Artificial intelligence, machine learning and intelligence

Over the
past two years, the development of Artificial Intelligence and the new
techniques for using Big Data has become both faster and more widespread.

 According to the old definition, by Artificial
Intelligence we mean teaching a machine to think like a man, while Big Data is
such a large mass of data in terms of quantity, speed and  variety that it has to enable specific
technologies and methods to extrapolate data from news already learned and
extract new data and links from the news which seem unrelated to one another.

 This ranges, for example, from the analytical
forecast of buyers’ behaviours -by always using machine learning – to the
inference of relations between single data and sequences of phenomena. Just to
make an example, each buyer wants a specific reward.

 Currently we also have the possibility of
developing  Generative Adversarial
Networks (GANs), which create objects not existing in reality, but similar to
reality, as well as faces that have never been seen before but are quite
probable, and objects that do not exist but seem to work well.

  Not to mention the self-correcting systems
based on concepts that are adapted by the machine itself, as well as programs
that self-create themselves, starting from a small nucleus.

 In the United States, the total investment in
AI companies is already worth 2.3 billion US dollars.

 According to the analysts of this specific
market, however, there are some trends which will emerge shortly and will make
the difference among the various global competitors.

  Reinforcement learning, for example, is a
technique enabling the software used to maximize a cumulative reward. An
information reward or even a reward in terms of speed in data search.

 A sort of Pavlovian algorithm favoring the
most suitable AI network and, above all, more capable of creating new
algorithms during its “evolutionary” activity.

 This AI device is needed for robots, but – as
can be easily imagined – also for university training or for health, especially
for arranging therapies for chronic diseases or even for analyzing and
forecasting the share flows on the markets.

 There is also Artificial Intelligence for
quantum computing, i.e. a technology used by the computers operating with
quantum physics.

 Besides processing information in the
“classic” way, quantum computers use two specific characteristics of
the quantum system, i.e. overlapping – where two or more quantum states can be
added together – and entanglement that implies, in a counter-intuitive way, the
presence of many remote correlations among all the physical quantum states
examined.

 Hence an availability of data and calculation
speeds, enabling to carry out previously unimaginable operations: the analysis
of continental climate change; the world economic cycles of raw materials; the
number and physical constants of galaxies in space.

 In the future, there will also be convergence
between AI and the Internet of Things, which will make both the construction of
vehicles and their driving autonomous.

 Another short-term integration will be between
blockchain technology and Artificial Intelligence.

 We have often spoken about blockchain, but in
this case it is above all the integration between the blockchain
“closed” network and a selective data collection or, otherwise, a
patented and still secret technology.

 Another promising AI sector is facial
recognition, as well as the specialized programs’ ability to recognize
manipulated data.

 We can easily imagine to what extent this algorithm
is important in intelligence analysis.

 We will also have complex neural networks
available for “deep learning” but, above all, we will have the
possibility of developing very complex and highly predictive socio-economic
models.

 Deep Learning is the AI automatic learning
network using concept or sign hierarchies, where higher-level concepts are
defined by lower-level concepts. Identifying the genetic sequences of some
diseases, as well as identifying tumors with X-ray and arranging an automatic supermarket
are all Deep Learning operations.

However,
there will also be significant developments in privacy protection and in the
development and processing of natural language, both for Deep Learning, which
often uses personal data, and for the other AI techniques.

 Hence how do major countries act, faced with
this new extraordinary technological and productive opportunity?

 China has entered the global AI “first
level” as early as 2017, while it sells many weapons with Artificial
Intelligence content in the Middle East (Saudi Arabia and the United Arab
Emirates) and in the areas where it is not possible to trigger competition
between China and the other countries having AI technologies.

 For the Chinese People’s Liberation Army, war
is currently shifting from the destruction of the “conventional”
enemy  to the operations for harming and
eliminating the enemy, which are based on AI, but are extremely fast and aim at
the enemy’s complete destruction.

 For China, in the future war will be a
“confrontation of algorithms” and not a clash of “forces”.

 In addition, President Xi Jinping and his team
believe that, as the role of AI is expanding in both the civilian and military
systems, China must rely ever less on imported technologies and ever more on
those developed within China.

 Precisely in October 2018, President Xi
chaired a special Politburo on AI.

 Hence strategic, scientific and technological self-centeredness,
together with the achievement of world hegemony.

 An important strategic element in the Chinese
AI doctrine is the need – raised by some leaders as early as 2018 – to
“avoid the AI global threat” and hence set some global checks at
multilateral level, as happened for nuclear and chemical weapons.

 A recent document drafted by the China Academy
for Information and Communication Technology already speaks openly about
international standards that can put AI under control.

 Furthermore, the Chinese military
decision-makers are already thinking about a future war “without
fighters”, with weapons fully independent from man and even transported
autonomously.

 Currently China is already exporting most of
its aerial drones to the Middle East, including the latest generation ones,
which are almost all remote-controlled.

 China, however, also shows strong interest in
military robotics and, particularly, in automated military decision-making.

 In China’s current doctrine, there is – first
and foremost -intelligence supremacy, which is almost naturally followed by AI
dominance.

 In Xinjiang, for example, Artificial
Intelligence is already used against local terrorists.

 In this case, AI technologies are used to
identify and track all terrorist activities, both through the sensor network
and by means of facial recognition technologies and the recognition of other
physical characteristics.

 Moreover, the Chinese government has
established two new research centres in the AI field, namely the Unmanned
Systems Research Center and the Artificial Intelligence Research Center.

 They are dedicated to the AI dual use research
-both civilian and military research – but, despite other countries’ undeniable
AI development, China wants to become the top country in the field of research,
AI patents, venture capital invested in AI and number of companies dealing with
Artificial Intelligence. Finally, it wants to become the largest pool of talent
in the world.

 With specific reference to the analysis of its
own strategic weaknesses, currently China perceives it has AI limits in terms
of best researchers; technical standards used; the quality of software
platforms and the evolution of semiconductors – which is essential for
developing advanced software systems.

  Chinese leaders find other technological
limits of their country’s AI project in the specific hardware for AI platforms
and in the evolution of algorithms.

 Currently the “best” AI experts are
approximately 204,575 worldwide.

 The United States currently has at least
28,536 of them and China, which is already ranking second, has over 18,232 of
them.

 China, however, is still ranking only eighth
in the list of  Top AI talent, with mere
997 AI scientists at the highest levels, compared to 5,518 in the United
States.

With
specific reference to the search for new AI technologies and markets, in its
official documents China argues that we should always “abide by market
mechanisms, but step up the marketing of AI technologies to create a
comparative advantage. Finally, Chinese operators must always well understand
the division of labour between the market and the government.” Marketing to
create a comparative advantage is a very interesting concept to evaluate
China’s Artificial Intelligence strategy.

 For China the turning point will be the
development and autonomous innovation in the semiconductor industry, which
currently – as in the past – is at the core of information technologies, at
first, and later of AI technologies.

 In the future, the new AI technologies will be
quickly marketed in China to support the financial effort for their
implementation and, above all, to keep on operating with the old mass tools and
instruments in the intelligence field.

 In abstract terms, however, which are the
factors of national power in the AI era? Firstly, a large amount of useful data
must be available.

 In fact, AI will greatly increase the power of
the countries capable of identifying, acquiring and applying the data sets
enabling to develop new effective AI architectures.

 More data, more algorithms. More algorithms,
more accuracy and complexity.

 Furthermore, considering that the abilities
for developing AI are still very rare in the research community, the Artificial
Intelligence competition will be won by the country that will invest a great
deal of resources in research but, above all, in the salaries and scientific
equipment of AI researchers.

 Nor should we forget the resources for
calculation, which must already be very large.

 Currently the most powerful computer in the
world is already Chinese.

 Then there must also be the political or
economic incentive to adopt AI in business, in companies or in offices.

 With specific reference to investment, a sound
correlation is also needed between the private and the public sectors.

 China is favoured from this viewpoint,
considering its link between the military and scientific academies, while the United
States shows some limits.

 These limits are inherent in the Silicon
Valley’s private operating logic and in the scarce relations between it and the
military decision-makers.

 Finally, however, there is also a smart – and
not mythological – assessment of privacy regulations.

 The countries that – sometimes
obsessively-give priority to privacy over other regulations, are obviously
slower in developing advanced AI technology.

 Here again material technology is decisive in
itself:  the evolution in graphics cards,
the chips with particular characteristics and the evolution of hardware enable
to achieve not the abstract possibility of Artificial Intelligence, but its
operational existence.

 Without a specific level of technology already
reached, AI is simply impossible.

 Apart from the United States and China, Israel
invests in AI for both commercial and military reasons: currently Israel has
already collected a total amount of 7.5 billion dollars to invest in AI, with
950 small companies, 51% of which use machine learning technologies.

 The Russian Federation has long been investing
a great deal of resources in AI and robotics.

 Last year Russia even doubled its AI
investment while, according to its military leaders, “robots will be the
real protagonists of the future war”, while Russian military staff is
already tending to the “complete automation of military space “.

 The well-known Kalashnikov company has already
studied and marketed a series of autonomous weapons, managed by AI neural
networks. In the near future, however, there will be Russian robotic nuclear
submarines, in addition to the Armata T-14tank – also incorporating AI
technologies -which has already been used in Syria.

 Here the legal matters to which China
sometimes refer are linked, above all, to the Convention on Prohibition or
Restrictions on the Use of Certain Conventional Weapons which may be deemed to
be excessively injurious or to have indiscriminate Effects, a Geneva Convention
of 1981 signed by 50 States.

 While the aforementioned Convention applies to
the new killer robots and lethal autonomous weapons systems (LAWS), Russia, the
United States, China and Israel must obviously put new types of LAWS into
action.

 They are certainly not robots like those of
the 1960s comics, but conventional weapons, at least apparently, which decide
for themselves – without human command and control – who must live and who must
die.

China,
however, agrees with the new LAWS criteria, but the fact is that: a) LAWS
weapons are decisive for the future battlefield; b) China has already decided
and established the technologies suitable for the future LAWS; c) China has
developed even more advanced weapons, in relation to the new growing powers.

 The new arms race will always take place
within the AI context.

 With specific reference to Russia, however,
additional considerations must be made.

 In 2014, Russia’s political and financial
system defined 9 high-tech sectors, in view of Russia producing these AI
technologies by the end of 2035.

 The projects are AutoNet, AeroNet, EnergyNet,
FinNet, FoodNet, HealthNet, MariNet, NeuroNet and SafeNet, which are basically
all AI networks.

 So far 1,400 AI projects have been carried out
in Russia. According to the Russian government’s forecasts, the AI and machine
learning market is expected to increase by at least  three times within 2020 while, over the next
five years, 80% of decisions in financial markets will be taken through AI,
while 50% of the service sector will still be dominated by AI techniques, in
both the field of e-commerce and of other types of trade.

 There is also Singapore, a small but powerful
hub for Artificial Intelligence.

 Finally, there is South Korea, which uses AI
for its financial and export markets but, above all, to control the
Demilitarized Zone on the border with North Korea.

 Hence, in principle, we could say that AI
operates preferably in capital-intensive countries.

 Certainly, with specific reference to the AI
military issues, in the United States there is Google, which can be partly used
by strategic networks, but China has full State control of the Internet, which
allows a huge collection of data to later process some “useful”
algorithms.

 In principle, we have already seen China’s
future AI strategy.

 Conversely, so far the United States has not
had a real national AI strategy, although currently – after some documents of
the White House during Barack Obama’s Presidency, but above all after some
decisions taken by President Trump – AI has been integrated into the Defence
sector and is examined in relation to the possibility of creating a private
market leading to the victory of the US Artificial intelligence over the
Chinese or Russian ones.

 Among the countries which are less interested
in or capable of achieving AI hegemony, there is also India, which is
interested in the Artificial Intelligence applications in the  agriculture and administration sectors, while
it deals with automated land vehicles and robotics in the Defence field.

 In April 2018 the European Union developed a
“Strategy for Artificial Intelligence”, with 20 billion euros of
public and private investments until 2020 and additional 20 million in the
following decade.

 There will also be a group of EU experts,
although we do not know yet who will appoint them. This group will deal with
the ethical guidelines for the use of Artificial Intelligence.

 The Italian public investment for the Internet
of Things and Artificial Intelligence must be placed within this framework. In
the public budget for the period 2019-2020, this investment is expected to be
15 million euros. There is no need for further comments.

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