The Supermoney Highway Needs On-Ramps

Can we build an on-ramp into blockchain that doesn't need a third-party to validate a user's identity?

We like to think of blockchain engineers as highway builders. We spend a lot of time worrying about the stability and scalability of our highway, and also how fast you’ll be able to go (send money), and what kind of vehicles (smart contracts) you’ll be able to drive. Unfortunately, we often forget about “on-ramps”, or ways to actually get on our highway. We forget how to get average people outside of tech to actually join our network.

Often, I speak with dApp owners who are only concerned with raising funds to cover technical costs. Generally, they want to operate their currency like a company, specifically by holding a pre-sale (or “ICO”) of an initial percentage of their currency, similar to seeking venture capital when starting a business. But currencies aren’t stocks. You can’t create a currency with an unbalanced initial distribution of wealth and expect people to want to join later on. Your goal should be to first build something desirable. Then, you should put your currency in the hands of as many people as possible. A highway is useless without drivers, and drivers can’t drive without gas.

 

In the U.S., the best way to get your hands on any cryptocurrency is to link your bank account to Coinbase, and wait 5 days for a bank transfer to convert your dollars to bitcoin. For the tech-averse or financially-privy, exposing personal details about one’s bank account to a third-party is a significant deterrent to adoption. Not only that, for a community that prides itself on limiting third-party risk, it’s somewhat unusual (and risky) to have one company tracking the financial records of nearly every professional crypto user involved.

 

There are other ways to obtain cryptocurrency aside from buying through Coinbase, but frankly they’re even more cumbersome. One way is by mining, but again this is not for the tech-averse. Another, newer way to earn currency is through a coin’s budget system. Typically every month, coins with a budget system will make a billboard list of tasks, such as coding or online marketing, that need to be accomplished by the end of the month. Users can sign-up to complete these tasks and if succesful, they receive cryptocurrency as a reward. In a future iteration of Project Oblio, every privileged person will be assigned one monthly task to accomplish.

 

On Project Oblio, one of the primary ways to receive value is by providing data from consumer EEG devices and/or Vybuds. The biometric aspect of this type of data ensures that the data is authentic, i.e., that it hasn’t just been copied and pasted from a previous submission.  This data has practical use cases within its features, including  neuromarketing and mental self-improvement.

 

Project Oblio is really a decentralized, crowd-sourced neuroscience experiment. Using data taken while performing tasks during EEG or tACS-like sessions, we can evaluate the effects of  leading neuroscientific techniques on improving memory, depression, and other mental ailments. Additionally, data that is recorded while watching TV shows, movies, or advertisements can be used to evaluate a user’s interest in cultural content or a product. This means musicians, filmmakers, and advertisers can have an objective metric over how much a user enjoyed their content. While review sites like IGN, IMDB, and Amazon often have third-party markets selling positive reviews, Project Oblio intends to have every review backed by spiritually-derived data. An experiment like this is the next obvious step for decentralized systems, because incentives for data can both improve a network’s quality while also laying out on-ramps for the average user.

 

When people want to join the “Information Superhighway” (better known as the internet), all they need is an internet-connected tablet, phone, computer, Alexa, or thousands of other devices made by thousands of manufacturers. When people want to join Project Oblio, they will need a consumer EEG or  a pair of Vybuds, which can themselves be used for tons of other things outside the network as well.  It might be the missing ingredient for a currency-like system to have an engine running off products that perform useful work for a user outside the actual currency system, so that a user can not only earn value with significant potential, but also better themselves. That is, for a currency to become popular, it should have goals of improving something other than the thickness of its initial investors’ wallets. It should have tenants that extend beyond the realm of corporate ideals.

Vybuds are ready to be manufactured, but venture capitalists don’t get it. We need money from the community to manufacture them!

Reigniting The Computational Arms Race

How can neuroscience research help fund research into new AI chips?

Bitcoin’s initial pitch was as a network where donated computing power would lead to the end of botnets, spam, and other malfeasance the internet had spawned. The idea was that instead of using their computing power for nefarious means, people with large amounts of underutilized computing power would be able to redirect their processors towards securing the bitcoin network, in return for a tangible financial reward.

As bitcoin mining became more profitable, what ended up happening was more akin to a computational arms race. Graphical processing units (GPUs) quickly became the weapon of choice over traditional CPUs in the ever-prospering bitcoin mining industry. Because GPUs are used by researchers in medicine, aerospace, and practically any field of science where there is large troves of data (i.e. everything), there was a brief moment in bitcoin’s history where it was doing tremendous good for the world. Research and development in faster processing cards for bitcoin mining was trickling down substantial benefits for poorly funded areas of clinical and other research.

That all changed with the advent of ASICs – dedicated hardware for bitcoin mining. Because bitcoin’s mining algorithm is relatively simple, and does not rely inherently on machine learning, as a single bitcoin became worth tens to hundreds of dollars, wise investors started developing power-efficient computer chips that could be used only for bitcoin mining. Bitcoin’s arms race had reach its full potential, but it was no longer doing good for the world outside of bitcoin. Sadly, a mining market that had once shown potential for improving nearly every big data problem faced by mankind, was now suffocated by the flow of capitalism.

Because Project Oblio is a network that rewards people for correct answers to a machine learning task, it is possible for us to re-ignite the computational arms race first started by bitcoin. Early on, Project Oblio will likely run on the same GPUs  that once propped-up bitcoin mining. However, as the network becomes more useful and thus valuable, we can expect custom-made “neural network hardware” to reach the network due to its increased profitability in mining oblios. These same cards can also be used in more general machine learning tasks, performing much better than GPUs, when conducting analyses in the less-well-funded scientific  areas described earlier.

Thus, an investment in Project Oblio is a long-term investment in big data technology. When you support the network, you are supporting all areas of science that analyze big data – cancer research, population health, self-driving cars, etc. A computational arms race that drives machine learning hardware research is something few other systems like Project Oblio can offer.

dApps: More d, Less Fee

The unfair releases and pyramidal wealth structures of previous cryptocurrencies has led to more expensive fees for developers than should currently exist.

The blockchain of the future will not be the one that raises the most capital initially. It will be the one that reaches as many hands as possible.

A new wave of blockhain developers means a new market opportunity for existing cryptocurrencies. By far the most effective crypto at recruiting new developers has been Ethereum (and more recently, EOS). With buzzwords like “dApps: decentralized applications”, “smart contracts”, “initial coin offerings”, and a number of other  side projects, it can be difficult to find any reason to doubt the churning machine that is Ethereum (and now, EOS).

Ethereum sold  roughly 85% of its total supply to 5,000 investors in a small, not widely advertised pre-sale. EOS did the same, and people bought it, WTF. While there are a lot of subjective reasons why we believe this pre-sale will poison Ether and EOS over the long-term,  there are real, objective consequences to this pre-sale that a number of new blockchain developers who I speak with are unaware of. This pre-sale has created a significant barrier to entry into the world of Ethereum smart contracts, but you likely won’t read anything about it until you’ve already prepared to launch your coin.

 

Unlike what many of the Ether and EOS docs imply, dApps aren’t just regular applications hosted in a “decentralized” way. When you run a regular application, generally you have one dedicated server, sized perfectly to your company’s needs and running code with minimal financial repercussions. Obviously, you can modify this code without an additional fee, because it’s on a server you control. On a decentralized network, however, even simple server modifications need to be propagated across thousands of nodes. For the purposes of application development, think of each node as a server. Instead of having just one server, you have 1000s – which means every change you make costs money in the form of Ethereum fees.

Computationally, and thereby, financially, a simple change to a database should be 1000s times more expensive in a dApp then in a regular database. On a network where wealth is evenly distributed, this price increase actually isn’t that bad.

But on Ethereum, wealth is not evenly distributed, not in the slightest. Instead, simple database changes carry fees with them, often in the range of $0.50 to $2.20, with similar fees for modifying your code. Developing for Ethereum is REALLY expensive – even more expensive than it should be if we were to run 1000 servers ourselves.

Ethereum is more expensive than it should be because its pre-sale has created an environment where there is an unsustainable distribution of wealth in the underlying protocol’s coin. Companies that raised hundreds of thousands of Ether in their pre-ICOs are prioritized by the network’s fee system over newcomers. Consider that raising $10,000 in Ether today might only cover fees for 5,000 of your dApp’s database changes, while $10,000 raised during the Ether pre-sale would cover roughly 60,000,000 database changes for your competitors. Although these competitors may have an application that serves a different purpose than yours, they are still your competitors on the Ethereum network for things like processing time and strength of computation. If your app shows any measure of profitability, these existing wealth structures have the power to fork your product and resell it in a much more efficient manner, because they have orders of magnitude more ether than you.  Whoever can pay the higher fee to the decentralized structure owns the network, and Ethereum, with its quiet pre-sale of more than 85% of its total supply, is insanely more unbalanced in its wealth structure than any other open financial system on the planet.

 

 

The unfair wealth structure has created a fee structure that is unsustainable. While 0.01 Ether is dust to older companies who bought in early, it’s a significant barrier  to innovation for new ones. The hoarding of Ether causes an unnecessary fee spike among the active older smart contracts that prevents new ones from taking hold.

 

Pre-sales, and more broadly private-turned-public blockchains, are bad for everyone because they limit long-term adoption of the network. They are a bad business decision financially because they don’t take into account secondary and tertiary growth phases – two phases that a cryptocurrency has yet to achieve. The blockchain of the future will be the one that touches as many people as possible, not the one that raises the most capital.

 

 

For a blockchain-like system to last, it needs a fair distribution of wealth — or at the very least, one that consists of far less than 80% of a coin’s total supply. Ideally, the network’s wealth grows proportionally to each new identity on the network. Each identity can receive only one “new member” bonus, although on traditional blockchains, this can be difficult to enforce.

 

Being able to recognize each new member as an individual provides a new way of thinking about blockchains, which is why Project Oblio is built on a spiritchain, not a blockchain. Each human spirit contains a unique, bioelectric human aura that Project Oblio utilizes in constructing the network. Read more about our protocol here.
Pre-existing smart contract blockchains have a lot of capability for sandboxing. But most reasonable people outside of crypto don’t want to join an “old boys” club of wealth, especially when they don’t have a financial incentive to. And if developers can’t afford to innovate on your network, that’s even worse.

 

UPDATE (03/22/2018):

The Ethereum developers have begun working on the Rinkeby test network, a scalable network similar to Project Oblio, with the exception that only a privileged number of persons (based on online identities) are allowed to confirm transactions. Because these identities are based on online accounts, they can easily be faked, meaning a person or group of people financially incentivized can easily overtake the network (as we’ve seen with fake news on Facebook, etc.). Using the Rinkeby network without a live biometric to confirm each user is a BAD idea for developers.

 

UPDATE (06/24/2018):

Block.One raises $4.3 billion and locks exchanges from withdrawing/depositing EOS. Then the markets crash.

Perhaps the “ECORP” of crypto is not as much Ethereum as it is EOS. EOS used its connections to Steemit to maniuplate an undereducated blockchain populace into effectively investing in nothing — no guarantee for developments, no guarantee for anything except a market crash (at least initially).

Ethereum set the precedent that basically allowed everything in this blog post to come true, in the form of EOS.

A Bot Tax: Scaling For the Average User

Real, human users should be able to transact for free. Unlike EOS, which rate-limits transactions at the smart-contract level, Project Oblio aims to rate-limit transactions at the user-level.

Every cryptocurrency to date has, at some point, garnished claims about the internet-of-things, machine-to-machine payments, and easy-to-use APIS for sending stores of wealth. Often, it only takes one or two lines of code to send a transaction, resulting in large amounts of automated payments between exchanges, wallets, and advanced users. However, these kinds of payments are actually a bigger problem for cryptocurrencies than one would initially expect. Because these transactions are taxed at the same rate as the occasional transaction made by a “new” or casual user, they end up clogging the network, causing increased fees, tremendous block sizes, and relatively simple and inexpensive attack vectors, such as DDOS. For this reason, you’ll often see bitcoin developers talking about “anti-spam” measures to limit these excessive automated payments from disturbing the user experiences of a newcomer. A bad user experience is a barrier to adoption, and this barrier to adoption is bad for everyone, as it ultimately harms the returns of the businesses using the network so much.

 

Through its one-human-one-vote protocol, Project Oblio aims to allow for reduced fees to those members who are well-identified by the network, through a “Karma” metric. More specifically, transactions are prioritized when a user is “liveness detected” – proven to be actually there, needing a transaction to be sent as quickly as possible. Although machine-to-machine payments are necessary for network function, they greatly stress the decentralized network protocol. Prioritizing transactions in this manner can allow for a better end-user experience, while still allowing businesses and other machine-to-machine payers to function. Ultimately, it encourages real user adoption.

 

Because so few transactions sent on networks like these are initiated by humans, it is unlikely that fees for bots will be greater than that of competing networks. As such, the bot tax is really better thought of as reduced fees for live humans, rather than any deterrent against machine-to-machine payments.

 

Of course there are a lot of reasons to have machine-to-machine payments, but there are better reasons to create a garden of the internet which is provably human. Namely, real discussions, real voting, and real applications for BMIs.

 

Most scaling protocols to date have focused on payment channels, which are themselves a great idea, and will one day be implemented on Project Oblio. But payment channels won’t be useful for one-time payments and other types of transactions an end-user may wish to make. Really, to create a decentralized network that is used by the masses, it is much more important to first solve the issue of one-human-one-vote, so that we can, among many other things, favor real-world users over anonymous bots.

Defending Against Hired Fake Accounts

Mercenary fake accounts have driven altruistic coders from the cryptocurrency community. Can we re-inspire the lost population of altruistic developers with a watering hole prohibiting financially-incentivized mercenary accounts?

The most underrated threat to society today is the threat of artificial intelligence, but not in the manner you might expect. Movies like iRobot concoct an image of actual robots turning on society. More reasonable portrayals in the media and among tech leaders convey the very real threat to persons’ employability by intelligent machines. One such threat rarely discussed is the loss of freedom-of-speech on digital watering holes, due to hired “socketpuppet” accounts, including those controlled by mercenary A.I.

Why should we be scared of A.I. pretending to be humans on the internet? Because in industries like cryptocurrency, it’s already been happening. The difference between fake accounts now and 10 years from now is that fake accounts today have to be controlled by humans (see www.reddit.com/r/HailCorporate). These “astroturfers” can make you think a product, government public comment section, or news article is more deserving of your attention than it actually is, by means of pretending to be multiple users sharing a single consensus. While today these are probably just hired humans controlling multiple accounts in a clickfarms, tomorrow cheap computer programs running simple machine learning algorithms will allow everyone and their grandmother to pollute the internet’s discussion boards with fake consensus. We need an area of the internet where we can be 100% certain that a human is a human, and they are who they say they are. This network works best if is decentralized, because decentralized networks do not rely on trust in a third party, such as a CEO.

A.I. is already capable of generating human text indistinguishable of that from human-generated language.

Please see “Brainwaves as a future-resistant biometric: Human detection, Identification, and Authorization” for more info.

Brainwaves as a Future-Resistant Biometric: Human-Detection, Identification, and Authorization

Brainwaves are the only biometric still untapped by governenments and corporations that possess fluid properties; Human-Detection, Identification, and Authorization. They are also a source of wealth.

“Human detection” is the act of proving whether or not an internet user is a robot, or a human. Google’s ReCaptcha2 (“I’m not a Robot”) is very convenient; It only takes about 10 seconds to complete. Unfortunately, the tasks required by Google’s reCaptcha are problematic for the following reasons:

  • These tasks are not future-proof. Eventually, A.I. will be smart enough to pass any image recognition task.
  • As Google trains their algorithms, they become the only ones with the algorithms capable of bypassing their own human detection protocols. They can then lease these algorithms to generate fake accounts. These fake accounts, paid for by a wealthy person or persons, or just a hacker, can be used to create a false sense of consensus on a discussion board regarding a government, product, or cultural content.

Project Oblio possesses a network component that is decidedly human-only. Transactions on this network can be decidedly human-only, as the network revolves around the idea that the most resilient form of human detection derives from the power of the human brain. Signals emanating from the brain and muscle areas around them are a cheap and efficient form of human detection, one that is vastly more future-proof that that currently implemented by Google.

Each of us is born with a multi-billion dollar supercomputer, capable of generating outputs immeasurably more complex than that capable of being understood by an A.I. For example, predicting whether a human will find something funny is much harder for A.I. than it would originally seem, even with plenty of data. This humor response manifests itself in an EEG recording, a piece of data that can simultaneously be conveniently monetized to the user on a decentralized network.  Common recording parameters like the P300 (a measure of whether a human brain has detected something “surprising”) are easily elicited over an EEG and probably just as difficult for a computer to simulate. Any form of human detection becomes significantly stronger when you’re simultaneously recording outputs from billions of live, biological neurons.

When we combine this type of human detection with transcranial direct current stimulation (tDCS: an “input” method, as opposed to EEG, which primarily records a brain’s output), we may get even stronger, faster human detection. Considering that tDCS has also been shown to improve memory, concentration, and relieve depression, it would seem to be the perfect technique for improving both inward and outward human communication.

Although non-invasive brain-machine-interfaces require a lot of data for most tasks we’d like them to be useful for (such as control of virtual reality), they are tremendously accurate at identifying us (like a “fingerprint”, but more accurate) with comparatively minimal data. While the more desirable tasks often have only 60-80% accuracy, identification of human beings by brainwaves can typically achieve 99% accuracy with minimal data. This is evidence that each brain and its corresponding outputs vary tremendously from person to person, and that collecting a lot of data from a single person is just as valuable, if not more valuable, than comparing data across persons. If you need more evidence for the uniqueness of human brains, check out the Human Connectome Project.

So. At this point we have two new terms: Human detection, and identification.It’s important now to realize that not only do human brains have tremendous power to human detect us, but they can simultaneously perform these two steps as well. No other biometric available can do this simultaneously, and it’s a crucial enhancement in a decentralized network’s stability. Fingerprints and DNA are both static – once you have the image or the code, it can be copied and used to impersonate you. Voice data is as fluid as brainwave data and could theoretically be used to human detect, but it is not as good at identifying you and is also (nowadays) easily forgable (see Alexa, Siri, etc.).  If data were easily foregable, a person could use the same data to receive multiple rewards, spamming the system and making themselves very rich (that is, until the markets crash due to the flaw they exposed in the network).

The last step in the three-pronged approach is authorization. While human detection is like reCaptcha, and identification is like a username, authorization is like a password. Authorization is as simple as you thinking a “password thought” recognized by a machine learning algorithm. There are tons of papers already out there about this, so I’ll point you to Google Scholar for this topic.

Combining these three methods: identification, authentication, and human detection, into a single protocol creates a triad of network security not found in other biometrics or in purely digital security. This is  interchangeably called “proof-of-person”, “proof-of-cognition”, “proof-of-humanity”, and “proof-of-individuality”. Its consequences are described further here.

Why re-distribute wealth?

Imagine a viral outbreak on a spaceship like Elysium — the ultra wealthy’s ideal future space home for the world’s 1%. If 95% of that ship are white, and it’s a contagion that affects 65% of white people (not an unreasonable number), how will the remaining 35% of people run the spaceship? If 2 out of 3 engineers on said ship are dead, how will society continue?

Biological diversity is the most valuable thing we as a species possess.  No other species possesses it to our degree, and it’s our one defense against an unknown threat: be it a viral contagion, global warming, or a meteoric invasion. That’s how life survived after dinosaurs, a biologically diverse planet found a way for life to persist. A community of diverse genes is good for everyone because those who have the lucky genes can use their good health to take care of everyone else.

Previous, small scale, studies have suggested that people of mixed race are perceived as being more attractive than non-mixed-race people. Here, it is suggested that the reason for this is the genetic process of heterosis or hybrid vigor (ie cross-bred offspring have greater genetic fitness than pure-bred offspring). A random sample of 1205 black, white, and mixed-race faces was collected. These faces were then rated for their perceived attractiveness. There was a small but highly significant effect, with mixed-race faces, on average, being perceived as more attractive. This result is seen as a perceptual demonstration of heterosis in humans-a biological process that may have implications far beyond just attractiveness.” https://www.ncbi.nlm.nih.gov/pubmed/20301855

One Person, One Vote: An Internet Democracy

A hierarchy is an organization where people at the top have more sway than people at the bottom. For many communities, this works pretty well. Take for example, academia. Would you prefer to be operated on by a neurosurgeon who graduated at the top of their class, or one who graduated at the bottom? Intuitively, people who are good at what they do should have more influence over their respective fields than people who don’t know anything about said field.

 

In communities defined by clear objectivity, hierarchies are preferred. But sometimes, even objective tasks are better suited for crowdsourced opinion. In The Wisdom of the Crowds, James Surowiecki describes the case of the jelly bean jar at the carnival. When collecting guesses as to how many beans are in the jar, often one person will turn out to be a half dozen beans off. However, the average of the entire crowd’s guesses will almost always be more accurate than one person’s best guess.

 

Look no further than cryptocurrency for an even more pertinent example. Bitcoin was going great until a group of experts began to disagree. An “experiment” in digital currency, with clearly defined goals and promises for its members, chose instead to redirect its path in a manner more aligned with those in control of its system (and probably paid off by pre-existing wealth). A new cryptocurrency that doubles as a democracy could avoid this pitfall.

 

When we build an internet democracy, and not just a currency, it’s important that we consider how laws and rules will be implemented. If we can quickly and accurately tabulate people’s opinions, we can more effectively develop a society that benefits the majority. On a broader scale, we can use these “verifiable accounts” to do things like objectively rate and evaluate cultural content and products. We can reward and propel artists, musicians, and content creators who are most deserving of attention from others. Is the music you hear on the radio also the most liked music by people in your life? Do you trust the poorly written 5 star reviews on Amazon, even if they come from a “verified purchase”? What about the Reddit comments in /r/The_Donald?

 

The internet was designed with a missing component; proof-of-person. In a purely virtual environment, it’s extremely easy to create a false sense of consensus. Democracy on the internet is impossible without a way to show that one person has only one account within a community. More importantly, A.I. has reached language capabilities indistinguishable from that of a human being, meaning a mercenary algorithm can be used to confabulate false opinions on legal, social, cultural, and political issues, unfairly swaying opinion on subjective content. These “fake review bots” can be used to propel artistic content, consumer products, and even presidential candidates that are undeserving of such positive sentiment. If you don’t believe that this is possible or desirable, then in the years 2013-2014, why were accounts on bitcointalk.org with many posts selling for hundreds of dollars in bitcoin?

 

Democracy as we know it hasn’t changed very much since it took a week for a pony-rider to mail a letter up the coast. Needless to say, a verifiable democracy, intertwined with the communication speed of the internet, would be revolutionary.