Thursday, January 4, 2018

Friday Thinking 5 Jan. 2018

Hello all – Friday Thinking is a humble curation of my foraging in the digital environment. My purpose is to pick interesting pieces, based on my own curiosity (and the curiosity of the many interesting people I follow), about developments in some key domains (work, organization, social-economy, intelligence, domestication of DNA, energy, etc.)  that suggest we are in the midst of a change in the conditions of change - a phase-transition. That tomorrow will be radically unlike yesterday.

Many thanks to those who enjoy this.
In the 21st Century curiosity will SKILL the cat.
Jobs are dying - work is just beginning.

“Be careful what you ‘insta-google-tweet-face’”
Woody Harrelson - Triple 9



The Future of Businesses and Organizations speaks Platforms
To highlight the huge impact that the adoption of open, boundaryless modes of production might have on organizations, another interesting 2017 report — from Bain — dedicated to exploring the shape of The Firm of the Future envisioned that, in ten years, most of the work in organizations will be performed by self-managed teams that “will blend internal and external resources to provide the right skills as needed” where “employees will have no permanent bosses […] and coaching and feedback will be real-time and continuous”.

The depth of opportunities and challenges for organizations that want and need to embrace this new way of thinking, is extremely well captured in Paul Hobcraft’s encompassing read “Adjusting to the Changing Landscape of Ecosystems” stating clearly how “the traditional confines of market boundaries are clearly breaking down” and how this is “driving a radically different environment to manage within”.

The Best Reads on Platforms from 2017

We humans are trapped by the narrative fallacy. The physical world may be irreducibly random, but our minds have evolved to assign causation to correlation, to see patterns in noise, to comprehend history not as one damned thing after another, but as the unfolding of some grand plan — perhaps the work of an Author.

The pace of invention seems to be speeding up, and advancing technology amplifies the power of every individual in our complex world, for good and ill.

Just as research is starting to embrace openness and citizen scientists, some creators are experimenting with collaborative science-fictional world-building. Mark Watney, hero of The Martian (2011) would not have been able to “science the shit out of” his predicament on Mars without the help of author Andy Weir’s online beta readers, who obsessively checked every technical detail. Keeping sci-fi relevant is also changing how we write it. What ultimately allows the heroes of Stranger Things to triumph is not Dungeons & Dragons’ static lore, but the lessons learnt from playing it: working together to map the unknown, avoid its traps and bring treasure home.

Science fiction when the future is now

We inhabit a world of emergence, uncertainty and unforeseeable change. The greatest opportunities for advantage lie in the combination of fast changing markets and emerging technologies. Because of this complex landscape, instead of preparing ourselves for a knowable future, we need to explore and probe for openings. We need to build on successful ventures and shift flexibly among opportunities as circumstances change.

The strategic logic is temporal rather than spatial. When following a spatial, foresight metaphor, there is a territory that can be mapped and understood, but here the territory is seen as being under continuous development and in formation by the exploration itself. “It is impossible to map an area that changes with every step the explorer takes.”

The significant point is that no one can predict how long an advantage will last. It is a Snapchat economy. The responsible and resilient way to think is that it could all end tomorrow. The key insight then is that we should be where the flow of opportunities is the fastest and most promising.

Biology, Blockchains and Quantum Physics

This is a 20 min. TED talk from 2014 - but maybe it’s even more important to listen too in these days of turmoil.

Beware, fellow plutocrats, the pitchforks are coming | Nick Hanauer

Nick Hanauer is a rich guy, an unrepentant capitalist — and he has something to say to his fellow plutocrats: Wake up! Growing inequality is about to push our societies into conditions resembling pre-revolutionary France. Hear his argument about why a dramatic increase in minimum wage could grow the middle class, deliver economic prosperity ... and prevent a revolution.

Maybe successful societies and successful teams have something in common. Here’s what Google found about successful teams.

The Results of Google’s Team-Effectiveness Research Will Make You Rethink How You Build Teams

A group of employees from Google’s People Operations section, the equivalent of an HR department, decided to complete an analysis to answer one question: What makes a Google team effective?

Google’s research
The minds at Google wanted to know why some teams soared toward success while others seemed to struggle. Initially, the company’s executives, like many other great business minds, assumed that, when it comes to hiring, bringing in the most talented professionals was the ideal path to glory. But, it turned out, they were “dead wrong.”

According to Google’s re:Work site, they made the discovery after reviewing over 180 Google teams, conducting more than 200 interviews, and analyzing 250-plus attributes they identified, cross-comparing the makeup of stellar groups and those that weren’t reaching such heights.

Ultimately, they determined “who is on the team matters less than how the team members interact, structure their work, and view their contributions.”And that is a powerful finding for those interested in upping team effectiveness and productivity at work.

Along the way, they discovered “five key dynamics that set successful teams apart” from the rest:
1. Psychological safety
2. Dependability
3. Structure and clarity
4. Meaning
5. Impact
While all five play a role, the first trait, psychological safety, was substantially more crucial to overall success. Here is an overview of the characteristics Google identified and why the unicorn company believes they matter.

The digital environment and the emerging distributed ledger technologies promises unprecedented capacity to account for an unprecedented range of value creation. But the key question is ‘what is Value?’ This article is a 5 min read that may be a bit over the head of most - me included. But it is well worth the effort to get a glimpse of the accelerating technology. We all have to work to re-imagine how we Value Our Values.

On Token Value

Millions of new people have entered the crypto space this year as a result of the soaring prices of cryptocurrencies.

A question that I consistently hear from new entrants is: what is the value underlying cryptocurrencies and crypto tokens broadly? It’s clear that speculation is the main driver of prices, but what may not be clear is that there actually is fundamental value underlying the speculation. With the proliferation of new tokens being created though, some tokens offer holders fundamental value while many others do not. How does one differentiate the value from the junk in such a noisy space?
Quantifying Value
Wall Street types are eager to create metrics to quantify the value of crypto tokens (like P/E ratios and cash flow statements are used to quantify the value of publicly traded stocks). I’ve even tried to do it myself and wrote about it in February (see The Investment Case for ETH). In retrospect, the piece was directionally right but too conservative in magnitude of direction.

I am now of the belief that it’s generally far too early in the space for models and metrics to accurately quantify value. If fundamental value as described above truly underlies usage tokens, work tokens and hybrid tokens, they’ll create many orders of magnitude more in value in the future (orders of magnitude not typically grasped by traditional analysis, much like early stage startups).

Algorithms are everywhere that human work, live and play only we call them habits, rules-of-thumb, heuristics, analogies, and so much more. But the digital environment is extending these to all forms of work.
Goldman Sachs has already begun to automate currency trading, and has found consistently that four traders can be replaced by one computer engineer, Chavez said at the Harvard conference. Some 9,000 people, about one-third of Goldman’s staff, are computer engineers.
Goldman’s new consumer lending platform, Marcus, aimed at consolidation of credit card balances, is entirely run by software, with no human intervention, Chavez said. It was nurtured like a small startup within the firm and launched in just 12 months

As Goldman Embraces Automation, Even the Masters of the Universe Are Threatened

Software that works on Wall Street is changing how business is done and who profits from it.
At its height back in 2000, the U.S. cash equities trading desk at Goldman Sachs’s New York headquarters employed 600 traders, buying and selling stock on the orders of the investment bank’s large clients. Today there are just two equity traders left.

Automated trading programs have taken over the rest of the work, supported by 200 computer engineers. Marty Chavez, the company’s deputy chief financial officer and former chief information officer, explained all this to attendees at a symposium on computing’s impact on economic activity held by Harvard’s Institute for Applied Computational Science last month.

The experience of its New York traders is just one early example of a transformation of Goldman Sachs, and increasingly other Wall Street firms, that began with the rise in computerized trading, but has accelerated over the past five years, moving into more fields of finance that humans once dominated. Chavez, who will become chief financial officer in April, says areas of trading like currencies and even parts of business lines like investment banking are moving in the same automated direction that equities have already traveled.

Today, nearly 45 percent of the revenue from cash equities trading comes from electronic trades, according to Coalition, a U.K. research firm that tracks the industry. In addition to back-office clerical workers, on Wall Street machines are replacing a lot of highly paid people, too.

But more than yesterday’s automation - I literally mean yesterday - the emerging automation hitting the financial and other service industries will include the blockchain.
Consider traditional accounting, a multi-billion industry largely dominated by the ‘big four’ audit firms, Deloitte, KPMG, Ernst & Young, and PwC. The digital distributed ledger could transparently report the financial transactions of an organization in real time, reducing the need for traditional accounting practices. And that is why most major players in the financial industry are busy investing significant resources into blockchain solutions. They have to embrace this new paradigm to ensure it works for, not against, them.


Around the time when bitcoin and blockchains were starting to catch the attention of the mainstream investment world, a New York-based start​up called Digital Asset Holdings (DAH) was launched. Blythe Masters was at its helm. The Wall Street veteran is knowledgeable about a common problem many banks face: Getting incompatible financial databases to talk to each other. It’s costly, complex, and takes time. While it might seem that traders work at Red Bull speed in lightning-paced environments, the technology used to execute trades is remarkably old- Fashioned and slow.

Lots of phone calls are made, emails traded and even the occasional fax is still sent. It can take up to three days—T3—for stock trades to change hands via clearing houses such as the National Securities Clearing Corporation (NSCC). It’s a process known as ‘settlement lag.’ Every hour before settlement happens, when a trade precariously hangs between sale and purchase, increases the risk that the trade won’t go through. Obviously, it’s in the banks’ interest to close that lag time as much as possible.

Blockchains could help reduce the gap of the entire lifecycle of a trade from days to minutes, even to zero. According to a report by Santander InnoVentures, the Spanish bank’s fintech investment fund, by 2022 ledger technologies could save banks $15–20 billion a year by reducing regulatory, settlement and cross-border costs.

Digital Asset Holdings wants to be the distributed database handling these speedy transactions. And the who’s who of the world’s biggest financial names, including Goldman Sachs, Citibank and Blythe Masters’s old employer, JP Morgan, have ploughed more than $60 million of investment into DAH. Speed and efficiency are not the only qualities that make distributed ledgers attractive to banks. ‘Regulators will like that blockchain-based transactions can achieve greater transparency and traceability– an “immutable audit trail”,’ Masters says. In other words, it could help eliminate the kinds of fraud that come from cooking the books. It’s rather ironic that these words come from a woman who spent several months being investigated by the Federal Energy Regulatory Commission for a cover‑​up of energy-trading strategies. Masters was not cited for any wrongdoing and no action was brought individually against her. JP Morgan paid $410 million to settle and close the case, without denying or admitting wrongdoing.

And there’s work on incorporating distributed ledger technology for better science - Nature examines some of these possibilities. In the world of Big Data and unprecedented capacity for research - secure and interoperable data may benefit everyone.

Could Bitcoin technology help science?

Blockchain could lend security measures to the scientific process, but the approach has its own risks.
The much-hyped technology behind Bitcoin, known as blockchain, has intoxicated investors around the world and is now making tentative inroads into science, spurred by broad promises that it can transform key elements of the research enterprise. Supporters say that it could enhance reproducibility and the peer review process by creating incorruptible data trails and securely recording publication decisions. But some also argue that the buzz surrounding blockchain often exceeds reality and that introducing the approach into science could prove expensive and introduce ethical problems.

A few collaborations, including Scienceroot and Pluto, are already developing pilot projects for science. Scienceroot aims to raise US$20 million, which will help pay both peer reviewers and authors within its electronic journal and collaboration platform. It plans to raise the funds in early 2018 by exchanging some of the science tokens it uses for payment for another digital currency known as ether. And the Wolfram Mathematica algebra program — which is widely used by researchers — is currently working towards offering support for an open-source blockchain platform called Multichain. Scientists could use this, for example, to upload data to a shared, open workspace that isn't controlled by any specific party, according to Multichain.

Blockchain, a technology that creates an immutable public record of transactions, has a “Wild West, boom or bust culture”, says Martin Hamilton, a London-based resident futurist at Jisc, which supports digital services in UK education. He warns that academics and entrepreneurs might be tempted to add the technology solely to make their projects seem “magical and sparkly”. As one sign of this trend, consulting firm Deloitte has identified more than 24,000 aborted, largely financial, blockchain projects on the GitHub software-development platform in 2016 alone. Yet Hamilton still says blockchain has incredible potential. “There will be things that we try which simply blow up in our faces,” he says. “But the rewards can be huge, if you’re willing to take a calibrated risk.”

This is a fascinating signal of the progress being made in fundamental science - that will inevitably contribute to the emerging fields of quantum computing.

Physicists Just Discovered a Way to Track Unobserved Quantum Particles

What we see is only a fraction of the picture.
One of the underlying principles of quantum theory is that quantum objects can exist as waves or particles. But, they do not exist as either until they are measured, making it seemingly unachievable to identify or track quantum objects when they're not being observed.

But recently, physicists faced this issue and proved that it is not an impossibility to track unobserved quantum particles.

David Arvidsson-Shukur, the study's first author and a Ph.D. student at Cambridge's Cavendish Laboratory, became interested in a physics premise called "the wave function."

Within this new study, published in the journal Physical Review A, researchers from the University of Cambridge demonstrated that, by examining the way a quantum object interacts with its environment instead of measuring the object itself, you can track unobserved quantum particles.

As particles move, they "tag" their environment.
Each "tag," or interaction with their environment encodes information within the particles. So Arvidsson-Shukur and his co-authors developed a method to map these "tagging" interactions without directly observing them.

This new way to track unobserved quantum particles could allow scientists to test old predictions in quantum mechanics.
These include ideas like that a particle can exist in two places at the same time, or suggestions like telepathy in which information can be transmitted between two people without any particles traveling between them.

This seems like a long time coming - the memristor was first developed around 2008 and promised the emergence of a new computational paradigm - perhaps it was awaiting a new computational paradigm. :)

New quick-learning neural network powered by memristors

U-M researchers created a reservoir computing system that reduces training time and improves capacity of similar neural networks.
A new type of neural network made with memristors can dramatically improve the efficiency of teaching machines to think like humans. The network, called a reservoir computing system, could predict words before they are said during conversation, and help predict future outcomes based on the present.

The research team that created the reservoir computing system, led by Wei Lu, U-M professor of electrical engineering and computer science, recently published their work in Nature Communications.

Reservoir computing systems, which improve on a typical neural network’s capacity and reduce the required training time, have been created in the past with larger optical components. However, the U-M group created their system using memristors, which require less space and can be integrated more easily into existing silicon-based electronics.

Memristors are a special type of resistive device that can both perform logic and store data. This contrasts with typical computer systems, where processors perform logic separate from memory modules. In this study, Lu’s team used a special memristor that memorizes events only in the near history.
Inspired by brains, neural networks are composed of neurons, or nodes, and synapses, the connections between nodes.

While Moore’s Law has been deemed dead - new computational paradigms seem to be rapidly developing. This is another important signal in the coming Cloud and Fog Computing infrastructure.
“It’s an entirely new family of devices because this type of architecture has not been shown before. For many key metrics, it also performs better than anything that’s been done before with inorganics,” says study lead author Dr. Alberto Salleo, a material engineer at Stanford.

New Artificial Synapse Bridges the Gap to Brain-Like Computers

... the momentum comes from breakthroughs in artificial neural networks, which loosely mimic the multi-layer structure of the human brain. But that’s where the similarity ends. While the brain can hum along on energy only enough to power a light bulb, AlphaGo’s neural network runs on a whopping 1,920 CPUs and 280 GPUs, with a total power consumption of roughly one million watts—50,000 times more than its biological counterpart.

Extrapolate those numbers, and it’s easy to see that artificial neural networks have a serious problem—even if scientists design powerfully intelligent machines, they may demand too much energy to be practical for everyday use.

Hardware structure is partly to blame. Our computers, with their separate processor and memory units, are simply not wired appropriately to support the type of massively parallel, energy-efficient computing that the brain elegantly performs.
Recently, a team from Stanford University and Sandia National Laboratories took a different approach to brain-like computing systems.

Rather than simulating a neural network with software, they made a device that behaves like the brain’s synapses—the connection between neurons that processes and stores information—and completely overhauled our traditional idea of computing hardware.

The artificial synapse, dubbed the “electrochemical neuromorphic organic device (ENODe),” may one day be used to create chips that perform brain-like computations with minimal energy requirements.

Made of flexible, organic material compatible with the brain, it may even lead to better brain-computer interfaces, paving the way for a cyborg future. The team published their findings in Nature Materials.

This is an amazing development - another signal towards what will inevitably be more breakthroughs. Science is fundamentally about instrumentation. :)

Breakthrough sensor for photography, life sciences, security

New Quanta Image Sensor enables new imaging capability in accessible, inexpensive process
Called the Quanta Image Sensor, or QIS, this next generation of light sensing technology enables highly sensitive, more easily manipulated and higher quality digital imaging than is currently available, even in low light situations, according to co-inventor Eric R. Fossum, professor of engineering at Dartmouth. Fossum also invented the CMOS image sensor found in nearly all smartphones and cameras across the world today.

Documented in the Dec. 20 issue of The Optical Society's OSA Optica, the new QIS technology is able to reliably capture and count the lowest level of light, single photons, with resolution as high as one megapixel, or one million pixels, and as fast as thousands of frames per second. Plus, the QIS can accomplish this in low light, at room temperature and while using mainstream image sensor technology, according to the Optica article. Previous technology required large pixels or cooling to low temperatures or both.

Here’s an important signal in the progressive domestication of DNA. This is worth the read - in order to understand a new approach to pests and disease.

Pesticide 2.0: Spray-on gene silencers

In their bitter war with crop pests, farmers have two big guns: chemical pesticides and genetic engineering. But excitement has been building in the farming community for a new weapon that is unlike anything they’ve tried before, a pesticide 2.0. Highly selective and non-toxic, yet applied using the conventional methods of pesticide sprays, this approach exploits an ancient biological process to turn the pest’s own genes against it. But the new farming tool is just one use of a technology— RNAi —that is primed to fight a host of other major global challenges, including human disease. Farmers may well be at the frontlines of an RNAi revolution.

What is RNAi?
RNAi is a natural process that occurs in almost all organisms, from crop plants to insect pests to mice. Short for RNA interference, it is a form of protection against invading RNA. RNA is a chemical similar to DNA, and it helps translate the genetic code into action. Like DNA, it is found in every living thing and is highly specific to the particular species it came from. Some viruses even use RNA in place of DNA as their heritable code. Cells need to be able to recognize foreign RNA, such as from infecting viruses, which is where RNAi comes in. Two key RNAi proteins called Dicer and Slicer recognize, break apart, and destroy the invading RNA molecules.

This system was first discovered in the model worm Caenorhabditis elegans by Craig Mello, Andrew Fire, and their teams. Simply by injecting short pieces of RNA into their worms, they could “interfere” with the function of specific C. elegans genes. The scientists were able to target the genes of their choice; if they knew the gene’s DNA sequence they could design a corresponding RNA sequence that would set Dicer and Slicer on the attack. The superpower potential of RNAi was quickly appreciated and a Nobel Prize was awarded to Mello and Fire in 2006, just 8 short years after their original publication.

Robots, AI, Mixed Reality (Virtual, Augmented) and more are transforming how we will work, play, live. A key innovation should be a shift toward Universal Basic Income.
“I’m not really worried,” he says. “There are so many jobs in this mine that even if this job disappears, they will have another one. The company will take care of us.”
“In Sweden, if you ask a union leader, ‘Are you afraid of new technology?’ they will answer, ‘No, I’m afraid of old technology,’” says the Swedish minister for employment and integration, Ylva Johansson. “The jobs disappear, and then we train people for new jobs. We won’t protect jobs. But we will protect workers.”
“A good safety net is good for entrepreneurship,” says Carl Melin, policy director at Futurion, a research institution in Stockholm. “If a project doesn’t succeed, you don’t have to go broke.”

The Robots Are Coming, and Sweden Is Fine

In a world full of anxiety about the potential job-destroying rise of automation, Sweden is well placed to embrace technology while limiting human costs.
From inside the control room carved into the rock more than half a mile underground, Mika Persson can see the robots on the march, supposedly coming for his job here at the New Boliden mine.
He’s fine with it.

Sweden’s famously generous social welfare system makes this a place not prone to fretting about automation — or much else, for that matter.

Mr. Persson, 35, sits in front of four computer screens, one displaying the loader he steers as it lifts freshly blasted rock containing silver, zinc and lead. If he were down in the mine shaft operating the loader manually, he would be inhaling dust and exhaust fumes. Instead, he reclines in an office chair while using a joystick to control the machine.

This is the reasonable consequence and of course great news for those of us waiting for self-driving cars.
The car insurance industry is scrambling to respond to autonomous technology, with experts predicting that uncertainty about liability could delay testing, deployment, and market penetration of these vehicles. Some consultants predict that up to 80 percent of insurance premiums could evaporate over the next decade, assuming driverless technology makes automobiles safer and less prone to accidents.

Riders in Waymo’s self-driving cars will now be insured

No cost to passengers
Riding in a self-driving car involves a certain level of risk taking, especially in these very early days of the technology. Recognizing the need to build trust among normal people, Waymo, the self-driving unit of Google-parent Alphabet, announced it would be partnering with an insurance startup to cover riders in its soon-to-be-released driverless ride-hailing service.

Trov, a five-year-old insurance tech startup based in Danville, Calif., said it would work with Waymo to insure passengers for lost and damaged property and trip-related medical expenses. In other words, if your driverless Waymo is involved in a fender bender — or, god forbid, something worse — your robot-induced whiplash treatment will be covered.

This is important for anyone playing games of chance


Summary: I collected data at the carnival for a full day. Then I used that information to figure out which games are the biggest scams using science to analyze them and show you how to beat them. I also figured out how much the carnival actually pays for the prizes so even if you win, you lose. And then I visited the carnival with my professional baseball playing buddy to dominate all the games. It worked well

Scams in the digital environment - this is just one signal illuminating the efforts of traditional and emerging players to make people the content being delivered to real ‘users’. More emphasis on protections of the Internet as a public infrastructure with more transparent tools, and net neutrality can serve everyone. One imagines the challenges facing Neilson ratings for commercials when people used remotes to change or when they simply shifted their attention way.
This is worth the read - especially in light of ‘Fake News’ and now Fake Readers’.
“We’re committed to only working with reputable and brand-safe publishers, and we don’t take this sort of thing lightly,” Erich Timmerman, a JPMorgan spokesperson, told BuzzFeed News.
The incident is the latest glimpse at the roots of a crisis of trust in online publishing. Blue-chip advertisers increasingly doubt whether their online ad spending reaches real audiences, and JPMorgan in particular has taken steps to ensure its ads only appear on quality sites. But even quality sites present risks.

These Publishers Bought Millions Of Website Visits They Later Found Out Were Fraudulent

Fake traffic was sent to pages containing ads for JPMorgan Chase & Co., Visa, Amazon, KFC, and other big brands. "We don’t take this sort of thing lightly,” a JPMorgan spokesperson told BuzzFeed News.
This summer,, a news site that’s raised more than $35 million in funding from high-profile investors, published a group of articles in an ongoing series about how companies and entrepreneurs are trying to be a positive force in their communities. The content was created as part of a partnership with JPMorgan Chase & Co., whose logo appears on each article.

The stories appeared to be a big hit: Between May and October, the sponsored content ranked among Ozy’s most-viewed articles, according to traffic data from analytics service SimilarWeb.

It’s the kind of success a publisher and brand would celebrate — except that the vast majority of traffic to the articles was in fact fraudulent, according to ad industry standards. Those stories, as well as other Ozy articles that carried ads from Amazon and Visa, received traffic that was purchased and delivered via a system that automatically loads specific webpages and redirects traffic between participating websites to quickly rack up views without any human action.

An estimated $16 billion will be lost to ad fraud this year, and a significant portion of that will go to criminals who use bots and other nefarious means to siphon money out of the digital ad ecosystem. But this example shows how legitimate publishers contribute to fraud when they knowingly or unknowingly use invalid traffic and other illegitimate means to grow their audiences and increase ad revenue.

“Illegitimate traffic sourcing occurs when a publisher pays a traffic supplier for a fixed number of visits to their website,” said a recent white paper about ad fraud published by the Alliance for Audited Media, a not-for-profit media auditing organization. “Publishers often buy traffic at the end of the month or quarter to ‘make its numbers.’ Traffic sellers often promise the publisher that the traffic is human and will pass through all ad fraud detection filters.”

This article is linked in the above article - but it’s worth noting and reading for all of us web surfers. There is a traffic war based on advertising business models that threaten the integrity of the Internet.
“To simplify our policies, we are no longer permitting the placement of Google ads on pages that are loaded as a pop-up or pop-under. Additionally, we do not permit Google ads on any site that contains or triggers pop-unders, regardless of whether Google ads are shown in the pop-unders,” the blog post said.
A Google FAQ also says that “sites using AdSense may not be loaded by any software that triggers pop-ups, modifies browser settings, redirects users to unwanted sites, or otherwise interferes with normal site navigation.”

How To Create Web Traffic "Out Of Thin Air"

Unscrupulous ad networks and publishers have come up with a way to generate massive amounts of fake traffic and ad impressions. And like many things on the internet, it traces its origins to porn.

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