This year’s election in Italy was shocking. The populist, anti-establishment Five Star Movement party emerged from obscurity to become the largest party in government. Its central campaign plank was to pay a Universal Basic Income (UBI), locally referred to as the “citizen’s income” and “citizen’s wage” to the poor. Italy has long suffered from mass unemployment. The new government is fulfilling its campaign promise: it has introduced a UBI of €780 per person, every month, in its draft 2019 budget

Economists have often wrongly predicted that technology will destroy jobs. Today, a widely held view is that technological advances will make up for the jobs they destroy by creating new ones, as they have in the past. But this time could be different.

AI could optimize workflows to the extent that minimal human contribution is required, thereby destroying more jobs than it creates. Take the example of taxi drivers. Uber and Lyft have reduced their wages, but increased the demand for their services. When cars become fully self-driving, these drivers will have to seek work elsewhere. A similar example is truck drivers. They will first transition into the passenger seat, supervising self-driving trucks. In the next phase, they will no longer be necessary.

​In a couple of decades, the interaction of AI, robotics and hive robotics, digital automation and the Internet of Things could make most jobs unnecessary — just as the population of the world hits an all-time high.

​Unemployment is already a major issue. Despite the booming US economy and high employment figures, wages are stagnating, a large percentage of people are underemployed and there has been a long decline in the labor participation rate (more people have been staying home and not looking for work).

​Even when the global economy is healthy, unemployment is a major problem in much of the world. After the next economic downturn, the world will witness mass unemployment and an even more volatile social environment.

To address unemployment, underemployment and wage stagnation, populist politicians in Italy and elsewhere have turned to UBI as a campaign plank.

Universal Basic Income (UBI), sometimes referred to as a ‘Basic Income Guarantee’ or ‘Universal Demogrant’, is a proposed welfare program in which every citizen of a country receives an unconditional, regular, and livable sum of money from the government.

Since UBI is unconditional, it is received by the employed and the unemployed alike, and the rich and the poor alike.
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UBI’s critics sometimes liken it to socialism or even communism. This is wrongheaded. History has shown communism to be a failed ideology that has led to colossal economic mismanagement and waste, violent unrest, and even genocide and mass starvation. Communist and socialist regimes have often consolidated power in a dangerous manner, enabling government officials to create state-sponsored economic fiefdoms at the expense of the citizens they purport to govern. UBI is an economic program that can co-exist with our tried and tested, modern, capitalist economic system. UBI’s aims are limited and simple: to support the basic needs of every citizen and to eradicate extreme poverty.

Policy makers are presiding over a political and economic system designed over 70 years ago and tweaked a few times since then. It has given us a period of economic growth, technological innovation, and increased personal freedom.

​It will have to be tweaked again to head off technology-sponsored mass unemployment.

Already, we are experiencing a backlash against big tech companies in the United States and around the world. Companies that were benign startups in the 1990s have emerged as market-leading conglomerates, and can deploy massive capital, data, and algorithms, not to mention the best tech developers and thinkers that money can buy. The power they have aggregated has increasingly engendered fear and suspicion.

These feelings will only become stronger if technology continues to destroy jobs. The process is far along in many industries, such as agriculture and advanced manufacturing. It is likely that the labor participation rate will continue to drop, with short bursts of job creation masking the overall downward trend.

However, elected officials around the world increasingly find their terms plagued with gridlock, political jockeying, and preparing for the next election. This is hardly the ideal environment for grappling with complex, long-term problems like the threat of mass unemployment in the future. Even the lucky few political leaders who are able to pursue their agendas often attract investment with the hope of creating jobs. Ironically, the sector that attracts the most investment is technology — the same sector which is poised to destroy our jobs in the long term.

​This is not to say that policy makers should oppose the march of technology. This approach would be akin to trying to patch a crack in the hull of an oil tanker with a bandage. A more pragmatic approach is to recognize the issue of technology-created unemployment and address the consequences it may have.

Economists often argue that despite UBI’s noble aims, it is too expensive. The amount paid to every citizen must come from somewhere. They are also often concerned by UBI’s effects on incentives to work and be productive.Running perpetual government deficits could be disastrous for the national debt, the money supply is controlled by independent, technocratic, and risk-averse institutions, and all of this exists within a complex, interconnected global economic system. The shockwaves of a poorly-implemented UBI program in one country may be felt by economies across the world. So, how can a government fund a monthly stipend for each of its citizens?

A recent model developed at Wharton (at the University of Pennsylvania) suggested three potential ways to pay for UBI in the United States: by running deficits, by increasing the payroll tax, or by external financing (similar to oil revenues from Alaska providing stipends for all of its citizens).
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The model found that UBI would reduce the hours people worked and would reduce the GDP. If UBI is not viable in the United States, it follows that it is even less viable in emerging economies. This explains why most economists oppose UBI.

However, in democracies, economists do not dictate policy — the political process does. In the next economic recession, populist leaders will seize upon unemployment, underemployment, and economic anxiety to promise UBI.

​What has happened in Italy could happen elsewhere. Therefore, it is important to think about how UBI and similar programs could be implemented effectively, before a politician promising the moon comes along and clumsily enacts a thoughtless or counterproductive policy.

There have already been many UBI studies and pilots in various parts of the world. Recipients often continued to spend money, were less likely to slip into alcohol or drug abuse, and strived to better their situations. The challenge is to retain these benefits while minimizing unintended costs.

​The ideas below are my contribution to the UBI debate. These ideas should be tested, tweaked, and iterated, with the aim of better modeling a UBI that can enhance the quality of people’s lives without harming the global economic system. Software developers are familiar with the idea of a ‘stack’, which contains a group of technologies that work together, but in which any element can be replaced. I think of the three ideas below as elements of an ‘Economic Stack’: they can be mixed and matched, and they can be tested on top of our current economic system

Proposal 1: Expiring Money

Blockchain technology and cryptocurrencies have introduced money that can be programmed with conditions and variables. I propose adapting this idea to UBI by issuing fiat currency tokens (that represent regular money), which can be programmed to expire at a specific time or when certain conditions are met. A whole array of strategies can be created with this technology. For example, imagine a UBI token (representing $200) which vanishes if not used by the end of this month. This ‘use it or lose it’ feature would ensure that people would spend their UBI income (thereby stimulating the economy), since this would make the UBI generated money impossible to save

Proposal 2: Money Programmed for Certain Goods & Services

Rather than providing money, governments could provide tokens that represent a basket of critical goods and services which each person is entitled to every month. Each person would be free to claim the goods and services each month, or not to. This already exists in many forms (for example, like food stamps in the United States).
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Categories of programmable tokens would be innovative because: 1) the funds would be fully digital and could be spent by cell phone (no need for cash or bank transfers, credit cards, or physical stamps that could be lost or destroyed), and 2) the basket would be divided into categories of goods and services (those in each category would be redeemable by corresponding tokens). For example, imagine three categories of coins. The first category is green coins, which can only be spent on rent and associated living expenses. The second category is red coins, which can only be spent on food and beverages. The third category is yellow coins, which can only be spent on medical and other health-related expenses. A government could then decide how many units of each category to dispense to each person each month.

Proposal 3: Tax Benefits for Merchants Accepting Programmed Money

Governments and people have incentives to experiment with new markets, tools, and contracts to help achieve a functional UBI. However, we also need to get providers of goods and services on board: if not properly implemented, either of the above proposals could create black markets for unused currency. It is thus important to ensure that colored money is only spent directly at trusted vendors or at authorized locations (and cannot be transferred to other parties).

Trusted businesses providing these basic goods and services and accepting programmable and/or colored money in return should be given incentives to participate in UBI experiments and pilot programs. These incentives could come in the form of a tax break in a magnitude proportional to how many colored coins are received.

​Programmable money can be used by designated cards or even mobile devices.

These are my initial thoughts. I encourage readers to build on these, experiment with them, mix and match, combine them with other ideas, or come up with better, novel ideas

​Populist politicians around the world will soon follow Italy’s lead in promising UBI. Public confidence in financial institutions, media companies, governments, healthcare companies, and the judicial system is very low worldwide. The next economic crisis could create a perfect storm for populism.

The populists are tapping into a legitimate grievance. In many ways, the world has never been better:

• New technology is steadily making clean energy production and distribution possible
• Scalable water purification technologies exist
• Precision farming technologies and advances in biotechnology are bolstering food security, even as we have already achieved an annual massive surplus of produce
• Advances in genetics are creating tailored, personalized medicine
• Human and algorithm-assisted intelligence is abundant
• Vast computing power exists, and quantum computing is on the horizon
• The internet has dispersed information broadly and democratized learning
• Many parts of the world have liquid capital markets
• Scientific research grants are available in almost every country

Given these achievements and positive trends, it is reasonable to ask why so many people in the world live in economic anxiety, and worry about meeting their basic needs.

It is time to proactively explore the impact of a possible UBI on economic incentives and poverty.

I love technology. I am passionate about the infinite possibilities it will help us unlock. But it is a double-edged sword. It could destroy hundreds of millions of jobs in the next few decades. We need to take a proactive approach to plan for this contingency.

​I encourage people to take any of the ideas presented in this essay, play around with them, build upon them and work to better understand the UBI puzzle.

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Shaan Ray
​​                                                                ​                                                                ​                                                                               

​Advances in computing require appropriate hardware. Though computers have become smaller and more powerful over time, the power of regular computers (also known as classical computers) is limited.

​Quantum computers are a new generation of computers built to solve the problem of exponential scaling (for example, finding the optimal solution to a problem in which there are too many possibilities for a classical computer to analyze).

Classical computers have many components (including main memory, arithmetic unit, control unit, and others). They represent, process, and control data through these components. Computer chips contain modules, which include logic gates, which in turn include transistors.

A computer module is a collection of electronic circuits on a circuit board. The logic gates are tiny computers within the computer itself. They look at two bits and push one of them out as an output. Their job is to read any input, in order to produce an output. A transistor is a switch that either allows or denies information to pass through it. The combinations of the logic gates form modules that allow for the basic functions of a computer. If we think of the transistor as an electric switch, the electricity is moving from one place to another when the switch is on. If the switch is off, then electrons are blocked.

Computer components are getting smaller. A typical scale for transistors today is 14 nanometers, which is 500 times smaller than a red blood cell. As these transistors decrease in size, electrons can move to the other side of a blocked passage, resulting in it not being blocked at all. This process is called ‘quantum tunneling’, and it is slowing down our technological progress.

Our computers are based on a binary system (also known as a base 2 numeral system), which uses 0 and 1 as bits. A bit, derived from ‘binary unit’, is a unit of information for a computer that holds the values of 0 or 1. For example, a 64-bit computer can work with 64 binary numbers at a time.

Combinations of these bits are used to represent more complex data and operations. The logic gate performs a Boolean function, producing a single binary output. Boolean logic is a division of algebra that is used to create true and false statements. Since classical computers operate in binary, their logic is expressed in Boolean terms. The computer uses operators such as AND, OR and NOT to express the value and return a true or false output. For example, if you have values for x and y and the logical expression states x AND y, the computer would return true if both are true, while if it said x OR y, it would return true if at least one were true.

An easy programming example, minus the programming language would be: 

x = 2, y = 4

x AND y are greater than 1: this would return true.

x OR y are greater than 2: this would also return true, as y is greater than 2.

In a classical computer, a true statement could (for example) return a value of 1, while a false statement could return a value of 0. This forms the basis of classical computing: though most calculations require more than one simple true/false statement, classical computers are large combinations of these binary statements. This is what everything from clicking a mouse to opening a browser rests on.

For certain problems that a classical computer solves, you may need a very small number of logic gates. However, if you want to find the factors of an extremely large number, it is going to take a large magnitude of logic gates (which that a classical computer will not have).

A quantum bit, known as a qubit, is a computer bit that is able to hold two different states at once, meaning that it can hold a position of 0 and 1 at the same time. A regular bit can only hold one of the two at a specific time.

A qubit can be any two-level quantum system - a spin and a magnetic field, or a single photon (particle representing a quantum of light). This system’s possible states are 0 and 1. Within the quantum realm, the qubit can be in any proportion of both states at once; this phenomenon is called superposition.
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Superposition allows quantum computers to analyze far more possibilities than a classical computer. As soon as you test the value of the photon by sending it through a filter, it needs to decide on vertical or horizontal polarization. You cannot predict if it will decide on position 0 or 1. When in superposition, the photon is in some combination of both 0 and 1 simultaneously. However, as soon as you measure its value, it collapses into one of the defined states.

​Think of 4 bits that can be on or off. Such a system would have 2^4 (so, 16) possible combinations. In a traditional setting, you can use only one of these. However, qubits could hold all of these 16 combinations at once. This number grows exponentially with every added qubit. 

​Qubits can hold the property of ‘entanglement’, a close connection between qubits that allows them to react to a change in the other’s state instantly no matter how far apart they are. Therefore, when measuring one entangled qubit, you can directly conclude the properties of its partner without having to test it. 

​As a traditional logic gate receives a simple set of inputs, it produces one definite output. The quantum gate manipulates an input of superpositions, rotates probabilities, and finally produces a determined state as its output. To break down the steps, a quantum computer:

1. Sets up qubits
2. Applies qubit gates to entangle them and manipulate probabilities
3. Measures the outcome, collapsing the qubits into one defined state: a sequence of 0s and 1s. This means no more superposition.

This way, all calculations in the setup are done at the exact same time.

​The essential power of a quantum computer is that you can consider many states simultaneously. In order to make it work, its algorithm must be able to produce an end state that is readable (so, the information that you read out at the end cannot have superpositions). This means that quantum computers require a more complex algorithm design to be useful.

Quantum computers will most likely not replace our home computers. However, they can be superior in areas such as data searching. To find something in a database, a classical computer must test every one of its entries. A quantum computer will take the square root of that time to come up with the same answer.
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Quantum computers can challenge existing IT security measures. Currently, data is protected by various levels of encryption. In this case, you can give everyone a public key to encode messages only you can decode. While technically this public key can be used to calculate your secret private key by the use of trial and error on a classical computer, it would take far too long to be worth anyone’s time. A quantum computer with exponentially higher speed will be able to do it much faster.

Example 1

You have a 10 person dinner party. You need to figure out how to seat everyone. There are 10! = 3628800 ways of doing so (where ‘10!’ is pronounced ‘ten factorial’ and represents 10x9x8x…x1. A classical computer will have to go through each of the 3.6 million ways individually and then compare them to figure out the best optimization.

​A quantum computer would:

1. Take the qubits and go into a superposition of all possible states and configurations
2. When this problem is encoded into a quantum computer, the encoder applies a phase on each of the states. When the ways are in phase, the amplitudes add. When they are out of phase, the amplitudes cancel. This is a similar idea to noise cancelling headphones, which create noise to phase out outer noise.
3. You use interference to amplify some answers, while cancelling the others, finally approaching one answer.

Example 2

Here we have a maze. Imagine you are in the center of it and want to get out at either of the two exits. You can start exploring each path, one by one. After a lot of tries, you will finally get out of the maze.
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Now, imagine you have with you several clones of yourself. Everyone can start exploring the different ways, and one clone will directly find the correct way out. You and your clones were exploring all the different paths at once, meaning that you were all in different places at the same time. You were in a superposition of states, like a qubit. This allows you to find the best solution possible, quickly.

These simplified, conceptual examples help explain why quantum computers (when created) will be immensely helpful in solving large, complex problems.

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Shaan Ray
​​                                                                ​                                                                ​                                                                               ​

Lidar technology is mainstream again, because of its use in self-driving cars. Lidar has been tremendously useful for decades now, in discovering mining sites, predicting earthquakes, mapping disaster areas before search and rescue operations, and measuring cloud density at airports. This article will dive into where Lidar came from, how it works, and how it is used in autonomous vehicles today

Lidar (short for ‘Light Detection and Ranging’ technology) is a technology used to detect, range, and map its surroundings. It is similar to radar and sonar, but uses light beams. Light has been used as a measurement tool since at least the 1930s, when light beams were used to measure cloud distances. Lidar was created in the 1960s and entered the public imagination when it was used by the Apollo 15 crew to map the moon’s surface.

​A Lidar machine consists of a laser pointing downwards from an aircraft and shooting up to 400,000 pulses or beams per second. The machine then uses active sensors to measure the energy of the reflection it receives. The resulting map of the surface below can be accurate to a within a couple of inches, and is called a ‘point cloud’. Lidar works naturally with GPS, since mapping requires both measurement and positioning. Lidar planes map small segments of land by flying in a pattern over the target area in grids.

​Lidar is useful for creating topographical maps. Archaeologists have used it to discover Mayan buildings covered by vegetation in the Central American rainforest. It has also been used to determine ocean depths in shallow areas near land (using two lasers: one for the water’s surface and one for its floor).

​Luxury car manufacturers have long used Lidar for Cruise Control mode (which allows a car to maintain a certain speed while the driver still pays attention to the road), by mounting a sensor to the front bumper to measure changes in speed and to look out for erratic movements in the cars ahead.

​In 2005, German company Sick AG won a DARPA Grand Challenge by mounting five Lidar units on its vehicle. The Grand Challenge included self-driving cars and teams from around the world. The cars were put through a series of tests, like driving in traffic, merging, parking, passing others, negotiating traffic, and performing more complex maneuvers.

​Another participant in the Grand Challenge was Dave Hall. Hall had grown bored of running an acoustics company that specialized in subwoofer technology. So, he turned his attention to self-driving cars. In 2007, Hall created a 3D Lidar of his own by packing 64 emitters into a flattened round device on top of his car. The emitters and the on-board computers gave him a precise picture of his surroundings. Hall adapted his prototype for commercial use, and his company released the Velodyne PUCK Lidar sensor (which has since gone through a number of upgrades).

Despite Lidar’s use in obstacle detection and avoidance systems in self-driving cars, it cannot function on its own. (For example, Lidar cannot read traffic signs or comprehend traffic lights.) It is instead used in concert with other sensing systems, including radars and visual cameras. The sensing systems then work with onboard computation to navigate the car.

​Thanks to advances in computing power, data storage, and machine learning, Lidar-enabled systems can now differentiate between bicycles and motorcycles, and between children and grown-ups. This allows self-driving cars to understand the flow of traffic and people at a more granular level.

So far, a Lidar system (a laser and a sensor) has had to rotate to scan a surrounding area, making the system either large or expensive.

​The recent advent of solid-state Lidar, in which the entire system rests on a silicon chip and does not rotate, has allowed for the twin benefits of more compact systems and more accurate readings. Solid-state Lidar systems are also more durable, which is key for self-driving car manufacturers. So, car manufacturers are paying more attention to emerging solid-state Lidar companies, such as Quanergy and LeddarTech. This year, BMW announced that it will use solid-state Lidar in its self-driving car efforts.

If Lidar technology continues to improve rapidly, companies will be able to offer stationary, compact, and durable Lidar systems for very low prices. Lidar will then become indispensable — not just to self-driving cars, but also to drones and robots.
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Shaan Ray
​​                                                                ​                                                                ​                                                                               ​

If adopted, the proposed ERC-1190 Ethereum standard could have important applications for creative rights and digital assets.

ERC-1190 is a non-fungible token for royalty payments. Non-fungible means that each token represents something unique, such as an image or a song. (See the code on Github).

Imagine creating a sculpture or a gaming object, which you now want to share with the world. The proposed token would allow you to share the artwork and to profit from it by easily keeping track of any revenues generated from it. Specifically, an ERC-1190 token would allow you to sell the art’s creative license, sell its ownership license, or to rent it to a third-party for a fixed period of time.

This article will outline how the proposed ERC-1190 token standard can help artists focus on creating art, while reaping the financial benefits of their artwork passively.

Put yourself in the shoes of an emerging painter. You can showcase your work at some of the thousands of art shows around the world each year. With talent and some luck, your paintings could be exhibited at an exclusive art fair, such as the privately-owned Art Basel, which maintains an excellent regional and global profile and showcases works for sale by both established and emerging artists. You would like to sell one of your paintings to the highest bidder.

​In ERC-1190 terms, you own both the asset’s creative license and its ownership license, and you would like to sell its ownership license while retaining the creative license. The buyer of the ownership license would be entitled to possession of the painting and most of the revenues from any future sales. However, the creative license you retain will ensure that you receive a fixed percentage of any revenues from future sales (for the example at hand, let’s say the creative license entitles you to 10% of revenues from any future sales).

Using an ERC-1190 transaction would not necessarily bypass the traditional method of selling artwork. For an emerging artist, a buyer would likely want to see a work of art before buying it. A more established artist may be able to conduct an auction on the blockchain alone.

​Let’s say you sold your painting to the highest bidder at a traditional art fair, but recorded the sale by transferring an ERC-1190 token representing the artwork. Recordkeeping for the sale and for any future movements of this work of art and any revenues received from them is now easily accessible to you on the blockchain.

Now, let’s say the buyer of your painting sells it to an international marketing agency at a markup. As the creative license holder, you are entitled to 10% of the revenues. If the sale to the marketing agency is conducted on the blockchain, you would receive the funds seamlessly (without even knowing about the sale). If the sale is conducted in a traditional setting but recorded on the blockchain, you will be notified on the blockchain and will have a right to claim 10% of the revenues from the recipient. Use of the ERC-1190 would therefore remove information asymmetry and contracting friction, benefiting artists

The international marketing agency now rents your painting to an event company for a week. The event company will display it at a multilateral political event. The rental license associated with the ERC-1190 token will show this rental, its time period, and its price. The holder of the ownership title will receive the majority of the rental income. However, as the holder of the creative license, you will get a percentage of this rental revenue as well.

An established artist’s work often appreciates in financial value over time. Art collectors and art investment companies commonly hold artwork as an investment. This art is not placed on walls or displayed. Rather, it is stored in a secure location. Sometimes, even when the art is sold, the only thing that changes hands is the ownership documentation, and the art remains stored in the same location.

​In these cases, using an ERC-1190 could open up this market to anybody by conducting sales entirely on the blockchain, reducing the roles of private auction houses and word-of-mouth sales. This would benefit art collectors (by giving them a more liquid market for sales), art enthusiasts (by allowing them to buy art more easily) and artists (if they hold on the creative license, they would be entitled to revenues from future sales)

Until now, this article has only considered situations in which the artist holds on to the creative license. The artist also has the option of selling the creative license. Once the creative license is sold, the new holder of the creative license would receive a cut of all future sale or rental revenue.

​Due to the fragmented nature of the art world, it often takes decades for talented artists to become known. Indeed, several of the best known artists today were not appreciated in their time. For example, Vincent van Gogh was poor and virtually unknown when he was alive. His work was not widely viewed or appreciated until after his death. It wasn’t until after his death when people started to view and appreciate his work. Last year, a single van Gogh painting sold for $81.3 million.

Using an ERC-1190 token, an artist can bequeath their creative license to future generations even if they have sold the ownership license (and therefore no longer own the underlying work of art). If someone in van Gogh’s family or town held the creative license to one of his paintings today, they would receive significant revenues every time that painting was sold or rented.

ERC-1190 could allow artists to focus on creating art while knowing their financial interests are protected. Those who collect, trade, market, display or appreciate art could also focus on what they do best, and benefit from secure transaction records and more accessible, liquid markets.

***
Click here to check out the code.
Click here for another explainer article.
Click here for a brief, simple explainer video.
The ERC-1190 token standard has been proposed by Aalim Khan & Shaan Ray.

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Shaan Ray
​​                                                                ​                                                                ​                                                                               ​

A hashgraph is a patented algorithm that promises the benefits of the blockchain (decentralization, distribution, and security through the use of hashing) without the drawback of low transaction speed. It was created by Leemon Baird and is the intellectual property of the Swirlds Corporation, which Baird founded.
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While Bitcoin allows for approximately 5 transactions per second and Ethereum allows for approximately 15 transactions per second, a hashgraph can process thousands of transactions per second. This article will discuss how the hashgraph works and if it could rise as an alternative to the blockchain

The hashgraph algorithm operates through two techniques.

The first technique is used to share information and is called Gossip about Gossip.

To understand how it works, imagine five members: A, B, C, D, and E. Each member starts with a transaction, which results in an ‘event’. Then, each member calls another randomly selected member and the two share their transaction history. For example, D calls B and shares D’s transaction history with B. This type of call happens repeatedly, with each member randomly calling another member and sharing its transaction history. So, B now randomly selects another member (let’s say C), and shares its transaction history, which includes D’s transaction history. Simultaneously, E may have called A, and so on. Each call results in an event, and each event holds the hashes of all previous blocks.

The graph of these events looks like a tree:

The second technique of the hashgraph is Virtual Voting, and its purpose is to reach a consensus on the order of transactions. Here’s how it works: first, the events are divided into rounds. The hashgraph algorithm has a definite mathematical answer for when a round is created. Here, for the sake of simplicity, imagine that a round has approximately ten events. Now, each member votes to determine which event should qualify as a ‘famous witness’. To understand how this happens, imagine that each of the members with an event in the next round looks backwards to each event in the current round to see if it can trace its lineage back to the current round’s event. If it can trace its lineage back to an event, it votes yes for that event, and if not, it votes no. The current round event with the most votes is crowned the famous witness for the current round, and provides the definitive order of transactions

As discussed earlier, the hashgraph algorithm has one major advantage over blockchain technology: speed. However, the hashgraph is used in a private, permissioned setting. Anybody can join Bitcoin, Ethereum, and other major public blockchains as a node. On the other hand, each node on the hashgraph has been approved by the network’s administrator. Additionally, unlike the number of nodes on a blockchain at any given time, the number of nodes on the hashgraph is known by the network. Therefore, each node’s identity is known, and can be trusted. This is why the hashgraph is so fast.
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However, critics note that it is unfair to compare the speed of the hashgraph algorithm and blockchain protocols, since many of the latter are public and permissionless

The Hedera Hashgraph project is the most prominent effort to open the hashgraph algorithm to the public. Swirlds has licensed the hashgraph algorithm to Hedera Hashgraph. Swirlds will receive a 10% licensing fee from Hedera Hashgraph’s revenue.
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By creating a public network, Hedera Hashgraph will lose the speed advantage of a private, permissioned setting. It will compensate for this by adopting a consensus mechanism that is very similar to the Delegated Proof of Stake mechanism, which I wrote about earlier. The network will be governed by a council of 39 trusted members, from various industries and geographies

The hashgraph is an innovative new take on using decentralization and hashing to create a fast, distributed ledger than can process thousands of transactions per second. Though the hashgraph is a patented algorithm used in private, permissioned environments, the Hedera Hashgraph project seeks to create a public hashgraph network that it will open to developers. In adapting the hashgraph algorithm for public use, Hedera Hashgraph adopted a consensus mechanism that is similar to the Delegated Proof of Stake mechanism on the blockchain.

​Once up, Hedera Hashgraph’s network will be governed by a trusted council and will offer the ability to create decentralized applications using Java. These traits will likely attract interest from enterprise users and crypto enthusiasts alike.
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Shaan Ray
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The multi-billion dollar video game industry is booming: it is growing at several times the rate of the overall economy. The industry generates revenues from gaming content, in-game purchases, and hardware and accessories for better gameplay. Games are played on computers, mobile devices, and dedicated gaming consoles.

Games can be organized by gameplay characteristics, objective type, and subject type (for example, sports, action, or racing).
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This post seeks to provide non-gamers with an overview of the industry’s most commonly used abbreviations: FPS, RTS, MOBA, RPG, MMO, and MMORPG (among others).

Action games are currently the most popular genre of games, and FPS games form the most popular sub-genre within action games. FPS games feature three dimensional environments and are centered around weapon-based combat in the first-person perspective (so that the player sees the environment as the character would see it).

​TPS or Third Person Shooters are similar to FPS games, except that the player views the character they are controlling from behind.

In MOBA games, the player controls a single character in a team, which competes with other teams in an environment. The objective is usually to destroy computer-generated entities and to defeat other teams in the environment. In most MOBA games, each player assumes a specific role on the team. Various roles exist in these environments. For example, ‘support’ roles provide peripheral assistance to a team and its allies, for example by distracting or slightly harming enemies while the central members of the team fight them.

MOBA games are a fusion of action games, role playing games and real time strategy games. MOBA is often referred to as ‘A-RTS’ or action real-time strategy, though ‘strategy’ in this case refers to how a team collaborates and plays the map to succeed.

In RPGs, a player controls the actions of a character in a well-defined fantasy or science fiction universe. Players can often do things that are not possible in real life. The aim is usually for the player to complete a series of quests to reach the conclusion of a central storyline. In these environments, character development occurs through narrative elements and storytelling. Most RPGs include comprehensive 3D experiences.

MMO games usually feature enormous persistent open worlds and have thousands of users playing on the same server. These games require network-capable platforms such as smart phones, computers, and internet-connected game consoles.
In MMOs, players can cooperate and interact with one another on a large scale. There are MMOs across a range of different gameplay types and genres. MMOs can be FPS, RPG, or RTS, across fields as diverse as combat, sports, racing, social, and others

MMORPGs are a combination of MMOs and RPGs. They feature very large numbers of players interacting with one another in a constantly open virtual world.
The player assumes the role of a character and can collaborate or compete with other players in the game’s persistent world. The world continues to exist and evolve while the player is offline or away from the game. Popular MMORPGs are based on fantasy themes that include elements of crime, sorcery, and science fiction. Some MMORPG communities have developed their own sub-cultures that have their own slang, influencers, and social rules.

As the video game industry continues to grow rapidly and globally, these game genres will continue to evolve. As computing power grows and as virtual reality and augmented reality technology becomes mainstream, more complex gaming environments will become possible.​

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Shaan Ray

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