AI and Conquering the next frontier of the digital world.

1. Nadeem Abbas, Ahmad Ayaz
Mubashar Nisar, Muhammad Hamza
Inbasat Fiza
12-5-2017
A report on
Artificial Intelligence
Conquering the next frontier of the digital world.

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Abstract
This report explores the sub-disciplines of AI and the advancements in the field of Artificial Intelligence
in recent years with the discussion in the end whether the AI is really the future or a threat to humanity
as we know it.

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Acknowledgements
The Authors of this document would like to acknowledge nobody in creation and formation of
this report. We, however, are thankful to the BBP website for generously letting us use their
images for the report and “The Wired” science magazine that helped us achieve a better
understanding on different topics from their valued articles.

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Table of Contents
Introduction ..................................................................................................................................................5
Latest Tech....................................................................................................................................................5
Natural Language Generation...................................................................................................................5
Speech Recognition...................................................................................................................................5
Virtual Agents............................................................................................................................................5
Machine Learning Platforms.....................................................................................................................5
AI Optimized Hardware.............................................................................................................................6
Decision Management..............................................................................................................................6
Deep Learning Platforms...........................................................................................................................6
Biometrics .................................................................................................................................................6
Robotic Process Automation.....................................................................................................................6
Text Analysis and Natural Language Processing.......................................................................................7
Google Brain..................................................................................................................................................7
Recent Breakthrough Advancements .......................................................................................................8
Artificial Intelligence Devised Encryption System.................................................................................8
Image Enhancement .............................................................................................................................8
Google Translate...................................................................................................................................9
Blue Brain Project .........................................................................................................................................9
Major Accomplishments:..........................................................................................................................9
Development of Rat Cortical columns ..................................................................................................9
Higher Dimensions in Neural Networks..............................................................................................10
AI: Good or Evil?..........................................................................................................................................11
Lack of Judgment ....................................................................................................................................11
Misaligned Intelligence...........................................................................................................................11
Singularity ...............................................................................................................................................11
Conclusion...................................................................................................................................................12
References: .................................................................................................................................................13
Appendix .....................................................................................................................................................14

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Introduction
Before we start on the artificial intelligence, let us define the word “Intelligence” itself.
The intelligence is defined in the Cambridge Dictionary as “the ability to learn, understand, and
make judgments or have opinions that are based on reason”. Machines possessing the same
ability are said to be artificially intelligent. We can define the artificial intelligence as the ability
of machines to efficiently perform the tasks that usually require making appropriate and logical
decisions or simply the intelligence of humans.
Today, the artificial intelligence systems are actively changing multiple aspects of our life
and the AI market is rapidly prospering. Many of the companies have already decided to invest
in the field of Artificial Intelligence to nurture and invigorate their business. An estimation of this
can be taken by the study performed by the Forrester Research [1] that predicted an increase of
300% in the investment in AI this year (2017) as compared to the last.
Latest Tech
We will now discuss some of the latest key technologies of Artificial Intelligence that are
developed or are being developed today to improve the AI.
Natural Language Generation
Natural language generation or NLG is a sub-discipline of Artificial Intelligence that deals
with the translation of data into human understandable text. Use of this tech enables the
computer to relay the information and ideas effectively and accurately.
Speech Recognition
Today we see a lot of speech recognition softwares that understand the verbal commands
of the users and respond appropriately. Everyday new systems are being introduced capable of
transformation of human languages into computer understandable languages. Its current
applications lie in the interactive voice response systems and mobile phone and tablet apps.
Virtual Agents
A virtual agent is a computer system capable of interaction with humans on its own. The
chatbots are one example of the virtual agents. Currently these systems are being used in the
industry as tech support and customer care service. Another use of the virtual agents is as smart
personal assistant.
Some of the examples of the implementation of the virtual agents include the iPhone’s
personal assistant “Siri”, the Google’s “Google Now” service and Microsoft’s “Cortana”.
Machine Learning Platforms
Another aspect of artificial intelligence is learning through experience. Machine learning
platforms are being improved day after day by the use of algorithms, APIs (application
programming interface), development and training tools etc.

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Machine learning platforms are being used in industry mainly for classification and trends
prediction. These platforms receive big data for the users and try to identify any patterns to order
and assemble it appropriately. They use these patterns to later make smart decisions. For
instance, if such a platform receives the data of a stock market, it will cleverly and intelligently
analyze the data and then suggest the user the optimal place to invest.
AI Optimized Hardware
The human brain operates at an estimated 1 exaFLOP, equivalent to one billion billion
floating point operations per seconds. On the other hand, the latest processor in the market, the
Intel core i9-7900X, has about a teraFLOP of processing power. Another slightly powerful GPU,
the Nvidia Volta has a processing power of about 120 teraFLOPs. If we were ever to replicate the
human intelligence and put it in a machine, we would need to have the hardware on a par with
the human brain’s computational power. To make it possible, researches are being made to make
better-than-the-brain hardware specifically to execute AI oriented jobs.
Chip and hardware designing companies like Nvidia, Intel, IBM etc. are the leading
researchers in this field.
Decision Management
Intelligence requires appropriate and optimal decision making. Decision management is
making the machine intelligent enough to make its own decisions in maintenance, tuning and
setting up. This tech is incorporated in many systems that help in making the right decision by
analyzing data (like explained above).
Deep Learning Platforms
Deep learning is also a sub-discipline of Artificial Intelligence. It is a special form of
machine learning that is done by mimicking the human brain’s multilevel structure and function.
This tech involves learning through the use of artificial neural circuits with various abstraction
layers. Deep learning is one of the major subjects of Artificial Intelligence with its application in
various subdomains like Automated speech recognition, image recognition, visual art processing,
natural language processing, bioinformatics, recommendation systems, pattern recognition etc.
Biometrics
Biometrics deals mainly with the measuring, analyzation and identification of the physical
aspects of human body and human behavior. With this tech a more natural interaction between
humans and machines can take place by the use of touch, speech, image and physical recognition
of human body. Mostly this tech is being used for security purposes and for market research and
analysis.
Robotic Process Automation
Robotic process automation is the automation of robots by mimicking human tasks by the
use of intelligent scripting to help perform the tasks that normally humans are unable to do. It is
currently being used in the scenarios where the use of human resources is either dangerous,

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inefficient or costly. As humans cannot, with current technology and resources, take part in the
deep space exploration missions, robots with artificial intelligence are used instead.
One good example of it is the NASA’s Curiosity Rover, an automated robot being used to
explore the red planet, Mars.
Text Analysis and Natural Language Processing
Text analysis and natural language processing is relatively common and more broadly
used than the above mentioned other techs. This technology uses statistical methods and
machine learning to analyze text and the sentence structure to understand its meaning and
intention.
This tech is currently used for fraud detection and security systems. A more common use
of text analysis and natural language processing is in automated virtual personal assistants and
chatbots to understand textual input data and its translation to computer understandable form.
Above explained are some of the latest AI technologies that are being implemented in
today’s world in fields of business and industry, but the uses of AI are not limited to industrial
purposes. Artificial intelligence is slowly starting to work its way into every field of life like
Aviation, transport, medicine and healthcare, robotics, video games, education, military,
marketing, communication and networking and many others.
Now, we’d bring to light some of the significant Artificial Intelligence projects that are
being worked upon to create perfectly intelligent, autonomous, self-aware, creative and self-
sustaining machines. These projects, when completed, will be the true examples of Artificial
intelligence.
Google Brain
Google Brain is a deep learning Artificial Intelligence research project at Google. This
project is actually a combination of machine learning with system engineering with large scale
resources that Google can easily provide. Researchers at Google aim to create a self-learning
general purpose Artificial Intelligence system that would be the first of its kind.
The aim of this project, in the words of the Google Brain team, is described as thus, "Our
mission in the Brain team is to make machines intelligent and improve people’s lives. We do this
through deep learning research, a subfield of machine learning, focusing on building highly
flexible models that learn their own features, end-to-end, and make efficient use of data and
computation. [2]" (Google Brain Team (2017). Google Brain Team's Mission [Blog Post]. Retrieved from
https://research.google.com/teams/brain/about.html)
Back in the year 2011, the project was initiated by two google researchers, Jeff Dean and
Greg Corrado, and a Stanford University professor, Andrew Ng, as a part time research

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collaboration. Google brain started as a Google X project but due to its huge success, it was
graduated back to Google.
Recent Breakthrough Advancements
Let us have a brief look at some of the breakthrough advancements that Google Brain
recently achieved.
Artificial Intelligence Devised Encryption System
In 2016, Google Brain ran an experiment with three AI entities two of which had to
communicate using encryption whereas aim of the third was to attempt and crack the encryption.
The AIs generated their own cryptographic encryption at the same time attempting to keep it
safe from the intercepting system.
In this experiment the three AIs generated were named Alice, Bob and Eve. Alice had to
send an encrypted message to Bob who would decrypt it and at the same time Eve had to try to
intercept and break the encryption. Alice and Bob were not given any instruction on how to
encrypt the communication. The system was only given a loss function. The prediction was that
if communication between Alice and Bob were not successful, either Eve would have intercepted
the message or Bob miscalculated the meaning of the message from Alice. The communication
will be successful if Alice and Bob successfully communicate without Eve being able to decrypt
the message resulting in evolution in the field of cryptography and AI. The latter proved to be the
conclusion as the AIs devised their own encryption method without any prescribed encryption
algorithms, proving to be a breakthrough for encryption in the future.
Image Enhancement
In February 2017, an image enhancement system was introduced by the Google Brain.
This system uses neural networks to enhance and put more details in low resolution images.
The system uses two neural networks that work together to enhance the images. The first
neural network, called “conditioning network”, generates a high-resolution image similar to the
low-resolution input image and then lowers its resolution to 8x8. The second neural system,
called “prior network”, analyses and adds details to the pixelated high-resolution image by the
use of a large number of images. The input image is then upscaled and more pixels are added to
it on the basis of the knowledge of the system about how the image should look. Output of both
the networks is then combined to create the final image.
The added pixels are not part of the original image rather the best guesses about what
the image should be. The results of experiments show a breakthrough in the field of image
enhancement and deep learning.

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Google Translate
A relatively common implementation of the Google Brain is in the Google’s translation
service “Google Translate”. In September 2016, google launched its neural machine learning
system called “Google Neural Machine Translation” (GNMT). It is a learning framework that uses
the help of a large number of examples to improve itself. Introduction of GNMT made the Google
Translate service exponentially better with the experimental languages but the improvement of
all the 103 languages available in the application proved to be a difficulty. In an attempt to solve
this problem, a multilingual GNMT was created by the researchers at Google that enabled
translation between different languages. It even allows the translation to be possible between
two languages that the system never had seen separately and explicitly. Now, it’s even possible
for Google Translate to convert the speech of one language directly into text of another without
converting input to text only with the help of the Google Brain’s neural networks. To make this
work, researchers exposed the system to hours of speech of a language and its corresponding
textual translation in another. The multiple layers of neural networks of Google Brain, replicating
learning method of humans, were able to map the corresponding text to the speech.
Google Brain is progressing and getting near its objective with each passing day. An
artificial intelligence system of this scale surely will have a huge impact on humanity.
Blue Brain Project
Initiated in March 2005 as a collaboration between EPFL (Ecole Politechnique Fedarale de
Lausanne) and IBM, Blue Brain is a Swiss project, a project with the intent to reconstruct a digital
replica of brain by reverse engineering of the neural circuitry of the mammalian brain. The
primary goal or objective of this project is to achieve a better and more accurate view on the
fundamental principle of human brain structure and function by simulating brain activity on a
digital reconstructed human brain to bring improvements in the fields of health and fighting the
diseases.
The project uses the resources of Blue Gene Supercomputer using the NEURON software
that provides not only artificial neural networks but the biologically realistic digital replication of
the neurons. It is said that, with the tech in use, the project will eventually help us understand
the concept, nature and reality of consciousness.
Major Accomplishments:
Development of Rat Cortical columns
At the moment the researchers are trying to replicate and simulate the neocortical
column of a rat that has almost 10,000 neurons unlike the human neocortical column that has
six times more neurons than the rat’s neocortical column. The researchers are now very close to
completing the replica of a rat’s neocortical column.

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Higher Dimensions in Neural Networks
Wrapping the mind around the concept of multidimensional structures would be
impossible of most of the people. Human imagination is a prisoner of the three-dimensional
world even though the human brain operates at a multidimensional level.
Researchers of BBP published a research in Frontiers in Computational Science [3] six
months ago that shows the groundbreaking discovery of the structures and spaces of as many as
eleven dimensions. These structures arise as a result of neurons joining together to form a clique
(A structure formed when a neuron connects to all the other neurons in a cluster in a specific way
to create a very accurate geometrical shape). The number of neurons in a clique is directly
proportional to the dimensions of the geometrical shape formed.
In this research, to confirm if the formation of multidimensional cliques were not
incidental, the researchers provided virtual brain tissues with a stimulus in response to which the
cliques of higher dimension assembled momentarily to enclose high-dimensional holes, called
cavities. Researchers say that it is as if the brain reacts to stimulus by assembling and
disassembling a pillar of multidimensional blocks starting with rods, planks, cubes, hypercubes
and then higher dimensional complex geometrical shapes.
“Topology in neuroscience: The image attempts to illustrate something that cannot be imaged – a universe of multi-
dimensional structures and spaces. On the left is a digital copy of a part of the neocortex, the most evolved part of the
brain. On the right are shapes of different sizes and geometries to represent structures ranging from 1D to 7D and
beyond. The “black-hole” in the middle is used to symbolize a complex x of multi-dimensional spaces, or cavities.”
Frontiers Communication (2017, June 12). Blue Brain Team Discovers a Multi-Dimensional Universe in Brain Networks [Blog
Post]. Retrieved from https://blog.frontiersin.org/2017/06/12/blue-brain-team-discovers-a-multi-dimensional-universe-in-
brain-networks/.

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Surely, AI is gaining a lot of popularity because of the revolutionary advancements in
different fields but with it arises the question that’s being asked since the day the concept and
idea of Artificial Intelligence was first presented. The question of whether the AI will ultimately
surpass humans and establish their supremacy over mankind or would the AI remain submissive
and under human control, working as desired by the humans.
AI: Good or Evil?
At the moment, this discussion is a heated topic of debate in the scientific circles related
to Artificial Intelligence. Leading scientists are making speculations and putting forward theories
as of what will be the outcome if an AI is developed that is better than humans at everything and
what the consequences will be in case of an intelligence explosion due to recursive improvement
of Artificial Intelligence.
Lack of Judgment
The AI machines we currently have aren’t that much intelligent and lack judgment and
decision-making qualities. If these machines were to be hacked in by anyone with destructive
objectives, the machine wouldn’t think twice before execution of the commanded operation. An
example of it would be a scenario where the automated weapons fall into the wrong hands.
Misaligned Intelligence
If we were to ask an artificially intelligent system to achieve certain goals but fail to explain
the desired way of doing it, the AI might take a destructive route in the process of achieving its
goals. The AI would literally be solving the problem but in the process, it would be doing more
harm than good. For instance, if we program a self-driving car to take the shortest route possible
and arriving at the destination as fast as possible and the car ends up going through the park,
running over the pedestrians and involving itself in a police pursuit. In this case we would get the
thing we asked for but just not the way we wanted it. Similarly, if an AI is made for environmental
improvement, the AI might end up destroying the things that it’d perceive as a hinderance in for
it to achieve its goal even the humans if they attempt to stop it.
Singularity
Technological singularity is a hypothesis that introduction of an artificial super intelligence
will bring abrupt and revolutionary technological growth and changes in the human civilization
as we know it. One of the main concerns was highlighted by “The Independent” in the words,
“One can imagine such technology outsmarting financial markets, out-inventing human
researchers, out-manipulating human leaders, and developing weapons we cannot even
understand. Whereas the short-term impact of AI depends on who controls it, the long-term
impact depends on whether it can be controlled at all.” [4] (Stephen Hawking, 2014)

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Conclusion
The discussions such as these have no actual conclusion whether the AI will have a
positive impact towards building a better future or if that future will be destroyed by the
machines. Researchers have their hopes high despite the controversial theories by the scientists
and public. There is a speculated time of about at least a decade or two before a super intelligent
machine is built which is enough time to make the appropriate changes to avoid a situation where
the machine might become destructive because of the intelligence it possesses.
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References:
[1] https://www.forbes.com/sites/gilpress/2016/11/01/forrester-predicts-investment-in-artificial-
intelligence-will-grow-300-in-2017/#4d9e1aa75509
[2] https://research.google.com/teams/brain/about.html
[3] Michael W. Reimann, Max Nolte, Martina Scolamiero, Katharine Turner, Rodrigo Perin, Giuseppe
Chindemi, Paweł Dłotko, Ran Levi, Kathryn Hess, Henry Markram. Cliques of Neurons Bound into
Cavities Provide a Missing Link between Structure and Function. Frontiers in Computational
Neuroscience, 2017; 11 DOI: 10.3389/fncom.2017.00048
[4] http://www.independent.co.uk/news/science/stephen-hawking-transcendence-looks-at-the-
implications-of-artificial-intelligence-but-are-we-taking-9313474.html
google brain: https://www.wired.com/2013/04/kurzweil-google-ai/

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Appendix
1. The Loss Function:
“Given a prediction and a label, a loss function loss function measures the level of discrepancy
between the prediction of the algorithm and the output we desire.”
https://github.com/JohnLangford/vowpal_wabbit/wiki/Loss-functions
2. FLOPs
“in computing, FLOP or sometimes FLOPS stands for “Floating point Operations Per Second”, a
unit used for calculation of computational power.”
https://en.wikipedia.org/wiki/FLOPS
3. Neuron Software
“Neuron is a simulation software used for simulating and making models of neurons and neural
networks.”
https://www.neuron.yale.edu/neuron/