual parallel execution and verification gives exponentially more scalability than other architectures.

Additionally, privacy can be built into these models at minimal to no extra cost, depending on the business model. Lastly, we suggest these are sustainable throughput calculations and not burst capacity numbers which would be much higher (albeit with a marginally higher fee based on fee markets).

For example Ethereum is operating at 15 TPS but there are around 150k transactions pending, and the average cost is about 200 gWei currently. The fee rate is based on the calculation that it takes around 10000 seconds to clear, assuming this many transactions, no new transactions, and there is demand to settle earlier.

Extrapolating on 4M TPS the ratio would become 40B transactions pending with 4M TPS to achieve the same fee rate on Ethereum today assuming the memory pool is big enough on nodes to support that many pending transactions.

Since masternodes on Syscoin are paid to provide uptime, we can expect network bandwidth to scale up naturally to support higher throughput as demand for transaction settlement increases.

Today, the ability to transact at a much higher rate using the same hardware provides the ability for a greater scale than the state-of-the-art in blockchain design without the added desired caveat of avoiding asynchronous network assumptions.

We believe this proposed design will become the new state-of-the-art blockchain, which is made viable due to its security, flexibility and parallelizable computational capacity.

In regards to uncle rates with higher block sizes, keep in mind we make uncle rates and re-organizations in general negligible through the use of the PoW chain mining Syscoin along with Chain Locks. We provide intuition that block sizes can be increased substantially without affecting network health.

Furthermore, the gas limits can be adjusted by miners up to 0.1% from the previous block and so a natural equilibrium can form where even if more than 4B gas is required it can be established based on demand and how well the network behaves with such increases.

There is a lot to unpack with such statements and so we will cover this in a separate technical post as it is out-of-scope for this discussion.

Blockchain Foundry

One of the main reasons for a profit company is to take advantage of some of the aforementioned verticals which we expect to underpin the economies of tomorrow with infrastructure similar to what is presented here.

Since the company’s beginning in 2016, we have spent the majority of our existence designing architecture parameterized to global financial markets.

Breakthroughs in cryptography and consensus designs as described here lead us to formalize these designs to apply to market verticals, formulating new applications and solutions that would not have been possible before.

Specifically, , we believe these ideas can be IP protected without requiring privatization of the entire tech stack. These value-added ideas that will use existing open-source tech stacks enabling a massive network effect of value through incentivization of commercial and enterprise adoption.

These new ideas, innovations and proprietary production quality solutions could steer in a new wave of  for civilization.


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[7] J. Drake. Pragmatic signature aggregation with BLS, May 2018. Accessed on: Feb 2021. [Online]. Available: 

[8] S. Bowe, BLS12–381: New zk-SNARK Elliptic Curve Construction, Mar 2017. Accessed on: Feb 2021. [Online]. Available: 

[9] A. Block, BLS: Is it really that slow?, Jul 2018. Accessed on: Feb 2021. [Online]. Available: 

[10] S. de la Rouvier. Interplanetary Linked Computing: Separating Merkle Computing from Blockchain Computational Courts, Jan 2017. Accessed on: Feb 2021. [Online]. Available: 

[11] Anonymous Kid, Why the fuck did Satoshi implement the 1 MB blocksize limit? [Online forum comment], Jan 2018, Accessed on: Feb 2021. [Online]. Available: 

[12] Zero-Knowledge Proofs What are they, how do they work, and are they fast yet? Accessed on: Feb 2021. [Online]. Available: 

[13] E. Ben-Sasson, I. Bentov, Y. Horesh, and M. Riabzev, Scalable, transparent, and post-quantum secure computational integrity, IACR Cryptol, 2018, pp 46

[14] Dryja, T, Utreexo: A dynamic hash-based accumulator optimized for the bitcoin UTXO set, IACR Cryptol. ePrint Arch., 2019, p. 611.

[15] G.I. Hotchkiss, The 1.x Files: The State of Stateless Ethereum, Dec 2019. Accessed on: Feb 2021. [Online]. Available: 

[16] S. Bowe, A. Chiesa, M. Green, I. Miers, P. Mishra, H. Wu: Zexe: Enabling decentralized private computation. Cryptology ePrint Archive, Report 2018/962 (2018). Accessed on: Feb 2021. [Online]. Available: 

[17] A. Nilsson, P.N. Bideh, J. Brorsson, A survey of published attacks on Intel SGX. 2020, arXiv:2006.13598

[18] C. Nelson, Zero-Knowledge Proofs: Privacy-Preserving Digital Identity, Oct 2018. Feb 2021. Accessed on: [Online]. Available: 

[19] D. Boneh, Discrete Log based Zero-Knowledge Proofs, Apr 2019, Accessed on: Feb 2021 [Online]. Available: 

[20] Quantum Computing’s Implications for Cryptography (Chapter 4), National Academies of Sciences, Engineering, and Medicine: Quantum Computing: Progress and Prospects. The National Academies Press, Washington, DC, 2018.

[21] S. Naihin, Goodbye Bitcoin… Hello Quantum, Apr 2019, Accessed on: Feb 2021 [Online]. 

[22] L.T. do Nascimento, S. Kumari, and V. Ganesan, Zero Knowledge Proofs Applied to Auctions, May 2019, Accessed on: Feb 2021 [Online]. Available: 

[23] G., Proof of Stake Versus Proof of Work. Technical Report, BitFury Group, 2015. Accessed on: Feb 2021. [Online]. Available: 

[24] V. Buterin and V. Griffith, Casper the Friendly Finality Gadget. CoRR, Vol. abs/1710.09437, 2017. arxiv: 1710.09437, 

[25] M. Neuder, D.J. Moroz, R. Rao, and D.C. Parkes, Low-cost attacks on Ethereum 2.0 by sub-1/3 stakeholders, 2021. arXiv:2102.02247, 

[26] Starkware, Validity Proofs vs. Fraud Proofs, Jan 2019, Accessed on: Feb 2021, [Online]. Available: 

[27] A. Gluchowski, World’s first practical hardware for zero-knowledge proofs acceleration, Jul 2020, Accessed on: Feb 2021 [Online]. Available: 

[28] Introducing an NFT Platform Like No Other, Accessed on: Feb 2021. [Online]. Available: 

[29] A. Bhuptani, Vector 0.1.0 Mainnet Release, The beginning of a multi-chain Ethereum ecosystem, Jan 2021, Accessed on: Feb 2021. [Online]. Available: 

[30] V. Buterin, With fraud-proof-free data availability proofs, we can have scalable data chains without committees, Jan 2020, Accessed on: Feb 2021. [Online]. Available: 

[31] M. Al-Bassam, A data availability blockchain with sub-linear full block validation, Jan 2020, Accessed on: Feb 2021. [Online]. Available: 

[32] T. Chen, X. Li, Y. Wang, J. Chen, Z Li, X. Luo, M. H. Au, and X. Zhang. An adaptive gas cost mechanism for Ethereum to defend against under-priced DoS attacks. Proceedings of Information Security Practice and Experience — 13th International Conference ISPEC, 2017

[33] Y. Sompolinsky, and A. Zohar, Secure High-rate Transaction Processing in Bitcoin, Proc. 19th Int. Conf. Financial Cryptogr, Data Secur. (FC’20), Jan 2015, pp. 507–527

[34] Starkware Team, Rescue STARK Documentation — Version 1.0, Jul 2020

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Why bitcoin matters

Why Bitcoin Matters ?


“A mysterious new technology emerges, seemingly out of nowhere, but actually the result of two decades of intense
research and development by nearly anonymous researchers.

Political idealists project visions of liberation and revolution onto it; establishment elites heap contempt and scorn on it.

On the other hand, technologists – nerds – are transfixed by it.

They see within it enormous potential and spend their nights and weekends tinkering with it.

Eventually mainstream products, companies and industries emerge to commercialize it; its effects become profound; and later, many people

wonder why its powerful promise wasn’t more obvious from the start.

What technology am I talking about?

Personal computers in 1975, the Internet in 1993, and – I believe – Bitcoin in 2014….

The practical consequence of solving this problem is that Bitcoin gives us, for the first time, a way for one Internet user to transfer a unique piece of digital property to another Internet user, such that the transfer is guaranteed to be safe and secure, everyone knows that the transfer has taken place, and nobody can challenge the legitimacy of the transfer.

The consequences of this breakthrough are hard to overstate.

What kinds of digital property might be transferred in this way?

Think about digital signatures, digital contracts, digital keys (to physical locks, or to online lockers), digital ownership of physical assets such as cars and houses, digital stocks and bonds …

and digital money”.

– Marc Andreessen, Founder of Netscape & well-known venture capitalist, 2014

Marc Lowell Andreessen

(/ænˈdriːsən/ann-DREE-sən;

born July 9, 1971) is an American entrepreneurinvestor, and software engineer.

He is the co-author of Mosaic, the first widely used web browser; co-founder of Netscape; and co-founder and general partner of Silicon Valleyventure capital firm Andreessen Horowitz.

He co-founded and later sold the software company Opsware to Hewlett-Packard.

Andreessen is also a co-founder of Ning, a company that provides a platform for social networking websites.

He sits on the board of directors of Meta Platforms.

Andreessen was one of six inductees in the World Wide Web Hall of Fame announced at the First International Conference on the World-Wide Web in 1994.

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Btc-Usd Monthly Returns


Btc-Usd Monthly Returns 2011-2021

Asset Class Total Return over last 10 Years

Numbers talk louder and more truthful than words could ever do !!!

Simple plain numbers that have the answer everyone is looking for 🙂😉

That’s what I love about mathematics, it’s an undeniable Truth !!!

Read and pick your own conclusion folks !!!

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Books I  💚 ly Recomend

“So many books, so little time.”

Frank Zappa

Good friends, good books, and a sleepy conscience: this is the ideal life.”

Mark Twain

“A book lying idle on a shelf is wasted ammunition.”

Henry Miller, “The Books in My Life
My Preciousssssssssss 😊🤗💚

Books I  💚ly reccomend

"The Compound effect" - Darren Hardy

"Algorithms to live by" - Brian Christian & Tom Griffiths

"Ikigai" - Hector Garcia & Francesc Mirales

"Thinking, Fast and Slow" - Daniel Kahneman

"Emotional Intelligence" - Daniel Goleman

"The magic of thinking Big" - David Schwartz,PHD

"Sapiens" - Yuval Noah Harrari

"Noise" - Daniel Kahneman & Oliver Sibony & Cass R. Sunsteen

"The tipping point" - Malcom Gladwell

“Blink” – Malcom Gladwell

“David & Goliath” – Malcom Gladwell

"The New Human Rights Movement" - Peter Joseph
(Zeitgeist - watch it 😉 )

"Zero to one" - Peter Thiel

"The intelligent Investor" - Benjamin Graham

"How to make friend and be successful" - Dale Carnegie

"Law of Success" - Napoleon Hill

“Think and Grow Rich” – Napoleon Hill

"Positive Thinking" - Napoleon Hill

"The Business Ideea Factory" - Andrii Sedniev

"Common Stocks & Uncommon Profits" - Philip A. Fisher

"The little book of common sense investing" - John C. Boogle

"Freakonomics" - Steven D. Levitt & Stephen J. Dubner

"Influnce" - Robert B. Cialdini,PHD

“The Psycology of Money” – Morgan Housel

“The Art of Strategy” – R. L. Wing

“Warren Buffet and the Interpretation of Financial Statements” – Mary Buffet & David Clark

“30+ Years of Lessons Learned from Warren Buffet & Charlie Munger” – Daniel Pecaut with Corey Wrenn

“CryptoTrading Pro” – Alan T. Norman

“Mastering Bitcoin” – Andreas M. Antonopoulos

“Mastering Ethereumn” – Andreas M. Antonopoulos

“The Internet of Money” – Andreas M. Antonopoulos

“The Bitcoin Standard” – Saifedean Ammous

“21 Lessons” - Gigi

"Book of Satoshi" - Phil Champagne

"Inventing Bitcoin" - Yan Pritzker, Nicholas Evans

"Digital Gold:The Untold Story of Bitcoin" - Nathaniel Popper

"Grokking Bitcoin" - Kalle Rosenbaum, David A. Harding

"Alghorithms Illuminated" - Tim Roughgarden

"Consumer Psichology and Consumer Behaviour" - Max Mittelstaedt

"Deep Work" - Cal Newport

“Biology of Belief” – Bruce Lipton

“The HoneyMoon Effect” – Bruce Lipton

“Ego is the Enemy” – Ryan Holiday

“A history of almost Everything” – Bill Bryson

“Psychology of Money” – Morgan Housel

"Rich Dad, Poor Dad" - Robert T. Kiyosaky

"CashFlow Quadrand" - Robert T. Kiyosaky

"Guide To Investing" - Robert T. Kiyosaky

“Atlas of AI” – Kate Crawford

“Use both sides of your brain” – Tony Buzan

“Mind Maps for kids” – Tony Buzan

“Study Skills” – Tony Buzan

"Mind Map Mastery" - Tony Buzan

“Atomic Habits” – James Clear

“The First and last Freedom” – J Krishnamurti

"The Emperor of all maladies" - Siddhartha Mukherjee

"A brief History of everyone who ever lived" - Siddhartha Mukherjee

"The Gene" - Siddhartha Mukherjee

“Business Adventures” – John Brooks

“Code Breaker” – Walter Isaacson

“A thousand Brains” – Jeff Hawkins

“Social Engineering” – Christopher Hadnagy

“The Innovators Dilemma” – Clayton M. Christensen

“Critical Path” – R. Buckminster Fuller, Kiyoshi Kuromiya

“Price of Tomorrow” – Jeff Booth

“Pedagogy of the Oppressed” – Paulo Freire

“The Sovereign Individual” – James Dale Davinson,William Rees-Mogg

“The Broken CEO” – Chris Pearse

“Pragmatic thinking and Learning” – Andy Hunt

“The Creature from Jekill Island” – G. Edward Griffin

“The Wealth of Nations” – Adam Smith

“The Law” – Frederic Bastiat

"The Bastiat Collection:Volume 1" - Frederic Bastiat

“Tools of Titans” – Tim Ferris

“An Essay concerning Human Understanding” – John Locke

“A treatise on Human Nature” – David Hume,Thomas Hill Green

“The Richest Man in Babylon” – George O. Clason

“Think Again” – Adam Grant

“The Alchemist” – Paulo Coelho

“Black Swan” – Nassim Nicholas Taleb

"The Rise of the Computer State" - David Burnham

"The Productivity Revolution" - Marc Reklau

"The Power of Habbit" - Charles Duhigg

"The Way Out" - Peter T. Coleman

"Digital Body Language" - Erica Dhawan

"The Promises of Giants" - John Amaechi

"Dedicated" - Pete Davis


"How to Change" - Kathy Milkman

"Substract" - Leidy Klotz

"The Psichogy of Selling" - Brian Tracy

"Awaken the Giant Within" - Tony Robbins

"Crushing It" - Gary Vaynerchuck

"The Power of Now" - Eckhart Tolle

"Sell or be Sold" - Grant Cardone

"The One Thing" - Gary Keller

"The Snowball" - Alice Schroeder

"Tap Dancing to Work:Warren Buffet on practically Anything" - Carol Loomis

"Extreme Ownership" - Jocko Willink, Leif Babin

"The Subtle Art of Not Giving a F*uck" - Mark Manson

"The Miracle Morning" - Hal Elrod, Robert Kiyosaki

"Tools of the Titans" - Tim Ferris

"Die Sheeple! Die!" - DJ Hives

"A few Lessons for Investors and Managers from Warren Buffet" - Peter Bevelin

"Warren's Buffet Ground Rules" - Jeremy Miller

"Limping on Water" - Phil Beuth, K. C. Schulberg

"Shoe Dog" - Bill Knight

"Where are the Customers Yacths" - Fred Schwed Jr.

"40 Chances" - Howard G. Buffet, Warren E. Buffet

"Clash of the Cultures:Investment vs. Speculation" - John C. Bogle, Arthur Lewitt

"Poor Charlie's Almanack" - Charles T. Munger

"Think Again" - Adam Grant

"Charlie Munger-The Complete Investor" - Tren Griffin

"Bull" - Maggie Mahar

"The Hard thing about Hard things" - Ben Horowitz


"Atomic Habbits" - James Clear

“Books are the quietest and most constant of friends; they are the most accessible and wisest of counselors, and the most patient of teachers.”

Charles W. Eliot

“There is no friend as loyal as a book.”

Ernest Hemingway

“Make it a rule never to give a child a book you would not read yourself.”

George Bernard Shaw

“If you have a garden and a library, you have everything you need.”

Cicero

“Books are like mirrors: if a fool looks in, you cannot expect a genius to look out.”

J.K. Rowling

“I cannot remember the books I’ve read any more than the meals I have eaten; even so, they have made me.”

Ralph Waldo Emerson

“A book must be the axe for the frozen sea within us.”

Franz Kafka

“The best books… are those that tell you what you know already.”

George Orwell, “1984

“My Best Friend is a person who will give me a book I have not read.”

Abraham Lincoln

“One glance at a book and you hear the voice of another person, perhaps someone dead for 1,000 years.

To read is to voyage through time.”

Carl Sagan

The list will always be updated…


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Happy 13th BirthDay bitcoin

bitcoin – People’s Money

Brief history of Bitcoin

On January 3rd, 2009 Satoshi Nakamoto published the Genesis Block with the first 50 Bitcoins on Sourceforge. He also left a message on the blockchain at the time, quoting the headline in the British newspaper Times:

On January 3, 2009, the minister was on the verge of bailing out the banks.

Nakamoto started writing the white paper in 2008 and published it in October of that year.

The concept of a decentralized, anonymous, trusted currency emerged after the 2008 financial crisis, which left responsibility for the banks.

Satoshi neither supports the modern banking system nor does he like partial reserve banks.

A partial reserve bank is a bank that takes deposits and issues loans or investments, but only has to reserve a fraction of its liabilities for deposits. Basically, the bank is using money that it doesn’t own.

Satoshi wants to get rid of banks and seedy middlemen whom he believes are corrupt and unreliable. As such, he created a more community-centric digital currency.

13 years later, Bitcoin is still going strong with a market cap of nearly $ 900 billion. It is currently held by billionaires, banks, celebrities, governments, and corporations. This is evidence of how far BTC has come in its brief existence.

The precarious banking situation and economic uncertainty are also in crisis again.

The price of Bitcoin on its birthday 🎂

13 years: $ 47,310
12 years: $ 33,400
11 years: $ 7,319
10 years: $ 3,783
9 years: $ 14,764
8 years: $ 1,084
7 years: $ 432
6 years: $ 275
5 years: $ 816
4 years: $ 13
3 years: $ 5
2 years: $ 0.29
1 year: $ 0.05


Happpy Birthday bitcoin !!!

Thanks for all the teachings and wealth of Knowledge I do now have thanks to you !!!


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DEX Aggregators 2022

Top DEX Aggregators

Decentralized exchange (DEX) aggregators, also known as liquidity aggregators, compile the exchange rates of numerous DEX platforms and show you a list of platforms offering the best value for your crypto trades.

Moreover, you can access a deeper pool of liquidity by trading on multiple DEXs using a single trading dashboard. Think of them as the search engines of the DeFi landscape, scouring DEXs for the best deals so that you can swap your crypto assets with the lowest fees.

1Inch

Although it is a DEX in its own right, 1Inch’s main USP is its position as a top DEX aggregator across multiple blockchains. The network supports trades across major ecosystems like Ethereum and Binance and smaller networks like Polygon, Arbitrum, and Optimism.

As an aggregator, 1Inch gives you access to over 120 liquidity sources, with 68 on Ethereum, 39 on Binance, and 24 on Polygon. With daily trading volumes averaging close to $300 million from 300,000+ active users, it is one of the most active DEX aggregators in 2021.

The native token of the 1Inch DEX is also called 1INCH. It functions as both a utility token and a governance token for the protocol. 1INCH is a multi-chain token available on the Ethereum and Binance Smart Chain.

1Inch is one of the best DEX aggregators for crypto rookies, with detailed documentation and a well-developed Help Center filled with starter guides, FAQs, and more.



Slingshot

Slingshot grew out of DEX.AG, a DEX aggregator platform created in late 2018 as part of a hackathon event. At its launch, it supported seven major DEX, including Uniswap, Kyber, and DDEX.

After million-dollar funding rounds, DEX.AG was rebranded as Slingshot in November 2020. Slingshot works on Ethereum-based protocols – Polygon (formerly MATIC) and Arbitrum One. Across the two, you get access to over 326 exchanges/liquidity sources.

Slingshot is a very popular choice among experienced cryptocurrency traders due to its relative simplicity and advanced functionality. The average daily volumes touching over half a billion dollars is a testament to the platform’s popularity.

However, due to a threadbare interface and lack of easily accessible website FAQs, guides, and documentation, Slingshot is not a very beginner-friendly DEX platform.



Totle Swap

Totle is a DEX aggregator that also dips into synthetic asset providers, allowing traders to engage with tokenized assets of many shapes and sizes. Unfortunately, the platform seems to be dormant, with no updates since mid-2021 and a lack of stats on any major crypto platform.


ParaSwap

ParaSwap is a versatile DEX aggregator supporting Ethereum, Binance, Polygon, and Avalanche blockchains. In addition, it has a native token for liquidity and governance purposes called the PSP.

While it is one of the more feature-packed and beginner-friendly DEX aggregators, ParaSwap is still in the growth phase. In 2021, the platform reported 1.4 million total users over time, with daily transaction volumes peaking around $150 million.

ParaSwap allows you access to swap and payment options across 75 DEX platforms, focusing on better market rates and cheaper gas fees. In addition, decentralized applications (dApps) can also integrate with ParaSwap to better streamline token swaps.


Matcha

Like 1Inch and Slingshot, Matcha is both a DEX aggregator and a decentralized exchange in itself. Powered by 0x Labs, the platform focuses on transparency, lower fees, smart order routing, and easier access.

Thanks to a recent partnership with MoonPay, Matcha can now accept payments in fiat currencies, a first for DEX platforms. This could be very useful for newcomers – you can directly purchase cryptos using regular currency on Matcha and start trading immediately.

Matcha provides access to over 50 liquidity sources and DEX platforms across three blockchain systems – Ethereum, Binance, and Polygon. Despite being one of the younger platforms on this list (launched in 2020), Matcha boasts over 2.5k daily traders. Its daily volumes are close to $150 million.


Uniswap V3

Uniswap is a DEX platform based on the Automated Marker Maker (AMM) model. After its launch in November 2018, the DEX has seen a meteoric rise among crypto circles. As of Q4 2021, it routinely tops the charts of DEX platforms with the largest daily volumes with $5.5 billion.

The platform is currently in its third iteration – Uniswap V3. Based on the Ethereum Blockchain, Uniswap gives you access to over 50 liquidity pools, with 285 cryptocurrencies across more than 350 markets. The USDC-ETH pair alone accounts for over $1.8 billion worth of trades each day.

While not a DEX aggregator per se, Uniswap is still a great option to consider due to its sheer size and reach. Most of the other aggregators on this list have Uniswap as a major partner and source of trading options.


PancakeSwap

PancakeSwap launched in 2020 to work like Uniswap, but on the Binance Smart Chain instead of Ethereum. Like Uniswap, PancakeSwap is a DEX platform with an AMM operating model, with an additional focus on yield farming based on the native CAKE token.

Regardless of the sweet and syrupy “cake” theme, PancakeSwap is a major force on the DeFi scene, thanks to the sheer size of the Binance blockchain. It easily slots into the top three most active DEX platforms, with daily volumes exceeding $2.6 billion.

The platform is user-friendly, with detailed community guides, troubleshooting articles, and customer support. In addition, you can trade in over 30 major cryptos backed by an equal number of high-quality liquidity pools.


SushiSwap

Is based directly on Uniswap, with a fork in the original code created by its anonymous developer who goes by the pseudonym Chef Nomi.

Right from the outset, SushiSwap has courted controversy. To generate liquidity, its founder encouraged users to deposit in Uniswap tokens, leeching away almost $810 million from Uniswap in a “vampire attack.”

Chef Nomi then proceeded to withdraw his liquidity from the project, generating a massive controversy. Ultimately, he backtracked and returned all funds, relinquishing his control over the project to a new team.

Since these early missteps, SushiSwap has maintained healthy growth rates in the crowded arena of Ethereum-based DEX/AMM platforms. It currently ranks in the top ten list, with daily volumes of close to $800 million across 400+ markets.


dYdX

dYdX is a major DEX platform with a heavy focus on reducing the inflated gas prices on Ethereum. It is one of the few platforms to offer gasless deposits to new users who deposit above a certain threshold. The platform has plans to make this a permanent feature.

dYdX is also working closely with StarkWare to deploy a Layer 2 scalability engine designed to reduce gas costs and trading fees further. Using Ethereum Smart Contracts, dYdX enables traders to invest in the crypto-equivalent of futures trading and other derivatives.

Due to its unique position on the Ethereum ecosystem, dYdX has managed to gain ground on other more popular DEX platforms like Uniswap. As a result, at the end of 2021, dYdX is ranked second on the list of the most active DEX platforms, with daily volumes of $5.4 billion.


Raydium

Instead of Ethereum or Binance, the Raydium platform operates on the highly promising Solana blockchain. As a result, the Ethereum-competitor has a vibrant developer ecosystem, and its cryptocurrency has grown at least 16,000% since January 2021.

The increased interest in the Solana blockchain has also helped Raydium, an AMM platform based on the Serum DEX.

The platform gives access to over 430 trading pairs, with Solana-USDT being the most popular.

The native token, also called Raydium, is the foundation of all future apps and projects on the Solana and Serum ecosystems.

The project’s primary focus is to function as the engine of DeFi on Solana. However, with current daily volumes already reaching $300 million, Raydium shows a lot of promise for future growth.


TraderJoe

Launched in 2020 as a less expensive, more efficient alternative to Ethereum,  Avalanche blockchain focuses on decentralized apps.

Its AVAX token has hit all-time high demands in late 2021, thanks to positive media coverage and high-profile partnerships with entities like Deloitte.

This surge has also propelled TraderJoe, the major DEX platform based around Avalanche blockchain, to the top of the DEX pile in recent times. Its pole position in the blockchain ecosystem has helped drive TraderJoe’s daily trades close to $1 billion.

You can trade major cryptos, stake and gain the native JOE token as rewards, lend other cryptos and farm yields on the TraderJoe platform. With low fees and over 170 markets, TraderJoe is a top target for anyone interested in the Avalanche ecosystem.


Top Pick: Uniswap

The Top pick is Uniswap, for its deep liquidity pools, its user-friendliness, and its commitment to continuous innovation.

As the various DeFi ecosystems continue to grow and expand, the importance of DEX aggregators and AMM platforms will increase further.

These platforms serve a vital purpose, finding liquidity and facilitating transactional activity across multiple blockchains.

To say that the future of DeFi, and by extension, the future of finance as we know it, hinges on DEX aggregators would not be an overstatement.


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#1 Book of the Year I recomend reading…

“Ego is the Enemy”


“Re-read it each year. It’s that important.”

Derek Sivers, author of “Anything you want”

“This is a book I want every athlete, aspiring leader, entrepreneur, thinker and doer to read. Ryan Holiday is one of the most promising young writers of his generation.”

George Raveling, Hall of Fame Basketball Coach

“Ryan Holiday is one of his generation’s finest thinkers, and this book is his best yet.”

Steven Pressfield, author of “The War of Art” and “Gates of Fire

“Ryan Holiday has written a brilliant and engaging book, well beyond his years… It is invaluable.”

Brian Koppelman, screenwriter and director, “Rounders”, “Ocean’s Thirteen” and “Billions”

Ego Is the Enemy

“While the history books are filled with tales of obsessive, visionary geniuses who remade the world in their image with sheer, almost irrational force, I’ve found that history is also made by individuals who fought their egos at every turn, who eschewed the spotlight, and who put their higher goals above their desire for recognition.” – from the Prologue

Many of us insist the main impediment to a full, successful life is the outside world. In fact, the most common enemy lies within: our ego. Early in our careers, it impedes learning and the cultivation of talent. With success, it can blind us to our faults and sow future problems. In failure, it magnifies each blow and makes recovery more difficult. At every stage, ego holds us back.

The Ego is the Enemy draws on a vast array of stories and examples, from literature to philosophy to history. We meet fascinating figures like Howard Hughes, Katharine Graham, Bill Belichick, and Eleanor Roosevelt, all of whom reached the highest levels of power and success by conquering their own egos. Their strategies and tactics can be ours as well.

But why should we bother fighting ego in an era that glorifies social media, reality TV, and other forms of shameless self-promotion?  Armed with the lessons in this book, as Holiday writes, “you will be less invested in the story you tell about your own specialness, and as a result, you will be liberated to accomplish the world-changing work you’ve set out to achieve.


RYAN HOLIDAY


Ryan Holiday is a strategist and writer. He dropped out of college at nineteen to appren­tice under Robert Greene, author of “The 48 Laws of Power”, and later served as the director of mar­keting for American Apparel.

His company, Brass Check, has advised clients like Google, TASER, and Complex, as well as many prominent bestselling authors.

Holiday has written four previous books, most recently The Obstacle Is the Way, which has been translated into seventeen languages and has a cult following among NFL coaches, world-class athletes, TV personalities, political leaders, and others around the world.

He lives on a small ranch outside Austin, Texas. 


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