Money Magazine: How would you define Quantum Relations Intelligence in such a way that even a little child could
understand? Or for someone from a remote village without a proper education to empathize with?

Dr. Anwar ul Haque: QRI, or Quantum Relation Intelligence, is
an artificial intelligence method that mimics human
intelligence in understanding and reasoning. For example, if a
child is hungry and you feed it something, the next time he finds himself hungry and you give
him toys to play with, he will ask for chocolates because he knows that the hunger sensation is
handled with eating, not with playing. This is called the rule of Cause and Effect. So, QRI is
designed to understand the cause and effect in the data to find possible solutions to a problem
(s) similar to how a human brain functions.

Money Magazine: You say that “All things that are not language initially, such as images,
videos, measurements, and natural or abstract phenomena, can also be expressed in
language”. How?

Dr. Anwar ul Haque: QRI is not a linear brute-force learning technique; instead, it is a
causation-driven analysis system, so QRI can use any data expressed in terms of causation for AI
purposes, regardless of language or other cognitive representations such as pictures or objects.

Money Magazine: What technologies are crucial for the implementation of QRI?
Dr. Anwar ul Haque: The dynamic QRI technology stack supports all modern computer
languages and frameworks. However, the current stack is based on Python, Go, and Django on
the backend, MongoDB and Redis as storage engines, a combination of Rest and WebSockets as
middleware, React and React Native on the front end, and Kubs for deployments. This
combination of technologies is quite portable and scalable and can be deployed on clouds and
on-prem as well.
Money Magazine: What are the main practical applications of QRI in industry and research?
Dr. Anwar ul Haque: QRI is designed to handle and help modern-day challenges such as news
fact analysis, medical data analysis, geopolitical analysis, global energy generation,
consumption forecasting, and hundreds of other problems. However, more technical use cases
are analyzing infrastructural damage for bridges, dams, and buildings and backtracking to find
the root causes of damages, similarly analyzing healthcare data for diabetics or cancer patients
and trying to extract the root causes of the disease on a person-by-person basis using the QRI
backtracking capabilities. The backtracking analysis is not available to the world in any AI
technology outside of QRI.

Money Magazine: You also promote the importance of QRI in government intelligence. Would
it be an objective one or it could be manipulated politically?
Dr. Anwar ul Haque: Since the start of the platform, QRI has been operator bias-free. As you
know, QRI is not a continuous training system of AI that is trained over a multitude of data and
reflects the inferences (results) based on patterns available in data. So, you feed biased data to
the training program, and the inferences will always be biased, irrespective of whether you like
it. In the case of QRI, we do not train the model; instead, we integrate intelligence with every
packet of data and make them addressable using ecologic forward and backward-tracking
network technologies. We also feed them information related to their cause and the effects
they can have. This enables the data to be bias-free and self-intelligent. The framework then
acquires the data from the Data Fusion Object database of QRI, which is aligned with the cause
and its effect on the user query. So no training, no operator manipulation, and no bias. Yes, it
would be objective for the purpose, and this is a big opportunity but also a challenge for us to
sell and deploy QRI to governments for intelligence, as they often like to have systems they can
control and manipulate concerning the results. QRI, on the other hand, cannot be manipulated,
not even by its own creators.

Money Magazine: Can this QRI be applied to the medical field? In what way could it make a
change in saving people’s lives?
Dr. Anwar ul Haque: A recent publication of one of the QRI works was accepted and published
in Elsevier for analyzing pneumonia and COVID with limited data or CXRs. However, the
significant impact QRI is trying to bring in medical is to enable the system backtracking to find,
analyze, and control the root causes of certain diseases initially on a group basis and later
individually. So, for example, if you can see the root cause of getting diabetics, I am not talking
about all those given facts like stress, obesity, sugar intake, etc.; we all know that none of them
have yet been proven. Instead, I am talking about what happened to the DNA of the person
who is diabetic now and how that did happen to him. If we can solve this mystery, then we may
have control over the next occurrence or are ready for a solution to remove it.

Money Magazine:. What are the most common misconceptions about QRI that you encounter?
Dr. Anwar ul Haque: The most common misconception about QRI is that even people from the
field of AI take it as a deep learning system trained on data and generating results like the rest
of the world. We already have enough evidence that the current AI systems are not solving the
critical challenges of this world and, at the same time, creating a more significant problem by
consuming a huge amount of energy during the training phase. QRI does not have any Deep
learning-trained model to perform analysis. Instead, it is a complete cognitive and probabilistic
engine with integrated causation analysis to provide solutions. The second major problem we
encounter is that QRI is not a single model that helps you solve a minimal problem like counting
the number of people coming or going out of the door instead, it is a platform that is designed
to tackle significant global challenges, top-down and bottom-up; for example, global energy
demand and supply analysis, international news analysis, geo-political analysis etc.

Money Magazine: Did the “simple” artificial intelligence become inefficient or outdated in such
a way that experts found it necessary to find a way to improve it by adding relations?
Dr. Anwar ul Haque: Well, it is about something other than being outdated but cost and result.
So, if you want to understand the demand and supply of a city for energy, you train a model
using current AI systems and then deploy it for the work. The very next day, you find that the
model needs to account for the weather changes or infrastructure evolutions, you train the
model again; after that, you need to account for local customs of people for the usage of
energy, you train again, and the next day you account for local festivals that will happen
throughout the year you train again…. So it is a lifetime of training, and then you find that you
have already consumed enough energy in training, which already has surpassed the amount the
client was trying to save. The second problem is that you can only find correlations with current
AI systems, which may be suitable for seeing patterns and giving a response. Still, AI systems
are dumb when they find something out of a pattern, such as ZeroDay attacks.

Money Magazine: How do you think QRI will shape the future of work and society as a whole?
Dr. Anwar ul Haque: Once QRI has started making intelligent data for a sector or segment of
society, it enables many analyses that people can perform without going through all the hurdles
of training and inference. In that, you give people the power of dynamic causal knowledge and
analysis, which they can use to the fullest extent of their imagination. It is like enabling the
human race to move from the will of power to the will of knowledge. The only limiting factor is
the imagination they can develop.

Money Magazine:. Does a QRI Intelligence make better decisions for people than their own
brain?
Dr. Anwar ul Haque: The human brain is the most fantastic thing in terms of intelligence. The
only limiting factor is the human, who can learn and remember only a limited amount of data
and information, think and reason very slowly, and make inferences that may be colluded with
emotion. On the other hand, QRI is gradually progressing towards the technology of the human
brain but is currently free from storage limitations, processing speed, and negative influences of
emotions.

Money Magazine: Does this QRI have a belief? To what instance does it submit?
Dr. Anwar ul Haque: Well, QRI does have one. The knowledge any one of us has right now is
hardly a percentage of the knowledge of this world, and by applying the right technology and
mindset, we can uncover much more. QRI is a roadmap to ultimately unite and draw from all
global knowledge for the mutual benefit of all.