Preface: From this point forward things haven’t become fully public. Such as, what exactly is AiGarth and how will it interact with IOTA and the Tangle. Or, how do the foundational layers of IOTA, the Tangle, and Qubic start tying together in which they create an ecosystem for the world’s resources, such as Data, and Computational Power? As well, where does swarm intelligence fit in? Where is that puzzle piece?

Understand, that the below is simply a thought experiment. Such as, if AI has a secure messaging protocol being fed processed and digestible data, what can this type of AI become. Or what can it do? If those were the building blocks, then what kind of application could evolve from them? In this article, I will discuss Artificial Intelligence and how a secure feeless distributed network can support AI growth and enable a system in which no one government, or company, can own the lion share of it. I will discuss how AI will not become the terminator, how it will not take everyone’s job, and how AI should be controlled by the many, not by the few. Again, I may be incorrect on some of this. I’m not a techie myself, but I am simply trying to inspire thought and discussion, about what the future a could be. As well, how IOTA and the Tangle be a pivotal force keeping the power from the few, but rather for the many.

Let Us Define Artificial Intelligence

In the book The Fourth Age, by Byron Reese, he describes how there are two types of Artificial Intelligence (AI).

Artificial Narrow Intelligence (ANI)

Artificial General Intelligence (AGI)

He describes that the AI Robot, which is what the movies depict as who will become the singularity, a robot which can instantly become smarter and more powerful than mankind, is not the current AI that is currently within our society. The AI that we see in the Matrix, which uses humans as an energy source, is called an Artificial General Intelligence (AGI). This AI is very different from the AI we have today. In your own pocket, if you own one of the newer iPhones, you have an AI-enabled and powered connected device. From the article in 2018, Apple’s Latest iPhones Are Packed with AI Smarts by Tom Simonite on Wired.com, “All three iPhones announced Wednesday include a new chip called the A12, designed in-house by Apple. It has a unit called a neural engine, dedicated to running the neural network software behind recent advances in the ability of machines to understand speech and images.” Many of you reading this article are doing so on an Artificial Narrow Intelligence (ANI) hardware connected device right now.

If you look at your phone, do you think it could take over the world? This is the difference between AGI and ANI. The question then becomes, if they have created ANI, can society create AGI? People debate this not necessarily in the aspect of ‘can’ AGI be created, but more so will it be created within our lifetime, or in a soon enough time span where we must fear it. My personal opinion is that ANI itself will help us research, analyze and eventually create a safe and controlled AGI. Now, there are those that will say, “There is no stopping an AGI once it is created, it will look at humans as inefficient and make us their slaves. We will be ants to them!”. If the above statement is true then we are doomed. The fact is some country, some company, or some person will without a doubt one day (maybe in 200 years), but one day will build an AGI (if it is possible that is). My personal thought is that one day an AGI will be created, but until then we should focus on enhancing our technological abilities with ANI, which may simply be the powerful resource we need that researches and analyzes a solution to creating a safe and controlled AGI. In other words, Artificial Narrow Intelligence is present, and it is here to stay.

But is AI really here?!?

In Part V we discussed how computational resources are not only valuable but wasted throughout the world. As well, how Supercomputers are owned by governments and businesses who control and regulate access to them. We see that AI needs an immense amount of data and computational power to work correctly, such as supercomputers, or, a distributed network offering access to computational resources. So it is companies like IBM, with Watson, or governments like the United States who are harnessing these supercomputers which can run AI programs. The race is on. Even now, the United States in which the US Department of Energy (DoE) has announced it’s setting aside $600 million to build the world’s fastest supercomputer called Frontier which can complete 1.5 Quintillion calculations per second and be about 10 times faster than the current fastest supercomputer dubbed Summit.

People always thought that AI needed strict parameters to be programmed, as we saw with Alpha Go. That Narrow, was VERY NARROW when describing Artificial Narrow Intelligence. However, Alpha Zero (Alpha Go’s successor) showed us that by simply programming a set of rules, the AI program can simply teach itself. Instead of learning by providing the AI program with human strategy, it simply taught itself and created its own game strategy. Not only was it able to do so, but it dominated its predecessor beating it numerous times in the Go Game. Go, is a Chinese game over 2,500 years old. The lower bound estimate of board positions or different game positions that could be possible is (2 x 10 to the power of 170). As a comparison, there is 10 to the power of 80 atoms in the known universe. So there are more moves exponentially than anything we could possibly conceive. In other words, the AI computer cannot simply study the moves, but rather it must teach itself a strategy.

So, is this Artificial General Intelligence or Artificial Narrow Intelligence? In fact, it is ANI. No matter how good it is at teaching itself Go, it is still only programmed to play Go. In no way can this ANI simply decide to tap into the World Wide Web, change its programming, distribute itself throughout all the connected devices and then eventually take over the world. These AI programs as powerful as they are, are still extremely very specific in what problems they are solving. The key point is, they solve problems extremely well! In fact, they solve problems not only better than humans but better than other AI’s! What has been factually proven is not only can AI perform better than humans when programmed at a specific task, but even AI’s can perform better than other AI’s.

So Artificial Narrow Intelligence is Here To Stay,…Now What?

Implementing Machine Learning In Your Organization (from aws.amazon.com/machine-learning/whatis-ai/)

So what can ANI do for us? On Aws.amazon.com, ‘what is Artificial Intelligence? Machine Learning and Deep Learning’; they state, “Machine Learning (ML) is the name commonly applied to a number of Bayesian techniques used for pattern recognition and learning. At its core, machine learning is a collection of algorithms that can learn from and make predictions based on recorded data, optimize a given utility function under uncertainty, extract hidden structures from data and classify data into concise descriptions.” “With the right data, an ML model can analyze high dimensional problems with billions of examples, to find the optimal function that can predict an outcome with a given input.”

Amazon goes on to state that use cases are: anomaly detection, fraud detection, customer churn, and content personalization. Yet we see AI everywhere. We see and use it with Google for our search, our smart-phones use AI, the medical industry, the visual graphics, science, pharmaceutical, sports, banking, marketing industry, the financial industry, and others. Pretty much, EVERY single industry is currently using Artificial Narrow Intelligence.

Artificial Intelligence in itself is a valuable resource and the market is worth tens of billions of dollars. On orange-business.com from a magazine article in 2017, they stated that the worldwide revenues for cognitive and AI systems will reach $12 billion in 2017, an increase of 59% since 2016. They further stated that companies are consolidating such as showing an example where Microsoft acquired the startup Maluuba for its AI expertise earlier in 2017. As stated in Part V, just as natural gas became a resource, so is and will computational power. Companies are already gaining market share over the resources of Artificial Intelligence.

Amazon is a clear example that shows that data is valuable to its machine-learning process. In Part V we also discussed how Watson, IBM’s supercomputer, aids the medical industry so well that 90% of nurses in the field follow Watson’s guidance. Further, we have found that supercomputers, or vast amounts of computational power, with enough data, will eventually be what supports AI to solve such social issues as a cure for cancer. We see that AI programs are applications that are fueled by distributed computational power. Feeding these programs can propel humanity to not only the next level but into the next Age!

So AI Is Smart and It Is Here. Will It Take My Job?!?

So the question becomes, will this new application that will power the next industrial revolution put humans out of work? This is a debatable subject which I personally, believed before, that AI ‘would’ put humans out of work, that is until I read The Fourth Age by Byron Reese. Reese stated in chapter 9, “The accusation that technology is a net job destroyer has been argued for a long time. In the 1580s, William Lee invented the stocking frame knitting machine. He pulled a few strings and arranged to give a demonstration of his device to Queen Elizabeth in the hopes of obtaining a royal patent. The queen thought the device cunning but remonstrated Lee, saying, Consider thou what the invention could do to my poor subjects. It would assuredly bring to them ruin by depriving them of employment, thus making them beggars.”

Lee, in fact, had to leave England because of the anger of the hosiers. Now, this was more than 100 years before the steam engine was invented! Literally, over 400 years, technological advancement has been a constant topic that machines will put workers out of business and end up as beggars! So, can you tell me, how many hosiers do you know on the side of the street begging? Reese articulates many other examples; not only how technology and machines have been progressing over the last thousand years, but specifically the major advancements. Such as the invention of fire, the steam engine, computers, and finally, AI. He points out that throughout all of those years, yes, people may have lost their job, but each new invention enabled new jobs which not only replaced the old jobs but created more jobs than before. The fact is that there is historical proof that machines and technological advancement in both mechanical and cognitive industries simply enable humans to perform better! The more efficient we become, the more tasks we can complete, and the more resources governments and organizations gain through such technological aides. This allows more opportunities and resources which in turn creates more jobs and activities for people.

So no, AI is not going to put 50% of the workforce out of the job forever, that won’t happen. Society will adjust as they did over the past 500 years during the rise of mechanical and cognitive machines. Yet one thing is for certain, the more access humans have to AI, the more AI has access to processed data, this simply means the more productive and efficient humans and societies can be.

Aritificial Intelligence: Centralized or Decentralized?

We now know that AI is not just a little computer program. It is an absolutely powerful Application that is becoming an even more valuable resource. So the question becomes, should this Application be built and controlled by one central entity, or should it be an Application built on top of a decentralized and distributed secure network which ‘ANYONE’ is free to use? Don’t forget now, in Part II — The Internet of Things and the Solution to Centralization…, I discussed how the Internet of Things cannot be built on a centralized protocol layer, which only leads to network weaknesses and central-point-of-failures.

Siemens FABRIC — https://vimeo.com/345494979

The above video is a clip by Siemens FABRIC. I don’t know much about it but it shows that Siemens is creating a system to record, access, and analyze data to create and a new ‘smart city’. It clearly shows the valuable resource in which they call, ‘patterns’, or, data. These patterns of the city are simply data that an AI can process and analyze. As they say, the FABRIC will develop a digital eco-system. Again, AI is here, the question becomes do we want companies like Siemens, Facebook, or Amazon controlling them?

The Tangle offered the solution of a decentralized, distributed and secure protocol in which the Internet of Things can be built upon. In Part IV — The Qubic Network!, I showed how the Qubic network layered on top of a secure decentralized protocol, offering a seamless data processing method to not only validate but provide data in a digestible source for applications. In Part V-But what about the computational resource? The natural gas to oil in the digital realm!, I described how the Qubic Network uses QCM written in a Ternary programming language specific to IoT for lightweight edge devices; as well, ABRA offers a language to enable QCM which creates a decentralized market place for the worlds computation resource. Now, we can start to see how these puzzle pieces start seamless fitting together with one another. We have a secure decentralized protocol, a processing and data validation layer, specific programming language to allow access to the worlds distributed resource of computational power and when you put that all together, what kind of application can be run? The Answer, AiGarth.

One of the main visionaries that imagined a world where the global computational resource can be harnessed and used for Artificial Intelligence, a power so great, that it should only be shared with all of humanity. A valuable resource that should not be controlled by a few conglomerates or governments. One of the visionaries was Sergey Ivancheglo a.k.a Come-From-Beyond. He believed that he and the other founders could complete this challenge, even despite all odds. Yet, let us look at the facts. We have seen how companies inherently become central-point-of-failures for global networks, but what about Governments? Would they manage such a resource as AI with benevolence or with greed?

James Vincent on theverge.com discussed in the article, ‘Putin says the nation that leads in AI ‘will be the ruler of the world’.

Not only do industries understand the power and importance of AI, so to do governments.

“Artificial intelligence is the future, not only for Russia but for all humankind,” said Putin reports RT. The Verge stated, “the development of artificial intelligence has increasingly become a national security concern in recent years. It is China and the US (not Russia) which are seen as the two frontrunners, with China recently announcing its ambition to become the global leader in AI research by 2030.” Later in the article they wrote, “Putin noted that Russia did not want to see any, one, country “monopolize” the field, and said instead: “If we become leaders in this area, we will share this know-how with the entire world, the same way we share our nuclear technologies today.” So we have to imagine what it would be like if governments had such advanced technologies. Would they use it to support societies, or simply use it for their own advancement of control and power?

Take a look at the United States when they had access to more powerful technologies over other state nations. Watch the movie Snowden to see how the NSA tracked, and currently tracks, data on anyone and everyone!

How about China? They are looking to be the world leader in AI technology by 2030 as stated on The Verge? The BusinessInsider.com described how China, is currently tracking workers brainwaves! That is right, they have workers wear a device on top of their heads so companies and the government can track their brain wave data. They can assess whether the worker is fatigued, concentrating, happy, sad, or tired. Another story the BusinessInsider wrote that China has implemented a Social Credit System. It is no secret that China has an insatiable thirst for data and sees it is a resource to control its citizens and other nations.

So how about Putin and his comment, “If we become leaders in this area, we will share this know-how with the entire world, the same way we share our nuclear technologies today.” Here is a question, did the Russian government attempt to keep anything secret before and after the Chernobyl disaster?

The answer is yes! HBO’s Chernobyl is a great example of how Russia not only kept nuclear technological weaknesses of their reactors secrete from their own countrymen and women, but they also attempted to keep the Chernobyl incident a secret from the world.

These are a few facts which simply show that when governments have access to extremely powerful resources they regularly fail to act righteously and morally, and almost always act in greed and immorally. Seeing Microsoft buying AI startups, IBM focusing on gaining market shares within the cognitive industry, & Siemens focusing on Smart Cities, it is clear that companies like Google and Facebook not only seek to control data and AI, but they regularly fail at keeping that data and resources secure.

What will happen when they fail to keep such a powerful resource like AI secure as they have failed with our personnel data? Failing to build a secure AI global network has the possibility to lead to catastrophic consequences. The answer, Artificial Intelligence should be an application built on top of a decentralized and distributed protocol so everyone has the freedom of access, and everyone can see how each other are using it. In this way, we can avoid digital disasters like Chernobyl and attempt to secure some method of privacy from the prying eyes of big brother, and at a minimum, attempt to keep China from recording our minds!

So What is AiGarth Then?!?

The truth is I have no idea! However, if I try to focus on what is possible with the Tangle and the Qubic Network, we can imagine that it brings several variables together which can allow for AI to grow and thrive. Imagine, if AI was to be decentralized, and able to be accessed by all humans in a safe manner, what would that look like?

In Part IV we discussed how farmers can use data and Qubics to grow crops more efficiently. Well, as we have found, Data flows securely through the Tangle where the Qubic Network can then process it. With processed secure data, this creates fields of information in which AI’s can feed off of. Essentially is gardens, massive farms, and fields of the exact needs in which for AI’s to feed and grow.

We also saw in Part V how the Qubic Computational Model offers people a marketplace to put up their unused computational resource. The world’s resources can now power AI’s to process their algorithms and learn at a global scaled-up version. No longer will medical doctors have to wait in a queue to use a supercomputer, nor will governments keep their power secrete. Instead, AI can flourish and grow within a global digital world fed with unimaginable amounts of data and fueled by the power equivalent to hundreds of thousands of supercomputers. Doctors and scientists can have un-blocked access to AI technology to solve societies issues. Small companies that can not afford massive supercomputers as Facebook and Google can create their own business AI’s and compete within the industries. Non-profits who seek to protect citizens by keeping an eye on governments can use AI’s to ensure that governments are not using their AI’s immorally. AI as a resource is too precious to be kept by the few.

Further, through clustering, and environments controlled by Qubic Supervisors, AI’s can be tested within these controlled private Tangles. Instead of simply unleashing them out into the open, anyone will be able to test them first, ensure integrity, and then release them to the main nets. AiGarth is an Artificial Intelligence ecological digital environment allowing AI’s to be born, learn, grow, and solve issues that humans and machines wish to solve.

Conclusion:

Not only is the current world’s Data, Computational Resources, and AI Applications controlled by a select few governments and a select few companies, but non-of-them are freely connecting with, sharing, and working together for the betterment of society. Instead, we see governments hoarding power and companies seeking to gain market share. With the Tangle, the Qubic Network, and AiGarth, we can have a secure permissionless decentralized network which processes data and enables a digital computational marketplace so that the Global AI can be accessed and powered freely by everyone in the world.

Through a bit of research, we also found that AI is not going to take everyone’s job. Just as in the 1500s, technological advancement enabled humans to be… well… better humans. Society and humanity as a whole will become more proficient and efficient with AI. Yet if this power is controlled by the few, then only the few will advance. This ultimately will only exaggerate the divide between the ‘haves’ and the ‘have nots’.

We saw in the Siemens FABRIC video in which entire cities data can be collected, processed and analyzed for ‘patterns’. That this is an essential need for growing populations. All this data can be processed by AI’s and offer unimaginable advances and efficiencies making life better for all. This is the true IoT! That is the big picture. Most importantly: IOTA, the Tangle, Qubics, and AiGarth can solve many of the issues that come from centralizing data and AI technologies. The only true way for the world to progress is through decentralization. Only then, can AI help ‘all’ people, not just a few.

Yet there is still one last issue, one last challenge. How do we ensure data integrity at the source? How can we cryptographically hash the data within IoT devices at the edge, and potentially mitigate bad actors? This is a big question. There are immense power constraints with these types of operations to ensure such data integrity right at the source. In addition, with all of the immense data points and devices which have limited resources, could they act together? Could they shard and distribute large computations and then participate in a swarm? Could they work together with each individual’s small intelligence, and combine them into a digital swarm intelligence? I believe this is what the final puzzle shows. With Jinn, the Tangle, Qubics, and AiGarth, the machine economy can start to evolve with swarm intelligence, ensure data integrity from start to finish, and change societies as we know it. I will attempt to explain these aspects in Part VII — Living on the Edge! Jinn & The Swarm. The Last Puzzle Piece. When It All Comes Together, What Does It Make?