What is neuromarketing?

Neuromarketing enables one to substantially profit off the multi-billion dollar super-computer between their ears.

Neuromarketing is the science about your customer’s minds. It includes the direct use of brain imaging, scanning or other brain activity measurement technology to predict the subject’s response towards specific products, packaging or any other marketing element. It is the application of neuroscience to marketing.

Every year, billions of dollars are being spent on advertising campaigns. But conventional techniques have failed to predict how a customer feels when he is exposed to an advertisement. Neuromarketing offers cutting edge methods to know how a customer’s brain actually works and what effect does marketing have on the consumers’ population.

Neuromarketing researchers believe that consumers sometimes make subconscious decisions in a split of second. They believe that consumer’s decision can be driven through changing their emotions.

How Neuromarketing Works:

Knowing how an advertisement captures a consumer’s attention is what neuromarketing is all about. Research data is gathered by using certain biometrics that include:

  1. Eye tracking: tracking eye movement to understand which part of the advertisement is most appealing to the viewer.
  2. Facial coding: Testing facial expressions to learn certain responses about a product or an advertisement.
  3. Skin response and electrodermal activity: measures sweat gland secretions and different levels of excitement and arousals.
  4. Electroencephalography (EEG): measures electrical activity in the brain which is linked with increased or reduced focus and/or excitement levels.

Use Of EEG in Neuromarketing:

EEG biosensors makes the neuromarketing research easy. This allows the researchers to record consumer’s response in the right place such as movie theatre, bars etc. The biosensors can be placed on the head that accurately measure the brain activity of the subject. The changes in the electrical activity of the brain determines the emotional response of the person being tested, also whether he is engaged in watching the advertisement or not at all focused.

EEG can also reveal that the consumer was very attentive during the first 30 seconds of the advertisement but lost interest in the last 30 seconds. This feedback, in, turn, could better help in making the last 30 seconds of the advertisement even more effective.

Earning Money by Watching Advertisements and Using EEG:

This has also become a popular way of making money. This simple yet very beneficial tool can be used as a source of earning by using EEG to record your brainwaves while watching TV commercials and advertisements at home. People get paid by different companies and brands for selling their brainwave data. The general price paid per brainwave recording is between $80 and $100 per hour.

Different companies recruit people and pay them for watching their advertisements and recording their brainwaves by using electroencephalogram scans. It records on a second-by-second basis regarding how people respond to the commercial.

Neuromarketing has helped marketers make engaging and effective commercials. This not just benefits the marketers but the customers as well in enhancing their experience with a brand or product long before they consider buying it. This field is gaining unbelievable popularity among marketing and advertising professionals and is growing day by day.




Making Ads That Whisper to the Brain. (2010, nov 13). Retrieved from https://www.nytimes.com/2010/11/14/business/14stream.html: https://www.nytimes.com/2010/11/14/business/14stream.html

Neuromarketing and EEG: Measuring Engagement in Advertising. (2018, june 14). Retrieved from NeuroSky: http://neurosky.com/2016/08/neuromarketing-and-eeg-measuring-engagement-in-advertising/

Neuromarketing: Marketers scan consumers’ brains to test their ads. (2015, nov 5). Retrieved from CBC: http://www.cbc.ca/news/technology/neuromarketing-brainsights-1.3303384

Neuromarketing: The New Science of Consumer Behavior. (2011, jan 14). Retrieved from springer link: https://link.springer.com/article/10.1007/s12115-010-9408-1

What is Neuromarketing? (n.d.). Retrieved from Neuromarketing: https://www.neurosciencemarketing.com/blog/articles/what-is-neuromarketing.htm




Enhancing focus

Can neurostimulation reliably enhance your focus in day-to-day activities?

Focus is about giving your full concentration to that one thing while saying no to all those things vying your attention. There is no shortage of distraction in this world, so to increase focus levels, there has been a significant interest in the techniques that can do so including transcranial electrical stimulation (tES).

Attentional disturbances lie at the core of many neurological and psychiatric disorders such as ADHD. That is why focus has primarily been taken into account for cognitive enhancement techniques that include video games, pharmacological stimulants and meditational training. The discovery of transcranial electrical current is another technique to the arsenal. It comprises of a weak current that is made to run through two electrodes placed on the skull that changes the excitability of the brain tissues under the electrodes.

A number of studies have been carried out that paired tasks that required focus and attention, with tES (mostly with transcranial direct current stimulation). We will discuss three important aspects of focus and attention here that have been most broadly been targeted to date.

  • Visual Searching
  • Spatial orientation
  • Sustained Attention

Researchers have reported some very promising effects of tDCS in each of these domains.

Visual Searching

The process of scanning the visual field is a common action which makes it an interesting target for cognitive enhancement. Different studies and experiments were performed to examine the results of transcranial electric current on the visual searching.

Visual search performance is supported by an extensive network of brain areas, centered on the right posterior parietal cortex and frontal eye field. Among an array of distracting objects, participants in visual search tasks had to look for a target item. The faster the reaction time in searching, the more efficient the visual search of the participant. The researchers found that anodal tDCS over the right parietal cortex may speed up visual search, while cathodal stimulation may slow it down.

Moreover, it was also found that learning to discover hidden objects fixed in realistic scenes was greatly intensified by anodal tDCS over the right inferior frontal cortex.

Spatial orientation

Another aspect highly relevant to visual search was spatial orienting. These studies figured out that attention and focus are not symmetrically distributed over the visual field. Most people are exposed to pseudoneglect; they overemphasize features in the left versus the right hemisphere. This happens because the right hemisphere is slightly more active than the left.

Presumably, it was seen that tDCS proved to be very effective in increasing the activity of the left parietal cortex beyond that of the right, and resultantly causing a rightward shift in spatial bias. Similarly, a rightward shift for right cathodal tDCS was observed. It was furthermore observed that a “dual” montage with one electrode on each posterior parietal cortex (anode on left; cathode on right) was even more effective.

Sustained Attention

Typically after prolonged time-on-tasks, the average performance of a person declines which is called vigilance decrement. To find ways to hinder vigilance decrement, different research work was done that examined the effects of tES on sustained attention.

It was reported that the vigilance decrement could be stopped by applying bilateral tDCS to the dorsolateral prefrontal cortex early into a vigilance task.

Furthermore, prefrontal tDCS did not affect performance on a sustained attention to response task, but they did increase mind wandering. In conclusion, two studies reported that prefrontal tDCS specifically offsets the vigilance decrement, suggesting that its effects may only become apparent after prolonged task performance.


With the applications mentioned above, we come to the conclusion that a person’s focus can be enhanced through transcranial electric current stimulation. The effects of tDCS are not confined to the stimulation period, but can outlast it for minutes to hours, or even months after multiple stimulation sessions!



Transcranial Direct Current Stimulation’ May Boost Cognitive Function And Brighten Your Mood. (2013, october 29). Retrieved from Medical Daily: https://www.medicaldaily.com/put-headset-sharpen-your-focus-transcranial-direct-current-stimulation-may-boost-cognitive-function

ATTENTIONAL MODULATION OF VISUAL PROCESSING. (n.d.). Retrieved from Annual Reviews: https://www.annualreviews.org/doi/10.1146/annurev.neuro.26.041002.131039

Enhancement of attention, learning, and memory in healthy adults using transcranial direct current stimulation. (2014, january 15). Retrieved from Science DIrect: https://www.sciencedirect.com/science/article/pii/S1053811913008550?via%3Dihub

Enhancement of object detection with transcranial direct current stimulation is associated with increased attention. (2012, september 10). Retrieved from BMC Neuroscience: https://bmcneurosci.biomedcentral.com/articles/10.1186/1471-2202-13-108#Sec6

Enhancing multiple object tracking performance with noninvasive brain stimulation. (2015, feb 5). Retrieved from Frontiers : https://www.frontiersin.org/articles/10.3389/fnsys.2015.00003/full

Frequency Band-Specific Electrical Brain Stimulation Modulates Cognitive Control Processes. (2015, september 25). Retrieved from PLOS: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0138984

Increasing propensity to mind-wander with transcranial direct current stimulation. (2015, feb 17). Retrieved from PNAS: http://www.pnas.org/content/112/11/3314

Modulation of attention functions by anodal tDCS on right PPC. (2015, July). Retrieved from Science Direct: https://www.sciencedirect.com/science/article/pii/S0028393215000950?via%3Dihub

Simultaneous tDCS-fMRI Identifies Resting State Networks Correlated with Visual Search Enhancement. (2016, march 7). Retrieved from frontiers: https://www.frontiersin.org/articles/10.3389/fnhum.2016.00072/full

TDCS guided using fMRI significantly accelerates learning to identify concealed objects. (2012, january 2). Retrieved from Science Direct: https://www.sciencedirect.com/science/article/pii/S1053811910014667?via%3Dihub

The effects of tDCS upon sustained visual attention are dependent on cognitive load. (2016, January 8). Retrieved from Science direct: https://www.sciencedirect.com/science/article/pii/S0028393215302207?via%3Dihub

The Truth About Electrical Brain Stimulation. (n.d.). Retrieved from vitals: https://vitals.lifehacker.com/the-truth-about-electrical-brain-stimulation-1822192429

Transcranial Electrical Stimulation as a Tool to Enhance Attention. (2017, march 10). Retrieved from Speinger Link: https://link.springer.com/article/10.1007/s41465-017-0010-y

When Less Is More: Evidence for a Facilitative Cathodal tDCS Effect in Attentional Abilities. (2012, september ). Retrieved from The MIT PressJournals: https://www.mitpressjournals.org/doi/10.1162/jocn_a_00248



Neuroscience Research Market

How valuable are anonymized and unaltered brainwaves?

According to various modern researchers and the news reports released by Grand View Research, Inc, the global neuroscience is projected to reach the value of USD 30.8 billion by 2020. During the forecast period, the pace of growing developments in the field of neuroinformatics and sudden rise in patented research initiatives supported and funded by governments are factors projected to be responsible for the drive in the market share.

In 2016, the estimated value of the global neuroscience research was at USD 28.42 billion and it is quite expected to grow at a CAGR of 3.1% over the period forecast. The factors responsible for influencing the price thereby propelling the market growth include brain mapping research and investigation projects, neuroscience-based initiatives by government bodies, and the advancement of the technological tools and algorithms that are considered for implementation in the neuroscience space.

Over the forecast period, the introduction of novel technologies serving the purpose of mapping neuronal circuits situated in the brain functions is expected to boost the growth of this market. Furthermore, as a result of the global geriatric population, there is a significant increase in the demand for neuroscience-based research as this segment of the population is more prone towards earning the high risk of central nervous system disorders such as Parkinson’s disease and Alzheimer’s thereby making the market growth highly propelled.



The science behind outdoor advertising




The science behind outdoor advertising


Proof-of-Work Versus Proof-of-Cognition

Can a proof-of-work (POW) protocol substitute or supplement a proof-of-cognition (POC) protocol?

Can a proof-of-work (POW) protocol substitute or supplement a proof-of-cognition (POC) protocol? It is possible, but not ideal. Humans in a POC protocol have equal mining power, instead using human biology to secure human conscience. If mining power were unequal (as is the case with POW), human consciences could be manipulated a debatably far worse outcome than a simple double spend in a currency system. By relying on machines rather than biology, the network can be overpowered by artificial intelligence producing their own mining hardware, or re-routing existing mining power to reap digital currency rewards (BGP hijacking). Furthermore, miners in a POW protocol are motivated by currency rewards for honest mining. Human-to-human transactions would need to be made feeless if humans were to continuously verify each other. Determining which verification webs were human-based would be difficult or impossible from a POW miner’s perspective.

Can POC replace POW? The simplest reason it cannot is that miners in a POC protocol would be able to inject bad blocks into the network, sending themselves currency when they had previously had sent it elsewhere. Since POC trades a valueless data structure, this risk is nonexistent.

Proof-of-work is ideal for currency, while proof-of-cognition is ideal for identity.

Reference: proof-of-cognition-implants , published May 2015. Disclaimer: Project Oblio’s mechanism does not rely on brain implants, but the mechanisms of action are the same. An early version of the paper provably exists in bitcoin address 13eeMVU5fXNfZdoBk5z4fEAbgSH9MawQ6H.

Services in a Brain-to-Brain Internet

The below article is intended for a very futuristic use case, involving implants. You can study actual, ready BTB services at our github.

Future plans: Imagine a service called YouLive. Rather than sharing user-uploaded videos (as YouTube does), YouLive would share user-uploaded experiences. In such a system of shared experience, care must be taken to ensure that a user’s downloaded experience does not exceed the length of the recording, and that the downloaded experience is of the quality expected by the receiver. A user’s brain must be fundamentally protected from becoming ‘trapped’ in another (potentially ill-acting) user’s experience.

On a POC blockchain, safety is ensured by publicly-announcing connections between humans and services. The value or script of the transaction would be signify the length of time a connection was assumed to be valid. A human would confirm a connection time after receiving a service’s proposal. Once a connection was terminated, a human would then send a second transaction to signify they had been disconnected. The publicized initiation and termination of a connection is crucial to the safety of the network. If a connection was not terminated after the specified time, users on the network would notice on the blockchain, and could remove the ill-acting service from the network, or simply leave the network themselves. Once again, the decentralized nature of blockchains offer a safer means for these broadcasts than a centralized server, the latter of which can be hacked. Thus, a blockchain is absolutely necessary as a foundation for brain-to-brain security.

In the bitcoin protocol, a small number of ’emergency broadcast keys’ are given to core developers to alert users in the case of network failure. These keys could be used to automatically disconnect users in the event a number of downloaded thoughts or service connections did not receive their termination transactions.

In the case of human-service handshakes, a minuscule digital currency fee would be incurred to allot for the cost of blockchain data storage, as well as to help support the centralized structure hosting the experiences. If the service were decentralized (which it should be), a portion of the digital currency fee could be sent to the user who uploaded the experience, or whatever other feature the service offered. This fee would be necessary as an incurred cost for network spam, and relatedly, would ensure human nodes with a poor level of trust could still have their human-service transactions posted on the blockchain.

The protocol for a brain-to-brain internet outlined here is one that is discontinuous. Downloaded thoughts and service connections would only be utilized for an agreed-upon length of time. Code signing (Kiehtreiber and Brouwer [2006]) would ensure that downloaded thoughts were unaltered, similar to how file downloads on the internet are secured. Continuous, live stimulation of neurons will probably never be a safe mechanism for brain-to-brain communication, though refreshable service connections may allow for continued data sharing.


Reference: proof-of-cognition-implants , published May 2015. Disclaimer: Project Oblio’s mechanism does not rely on brain implants, but the mechanisms of action are the same. An early version of the paper provably exists in bitcoin address 13eeMVU5fXNfZdoBk5z4fEAbgSH9MawQ6H.

Liveness-detectable biometrics, and cybersecurity

How can we use liveness-detectable biometrics to provide computational barriers to creating fake accounts and fake votes?

Network security today is more difficult than it needs to be, largely because it must be based on the assumption that a single user can hold multiple accounts or multiple IP addresses. The one commonality between e-mail spam, DDOS attacks, presidential election meddling, and blockchain fees is that they’re all based on a single person holding multiple accounts. This person may submit multiple forum posts, multiple http requests, or multiple high-fee cryptocurrency transactions for the sole purpose of attacking or clogging the network, ruining it for everyone else. You might know this just as “spam”, or as “fake news”.

If there were a walled garden of the internet where each user was guaranteed to have provably one account, based on their biometricity, just like in the real world. You could also ban users who spam the network with these inexpensive requests, and could hold each person’s posts to a higher degree of accountability (people wouldn’t submit fake news if they couldn’t shed their post’s biometric signature). In blockchain, the real reason blockchain payments aren’t cheaper than say Visa for millions of users is due to this fact; People are clogging the network with low-priority payments and spam payments.


So, building a biometric internet isn’t really that simple. You can’t just say “here’s my fingerprint, now create my account”, because a fingerprint is really just an image file. An attacker could copy the scan of your fingerprint and pretend to be you very easily, otherwise this would have been done before.

What you need is a signal that exhibits biometricity, unique features that identify you, but is also a liveness challenge, a puzzle that basically asks “are you human?” and “are you actually there, right now, submitting this biometric signal?”.  If what you submit equates to a yes, you can enter the garden. If you’ve ever had to type in numbers on a street sign, or crooked letters in all caps, or anything that’s like “I’m not a robot”, that’s a liveness challenge (Google’s reCAPTCHA). It’s a liveness challenge, but it doesn’t tie you to one account because it doesn’t exhibit biometricity. There’s nothing biological to distinguish your response from that over other users — it guarantees one person per computer, but it doesn’t guarantee you’re going to act honestly once you’re inside, because you’re still anonymous. A liveness challenge that also exhibited biometricity would ensure that whatever biometric signal you were submitting, like a fingerprint, wasn’t copy and pasted from a file, but rather the signal was generated quite recently, from an actual human being behind their computer screen.

A simple example of a challenge that exhibits both liveness detection and human detectability might be to have some sort of public ledger that is a string of random values, like a blockchain. Each block contains a random hash value that you can use to derive 20 random words out of a list of 1000. These words are derived from the hash value, meaning there is a relation between the block’s hash and this new, presentable stimulus. You could then present these 20 random words to a user and tell them, “quick, say these 20 random words out loud!”. A person says the words and their voice, which is unique to them, is recorded and propagated across the network, where it is confirmed by nodes to be a biometric unique to them. It’s a liveness challenge because it’s difficult for a computer program to generate audio that (1) exhibited biometricity and (2) contained words seeded by a very recent block (i.e. the computational power to generate this may expensive if the seeding block was found quite recently). The fact that you were able to say the words so quickly would indicate that the signal wasn’t generated in advance, or before the random value was submitted, which is a sign that the words came from a live human. A person’s voice is a good (but not great) biometric, so it exhibits biometric features as well.


Everything discussed so far is great, except for the fact that the NSA and big tech companies have been collecting voice data for years and would be really good at generating a voice simulation to say those 20 words within 3 minutes (or three seconds). We learned from the Titanic that nothing is ever going to be 100% secure, so voice data definitely has a role in our network, but as a more future-proof liveness challenge/biometric, imagine now you’re inputting an electrical signal that was generated based on a block hash. The signal passes over a user’s skin near their left ear and comes out their right ear. The signal as it leaves the right ear still contains elements of the original signal, but it has been modulated based on the unique biological properties of your skin. We then digitize the analog signal so that it can be transmitted to a network of computers which analyze it.


The most efficient blockchain will be one where every single user has provably one account. Decentralized systems are plagued by spam, so if you can unclog the network from these spam attacks, you can make the fees cheaper for everyone. Right now credit card companies take 2% off every transaction, a financial network with 0% fees is obviously going to be preferable; Money will always flow to the space with highest liquidity (unless it’s prone to corruption like EOS). To build this one-person-one-vote network you need a biometric that exhibits liveness, and one method for doing that is described here, using the unique properties of brainwave biometricities.

A long-term validation metric can be used as an appendage to this, as pioneered by OpenMined.org. Basically, to validate that data isn’t faked, a machine learning algorithm (over a time-consuming process) determines which data improves its recognition rates and which do not. If it were possible to fake out a machine learning algorithm with bad data, then ML theorists would already be doing it, and nobody would be paying for data. Thus, the most stable foundation for a network like this ultimately (and ironically) relies on artificial intelligence (in the long-term / for cementing transactions) as well as fluid biometrics and a reputation system (in the short-term / for immediate payouts).

Finally, we provide a financial incentive for identifying fake accounts based on biometric signals by creating a challengers-verifiers market. People are motivated by financial reward to check each biometric signal submitted and verified by block producers. Block producers are expected to submit fake data 1% of the time and distribute new oblio as a reward. See our github for the latest spec on this component.

Keep an eye out for our next post, where we’ll be delving into the fully-blockchain-compatible algorithm that reached higher identification rates on brainwaves than any other study we’ve seen.

How to Scale a Smart Contract Blockchain

The simplest solutions are often the best. Let's create a voting system to vote in good block producers, and kick out the bad ones, where everybody has exactly one vote.

Imagine if you were in a big, empty room with one or two other people. It would be very easy for each of you to communicate by shouting at one another from corner-to-corner. This is how blockchains used to be, back when very few people knew about them.

Imagine now you start adding more people to the room. Suddenly, communication relies on everyone shouting at each other in all different directions, and each person is overwhelmed with information. Nobody has time to understand anything that they’re hearing – the channels are clogged. How can you fix this problem?


Before you invest in any type of blockchain, you should understand what the cons are to blockchains themselves. When we talk about blockchains and scaling, it’s easy to misconstrue the facts, because just as there are many types of blockchains, there are many different viable ways to scale a blockchain as well.

For starters, “scaling” is just making a blockchain accessible to a lot more people – orders of magnitude more, in fact. On a decentralized network, everyone should be able to help out. But the more crowded a blockchain becomes, the harder it is for every person contributing to the blockchain to process new information related to supporting it. This, effectively, moves power to those with pre-existing wealth– those with more bandwith, more storage space, etc.

Going with the analogy described earlier, one solution to the ‘crowded room’ problem is to charge money before people are allowed to shout information. This makes sure only really serious people get to speak into the crowd. But, it also makes communicating (over blockchains) very expensive. People with a lot of pre-existing wealth can launch “spam attacks” on the network to drive up the fees on regular users’ transactions. If it’s a proof-of-stake chain or a centralized proof-of-work algorithm, then these rich persons are probably profiting in this attack, because they’re basically raising the fee price by paying huge fees while most of the fees go back to them anyway. As the network becomes clogged, its market price tumbles, and said “bag-holders” profit off their margin-traded short position. If we’re talking about a smart contract blockchain, this becomes a fundamental problem for developers too.

Experienced programmers can imagine the tiny, but not-so-negligible cost of running a website on one external server. It’s only about $5 per month to get a user database up and running on Amazon AWS. With dApps, things get a lot more expensive. Rather than only one user database, you’re effectively paying everyone on the network to calculate your program’s output at the exact same time, in addition to listening for basic communications. More computational power means higher fees. In the crowded room scenario, imagine if someone had to not only listen to transactions, but also type in each one’s instructions on a handheld calculator before they could process the next one.


Another solution to the crowded room is the “telephone game”. People at the corners of the room might whisper information towards central spokes near the middle. This is a bit like how Ripple works. It might also be an analogy for payment channels. But Ripple and payment channels don’t seem to apply to smart contracts, the part where people have to type stuff into calculators. This sucks, because smart contracts have proven to be incredibly useful. If we’re not only asking people to share information, but having each person do calculations on it, the “whisper method” really doesn’t play.

On Project Oblio, nodes that are “ordained”  run smart contracts in subgroups and tie their output to their own biometricity and staked wealth. The difference here is that rather than running the same program across many nodes (traditional smart contract chains), only a small group of ordained nodes need to run, verify, and sign a particular program’s output with their unsheddable biometricity. Because a person can’t shed their biometricity, one person can’t spin up more than one node to dupe the network (Project Oblio is one-person-one-vote, anti-Sybil system). Thus, this proof-of-individual system is a highly-secure way to evaluate smart contracts.  More importantly, it reduces fees by  requiring considerably less computational power.

The gist of it is, on wealth or work-based blockchains, a single smart contract needs to be run by every single node before a block is verified. On Project Oblio, a smart contract or “service” only needs to be verified by one or more trusted individuals to reach approval of the network.  This reduces fees, and allows for greater computational prowess than previously described.

As one eerily might have expected after reading Satoshi’s white paper, one-human-one-vote offers a lot more for society than one-CPU-one-vote. Only through one-person-one-vote  can you scale a smart contract blockchain.

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.