Impacts and ConsequencesThe main critical uncertainty related to the American move is first the level of this commitment and then its consistency over time. As a result the survival of the Syrian autonomous region, the Kurdish-led Federation of Northern Syria has also become more uncertain. The outcome in terms of American regional and global influence is also uncertain.The main other impacts areLower likelihood to see rapidly a constructive peace settling in for SyriaLower likelihood to see the creation of a Federal SyriaRising Middle East tensionRising global tensions, notably with the U.S. on the one hand, Russia, China, Turkey, and Iran on the other.(Nota: The symbolic board has been moved to the end of the analysis and before the sources/signals)Facts and analysisFor …
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In 2017, Bitcoin, a digital currency launched in 2009, monopolized international finance headlines. On 1st January 2017, a Bitcoin was worth 972 USD while one year later, on 1st January 2018, you would have needed to invest 14.000 USD to buy a single token, down from nearly 20.000 USD on 17 December 2017. Considering the same timeframe, its market capitalization rose from 15,5 billion to 233 billion US dollars, after having reached its peak on 17 December 2017 at 335 billion (Cryptocurrency Market Capitalizations).
Bitcoin, however, is just the tip of the iceberg. Underneath there is a whole universe of cryptocurrencies (nearly 1400) which value and market capitalization has skyrocketed in the last months of 2017. At the time of writing, on 8 January 2018, 40 cryptocurrencies have a market capitalization of 1 billion US dollars or more. As of 18 December 2017, they were 29.
First of all, what is a cryptocurrency? According to the Cambridge English Dictionary, a cryptocurrency is “a digital currency produced by a public network, rather than any government, that uses cryptography to make sure payments are sent and received safely”. Indeed, cryptography is used to implement the blockchain technology, which is at the base of Bitcoin and other major cryptocurrencies.
This article will explain further what a cryptocurrency is, focusing on the most common underlying technology, the blockchain, and its implementation relative to the top two cryptocurrencies by market capitalization: Bitcoin and Ethereum (respectively at 253 and 118 billion US dollars as of 9 January 2018). We shall also include in our analysis the third most-capitalized crypto: Ripple. It will thus underline commonalities and differences between the three cryptocurrencies, starting highlighting their potential advantages and dangers compared with classical international currencies. It will notably single out one of the main challenges characterizing the Bitcoin phenomenon: energy sustainability.
With the next article, we shall analyse the rise of Bitcoin and other cryptocurrencies, highlighting that climb’s main drivers. In conclusion, we shall try to understand if cryptocurrencies pose a long-term threat to traditional currencies and, therefore, to the US dollar supremacy over the international monetary system.
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About the author: Leonardo Frisani (MA Paris) focuses currently on challenges to the US Dollar supremacy. Beyond that, his specialisation is in international security, and his main interests are in geopolitics, macroeconomics, climate change, international energy and history.
Main references
Bradbury, D. (2014), “Congressional Report Warns of Potential Bitcoin Threat to US Dollar”, CoinDesk, 9 January 2014.
Brown, A. (2013), 10 things you need to know about Ripple, CoinDesk, 17 May 2013.
Cheng, E. (2018), Second-largest cryptocurrency Ripple may have run ahead of itself, CNBC, 5 January 2018.
Gupta, V. (2017), Programmable blockchains in context: Ethereum’s future, by Vinay Gupta, Medium, 1 May 2017.
Henry, D. and Irrera, A. (2017), JPMorgan’s Dimon says bitcoin ‘is a fraud’, Reuters, 21 September 2017.
Kaminska, I. (2018), The Ripple Effect, Financial Times, 5 January 2018.
Katz, L. (2017) Bitcoin Is at Risk of No Longer Being the Biggest Digital Currency, Bloomberg, 31 May 2017.
Kharif. O. and Leising, M. (2017), Bitcoin and Blockchain, Bloomberg, 11 December 2017.
Larson, S. (2018) Cryptocurrency boom: Why everyone is talking about Ripple, CNN, 4 January 2018.
Lee, T. B. (2017), Bitcoin’s insane energy consumption, explained, Ars Technica, 6 December 2017.
Robinson, E. and Leising, M. (2015), Blythe Masters Tells Banks the Blockchain Changes Everything, Bloomberg Markets, 1 September 2015.
Tapscott, D. (2018), “Ten cryptocurrency predictions for 2018 from the co-founder of the Blockchain Research Institute”, Quartz, 4 January 2018.
Thompson, D. (2017), “Bitcoin Is a Delusion That Could Conquer the World”, The Atlantic, 30 November 2017.
Worland, J. (2017), How China Could Shape the Future of Energy, TIME, 14 November 2017.
Increased likelihood to see a return to a more influential and independent foreign policy of the European states holders of veto power at UN Security Council (France and UK);
Increased likelihood to see a multipolar world settling in, however with also an
Increased likelihood to see a global perception of a rising Chinese global influence;
Increased likelihood to see the Chinese influence strengthening in France and Europe, and, reciprocally, France and Europe’s influence rising in the Far East;
Increased likelihood to see a global perception of the global U.S. influence and power lowered;
Increased likelihood to see rising tensions between the U.S. and China.
Facts and analysis
From 8 to 10 January, French President Emmanuel Macron has been on a State visit in China at Chinese President Xi Jinping invitation.
There, the two Presidents agreed to deepen and strengthen bilateral ties and cooperation notably in the framework of the Belt and Road initiative, including in a host of domains of interest to both China and France, such as science and technology, artificial intelligence, aviation, nuclear energy and agriculture. Meanwhile, they also each reiterated common interests and goals at global level, such as facing climate change, global terrorism, cyber insecurity or promoting global peace and stability and global economic governance.
China and France can build upon the historical ties existing between the two countries, notably since French President General de Gaulle recognition of the PRC and opening of diplomatic relations in 1964. The French tradition of an independent foreign policy could also be reasserted and be an asset.
The influence of the two countries could, as a result, be strengthened, while the interests of each could be furthered. Among others, for example, if China finds a way to benefit from high-tech transfers from France, yet without endangering this very French sector, China could further stress its image of a benevolent state and show again the validity of the B&R initiative and of its win-win ideal.
Internationally, notably at the U.N. Security Council level, and considering also the British Chancellor of the Exchequer visit to China in mid-December, it seems likely that we are heading towards a more balanced international order, yet one that may also be perceived by the U.S. as threatening.
Impact on Issues and Uncertainties
➚ Return to a French independent foreign policy ➚ France, and Europe influence and power in Asia ➚ France influence and power
➚ Chinese influence and power in Europe ➚ Global Chinese influence and power
➘ U.S. influence and power in Europe ➘ Global U.S. influence and power
BEIJING/LONDON (Reuters) – Britain wants closer cooperation with China over its landmark Belt and Road infrastructure scheme, finance minister Philip Hammond said on Friday at the start of a Beijing trip on which he hopes to seal a billion pounds in deals.
On 1 November 2017, Russian Premier Dmitry Medvedev and Chinese Premier Li Keqiang signed a mammoth deal in space cooperation.
That agreement involves six space-related areas, such as lunar and deep space, joint spacecraft development, space electronics, Earth remote sensing data and space debris monitoring (“China, Russia agree cooperation on lunar and deep space exploration, other sectors”, Global Times, Nov 02, 2017). This deal bestows a new dimension to the already massive cooperation between these two very large powers. Indeed, as we shall explore below, the Russia – China space cooperation is a de facto synergy about a new definition of industrial and strategic power. Space industry evolutions as well as the convergence of Chinese and Russian artificial intelligence strategies and robot development strategies overdetermine the emergence and settling in of this definition.
In effect, the Chinese space program relies heavily on the combination of launching capabilities and of autonomous robots, designed to operate on the Moon (Jean-Michel Valantin “The Chinese New Silk Road, from oil wells … to the Moon and Beyond”, The Red Team Analysis Society, July 6, 2015). Similarly, Russia is working at renewing its space capabilities, as well as the industrial and military basis that supports the development of its launch and space vehicles.
Moreover, both nations want to develop space assets and install themselves on the Moon, … for a start (Yang Sheng, “China eyes unprecedented 40 space launches in 2018”, Global Times, 2018/1/4). Meanwhile, as we shall highlight below, these technological, industrial and strategic convergences are also inscribed in the race for the development of artificial intelligence. Furthermore, this convergence of the Chinese and Russian space strategies also necessitates the coordination of industrial, robotic and artificial intelligence capabilities, as well as of space capabilities. Each of these capabilities already constitutes a strategic leap for the nations that are able to develop them. The convergence of such capabilities is nothing but a geopolitical revolution.
These are the issues we shall explore in this series of articles.
In the first article of the series, we shall look at the way China is coupling both its Moon robot and space programs, while the Moon robot development is inscribed within the Chinese robots and artificial intelligence current revolution. First, we shall see that the Chinese Moon program is robot-centred. Then, we shall stress that the next step of this program is intrinsically linked to the current robotics and artificial intelligence hyper development in China. Finally, we shall focus upon the interactions between the robots, artificial intelligence and space programs and their role in the current transformation of China into a technological cutting-edge world power.
Chinese robots on the Moon
The Chinese space and Moon program is largely robot-centred. On 13 December 2013, the Chang’e 3 rocket brought the Yutu Moon Rover close to the Moon, where the rover soft-landed. This event highlighted the tremendous success of the program (“China Moon Probe VIDEO Shows ‘Chang’e’ Nail Landing On Lunar Surface », The Huffington Post, 12/17/2013). The rover’s landing was the third step of the multiple phases of the space and Moon Chinese program, after the Chang’e 1 mission, which launched the first Chinese Lunar orbiter in 2007, and the Chang’e 2 craft, which orbited around the Moon with scientific sensors, before reaching the Lagrangian point between Earth and Moon (“Chang’e 5 Test Mission”, Spaceflight.com, 3 January 2018).
The Yutu Moon rover was operational for one year. Then, in 2014, it became immobile. It finally stopped functioning in August 2016. The three-years lifespan of the rover was much longer than its creators originally expected (Jean-Michel Valantin, “China and the New Silk Road: From oil wells to the Moon, … and Beyond”, The Red (Team) Analysis Society, July 6, 2015).
Building upon this success, the Chinese space agency is preparing the Chang’e 5 operation, which will involve the launch of a new Moon rover in 2019. (The link between Chang’e 3 and Chang’5, the Chang’e 4, is a spatial probe, designed after Chang’e 3, as a redundant part for Chang’e 5 that should be launched in 2018 (“Chang’e 4“, Wikipedia)).
In this context, the success of the new Moon rover missions is a very important technological, operational and political brick for China.
Chinese robot: from artificial intelligence and industry, to the Moon
In 2013, the key to the success of the Chinese Lunar rover, named the “Jade Rabbit”, was that the robot had been designed in order to be as autonomous as possible once landed on the Moon. This autonomy capability must be greatly upgraded for the much more complex Chang’e 5 mission, which involves sampling rocks and bringing them back by a fully automated robot (“Chang’e 5 Test Mission”, Spaceflight.com, 3 January 2018).
This crucial issue of autonomy for the new Lunar robotic mission is embedded in the Chinese technological and industrial environment, defined by the way robots are taking up tasks of a growing complexity thanks to their integration with artificial intelligence capabilities (Jean-Michel Valantin, “The Chinese artificial intelligence revolution”, The Red (Team) Analysis Society, November 13, 2017). In effect, China, along with U.S. private companies, is at the forefront of the twin development dynamics of robots and artificial intelligence (Ma Si “Smartening the world with robots”, China Daily, 2017-09-25).
This dynamic is generated by multiple sectors, from industrial to domestic robots, while, in the same time, the Chinese government and the giant Chinese tech companies Baidu, Alibaba, Tencent, and Huawei, heavily invest in the artificial intelligence field (Sarah Hsu, “China is investing heavily into Artificial intelligence, and could soon catch up with US”, Forbes, July 3, 2017). These investments are explicitly made in order to turn China into the world leader in artificial intelligence over the next 15 years. The government plans to invest more than 150 billion dollars into this endeavour, to which private funding will need to be added (“New Generation Artificial Intelligence Development Plan” (新一代人工智能发展规划 and “China’s got a huge artificial intelligence plan”, Bloomberg Technology, 21 July 2017).
This Chinese dynamic that allies robotics with artificial intelligence has been officially defined by the government in the “Made in China” report of 2015, which states the official will to turn China into the international leader in the different fields, among others, of electric/smart car, information technology, aerospace equipment, agriculture machinery, which are all related to AI and robotics, actually considered as a sub-field of AI (“Made in China 2015” Plan, The State Council of the People’s Republic of China, May 19, 2015 and Jean-Michel Valantin, “China: Towards the digital ecological revolution?”, The Red (Team) Analysis Society, October 22, 2017; Helene Lavoix, “When Artificial Intelligence will Power Geopolitics – Presenting AI“, The Red (Team) Analysis Society, 27 Nov 2017 ).
This policy supports giant partnerships as well as mergers and acquisitions between Chinese companies and leading foreign companies. For example, the mammoth Chinese robotics company Midea has now acquired the German giant of industrial robotics Kuka (Li Xuena, Wang Cixin, Zhang Boling, “China’s factories are building a robot nation”, ChinaFile, March 10, 2015). In other terms, by developing literally a robot workforce coordinated by multiple levels of artificial intelligence, China installs itself at the vanguard of “intelligent” industrial productivity on a global scale (Jane Perlez, Paul Mozur, Jonathan Ansfield, “China’s technology could upset the global trade order”, The New York Times, Nov. 7, 2017). In 2017 only, China produced more than 120 000 robots (“China produces more than 100 000 industrial robots in first ten months”, Global Times, 2017/12/13).
This exponentially growing expertise and practice in the fields of robotics and of artificial intelligence is the very ecosystem of the development of the Chang’e 5 Lunar rover as an autonomous robot. In other terms, this twin development of robots and of artificial intelligence and the implementation of the Lunar and deep space Chinese program appear as interactive drivers of the development of China and of its transformation into an “intelligent” industrial power, defined by the crossover between the robots and artificial revolution and a space development revolution. The Chang’e 5 Lunar robot is at the intersection of these interactive dynamics.
The Chinese space program
Furthermore, the Chinese space and moon program is also an industrial and political Chinese-led program, integrating, through the Asia-Pacific Space Cooperation Organization (Bangladesh, China, Iran, Mongolia, Pakistan, Peru, Thailand, Turkey) and other cooperation partnerships such as with India, industrial hardware, software and also political cooperation (K.S. Jayamaran, “India and China Sign Space Cooperation Pact », Space News, September 22, 2014).
As these countries are not directly involved in the space race, or even very far from it, with the exception of Iran and India, by supporting the Chinese space program, they become part and members of the opening of the space and Moon segment of the Chinese “Belt and Road” policy of which they are already part, again with the exception of India so far. Its space program also helps China to boost its research and development, while politically and industrially sharing its success with its partners. In the meantime, China gets access to this strategic “ultimate high ground” that orbital space and lunar space are (William Burrows, This New Ocean, 1998)
It is both in this international cooperation system defined by the Russia – China “special relationship” and the Belt and Road initiative and in the space development and cooperation dimension that the new partnership between China and Russia reveals its full geopolitical meaning, which will be the topic for the next article of this series.
About the author: Jean-Michel Valantin(PhD Paris) leads the Environment and Geopolitics Department of The Red (Team) Analysis Society. He is specialised in strategic studies and defence sociology with a focus on environmental geostrategy.
Featured image: Annotated image of the approximate landing site of the Chinese Chang’e-3 lander. It was launched at 17:30 UTC on 1 December 2013, and reached the Moon’s surface on 14 December 2013. The lunar coordinates are: 44.12°N 19.51°W. NASA, Public Domain.
The Red (Team) Analysis Society was featured in a very interesting article, “A New Era without Certainties” (Uma nova era sem certezas), by Portuguese author and journalist Jorge Nascimento Rodrigues, published in the December 2017 edition of the business and economy magazine Exame (group Expresso).
Among other references, a detailed interview of Dr Helene Lavoix, RTAS Director, around the theme of “The End of the Supremacy of the United States” (O Fim Da Supremacia dos Estados Unidos) was included in the article (see related links at the end of the page).
Among many crucial points, Jorge also stressed the importance of a little known yet most probably momentous change that is about to happen: the redrawing of the maritime frontiers of all states to include their claims over their extended continental shelf (save the U.S. as it did not sign the United Nations Convention on the Law of the Sea – UNCLOS 1982), which is expected to take place around May 2019 (read more in our “Deep Sea Resources Brief, updated 5 January 2018, created 1 June 2012). As a result, what we are certain to see happening is a fundamental redesigning of the geopolitical map of the world. Who will know how to take advantage – or not – of this novel situation remains to be seen.
Pictures of some of the pages of Jorge Nascimento Rodrigues ‘s article “A New Era without Certainties”
Human societies currently face dwindling resources and rising competition for them in the contemporary “resources order.” Thus, besides and in accordance with other ways to handle this challenge, new types and sources of resources are increasingly valuable and can make a strategic difference for polities, as well as for humanity as a whole. Meanwhile, if we are to ever learn from our worrying present, we must also, continuously, make sure that the extraction and use of those new potential resources will not have any unfavourable impact on the planet and its ecosystem, including this biodiversity to which we belong.* As has now been known since the end of the nineteenth century (Ifremer, les Nodules, 2012), mineral resources lie on the …
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2018 is likely to be overshadowed by the relationships between the U.S. on the one hand, a rising China and its strategic partnership with Russia on the other.
There is no fatality towards increased tension. It seems to be, however, more likely than a wise and cooperative approach, considering notably the overall transitional setting and the U.S. perspective and behaviour.
Most other issues will be impacted by the way these relationships develop.
Meanwhile, the increasing importance of Artificial Intelligence, its multiple uses and advances, could very well start very deeply transforming the world.
As we expected previously, the U.S. decision regarding Jerusalem not only polarised the situation, but also ended up as a test for U.S. power and influence. The testing nature of the situation was reinforced by the Americans threatening to cut American aid to countries, should the latter not side with the U.S. during the U.N. General Assembly vote for a resolution that “’demanded’ that all countries comply with Security Council resolutions regarding the status of Jerusalem, following an earlier decision by the United States to recognize the Holy City as the capital of Israel” (UN News) – a resolution that thus opposed the U.S. decision regarding Jerusalem.
Despite the threat, the “resolution [was] adopted by a recorded vote of 128 in favour to nine against (Guatemala, Honduras, Israel, Marshall Islands, Federated States of Micronesia, Nauru, Palau, Togo, United States), with 35 abstentions” (UN News). The U.S. thus lost.
As a result, the power and influence of the U.S. seems likely to have decreased.
This was not lost on China, as it held a third symposium, “of Israeli and Palestinian peace advocates” on 21 and 22 December 2017 in Beijing, where China’s Foreign Minister Wang Yi was to “meet with the Palestinian and Israeli attendees” (Foreign Ministry Spokesperson Hua Chunying’s Regular Press Conference on December 21, 2017). The Foreign Ministry’s spokeperson futher added that “We are willing to continue offering constructive assistance to promote the Israeli-Palestinian peace process.” (Ibid.)
Meanwhile, the content of the articles on the matter in Global Times (the international edition for the very official People’s Daily), not only stressed the American loss of influence, but also underlined the ideal Chinese position to now step in as potential broker for future peace negotiations between Israelis and Palestinians.
It thus appears likely that China could step in to try replacing the U.S. as peace broker.
Should this happen, then China would have extended and asserted its influence, furthermore in a region where it had not been so far a major player – however being increasingly active there – while the U.S. would have, on the contrary, lost not only regional but also global influence.
Impact on Issues and Uncertainties
➘ U.S. influence and power in the Middle East ➘ Global U.S. influence and power
➚ Chinese influence and power in the Middle East ➚ Global Chinese influence and power
By an overwhelming majority, Member States in the United Nations General Assembly on Thursday “demanded” that all countries comply with Security Council resolutions regarding the status of Jerusalem.
Diplomats brushed aside what appeared to be a hastily organized pressure campaign by the White House, including last-minute threats by President Trump to cut off aid to countries voting for the resolution. “We will not be threatened,” Mr. Malki, one of several diplomats who spoke before the vote, told the General Assembly at an emergency meeting.
The symposium of Israeli and Palestinian peace advocates held in Beijing shows China’s will to promote peaceful solutions to Palestine-Israel issues, but experts say the complexity of Middle East politics leaves limited space for China.
An emergency UN General Assembly meeting passed a resolution calling for the US to drop its recognition of Jerusalem as Israel’s capital as well as its decision to move the US embassy there. A total of 128 countries backed the resolution, nine voted against and 35 abstained.
The capability to use Alice in English could be developed in the (near-)future (Anadiotis, Ibid.). This would open the whole Yandex world to English speakers. Meanwhile this would also allow Yandex to get access to all the data of these very English speakers, so far the preserve mainly of Google, Apple and Amazon. Considering the current tensions between the U.S. and, with variations, NATO members, on the one hand, Russia on the other, one may only too well imagine the political paranoia that might then develop. Meanwhile, international competition among internet giants for users’ data, crucial to part of Deep Learning, as we shall see when explaining what is Deep Learning below, will very likely be intensified. On a more positive side, better understanding may also emerge as a result of non-Russian people discovering the Russian world. Nonetheless, this would also impact perceptions and thus international relations.
The AI world, notably in its Deep Learning component, is already here. It impacts everything, even though the extent and depth of its impacts are still hardly perceptible. We must understand Deep Learning to be able to live within this new world in the making, rather than only reacting to it.
This article thus focuses on Deep Learning (DL), the sub-field of Artificial Intelligence (AI) that leads the current exponential development of the sector. As we seek to envision how a future AI-powered world will look and what it will mean to its actors, notably in terms of politics and geopolitics, it is indeed fundamental to first understand what is AI.
Previously, we presented AI, looking first at AI as a capability, then as a scientific field. Finally, we introduced the various types of AI capabilities that scientists seek to achieve and the ways in which they approach their research.
In this article, we shall first give examples of how Deep Learning is used in the real world. We distinguish two types of activities: classical AI-powered activities and totally new AI-activities, related to the very emergence of DL. In both cases we shall point out their revolutionary potential, impacting three major emerging functions within polities we had previously started identifying: AI management, AI governance and AI-power status, when AI is most likely to be, to the least, part of the relative power ranking for world actors (Helene Lavoix, “When Artificial Intelligence will Power Geopolitics – Presenting AI“, 29 November 2017, and Jean-Michel Valantin, “The Chinese Artificial Intelligence Revolution“, 13 November 2017, The Red (Team) Analysis Society).
Then, we shall take a deeper dive in the world of Deep Learning, taking as practical example the evolution of Google’s DeepMind AI-DL program initially developed to win against human Go masters: AlphaGo, then AlphaGo Zero and finally AlphaZero. After briefly presenting where DL is located within AI, we shall focus first on Deep Neural Networks and Supervised Learning. Second we shall look at the latest evolution with Deep Reinforcement Learning and start wondering if a new AI-DL paradigm, which could revolutionise the current dogma regarding the importance of Big Data, is not emerging.
Deep Learning in the real world, AI-governance and AI-power status
In a nutshell, Deep Learning (DL) is used to solve at best complex problems and functions and to take the best possible decisions regarding whatever question it is applied or to succeed in whatever field it is used.
For example, DL is increasingly used in the oil and gas industry. Southwest Research Institute (SwRI) developed the Smart LEak Detection (SLED) system, which “uses algorithms to process images from sensors scanning infrastructure” to “autonomously and accurately detect liquid hydrocarbon leaks and spills” (Maria S. Araujo and Daniel S. Davila, “Machine learning improves oil and gas monitoring“, 9 June 2017, Talking IoT in Energy). DNV GL has explored the use of DL (actually Microsoft Azur Machine Learning) to predict corrosion in pipelines and concluded that the “performance achieved” was “extremely promising” (Jo Øvstaas, “Big data and machine learning for prediction of corrosion in pipelines“, 12 Jun 2017, DNV GL). Had Italy and the UK benefited from such systems, both the “explosion at a major processing facility in Austria, which is the main point of entry for Russian gas into Europe”, and the “shutdown of the North Sea’s most important oil and gas pipeline system”, respectively on 11 and 12 December 2017, with major consequences for European supply (Jillian Ambrose and Gordon Rayner, “Gas shortage to push up bills after ‘perfect storm’ of energy problems“, 12 Dec 2017, The Telegraph), would most probably not have happened – assuming, of course, investments related to response had been done.
Further, DL is also increasingly part of the development of what is called “Smart Factory”. “In April 2017, PCITC and Huawei jointly announced a smart manufacturing platform… a core part of Smart Factory 2.0 within the Sinopec Group”. Notably, one of the capability of the platform “creates a ‘smart brain’ for petrochemical plants using deep learning and reasoning data.” (Huawei, “Huawei Joins Hands with PCITC to Embrace Smart Factory 2.0“, 13 Nov 2017, PRNewswire).
With NVDIA’s “Metropolis AI Smart Cities Platform”, Huawei’s video content management product supports and uses Deep Learning for “accurate face recognition, pedestrian-vehicle structuring and reverse image search”, also cooperating with the Shenzhen Police. Always with Metropolis, Alibaba Cloud’s City Brain uses AI for services such as “real-time traffic management and prediction, city services and smarter drainage systems”, improving for example “traffic congestion by as much as 11 percent in Hangzhou’s pilot district” (Saurabh Jain, “Alibaba, Huawei Adopt NVIDIA’s Metropolis AI Smart Cities Platform“, 25 Sept 2017, NVDIA blog).
Most famously, Deep Learning has been and is still used to play games such as go or chess, which allows for developing and testing new AI programs, in their architecture and algorithms. It is these programs, notably those developed by Google’s DeepMind, that we shall use below to further deepen our understanding of what is DL.
These may appear as classical cases of the way AI in its DL component may revolutionise already existing ways and practices.
For the very first time in human history, we could start thinking we could manage activities in near-perfect ways, as well as govern, in the multiple dimensions ruling demands, also in near-perfect ways. This, in itself, in a world of very imperfect humans is a revolution. It leads us to wonder about new issues such as how we, humans, with all our imperfections, with our multiple cognitive biases – i.e. mental errors which we are systematically doing but which were useful to survive and reach our current level of development (Richards J. Jr. Heuer,, Psychology of Intelligence Analysis, Center for the Study of Intelligence, Central Intelligence Agency, 1999) – are we to handle suddenly near-perfect activities? The very simple example of the self-driving car springs to mind immediately. The high number of crashes involving self-driving cars seems indeed to come from their inability to handle human imperfect driving (James Titcomb, “Driverless car involved in crash in first hour of first day“, 9 November 2017, The Telegraph).
However, new activities are also starting to appear, which are less classical to say the least. We have the case of learning platforms, where AI-DL agents learn and train (Cade Metz, “In OpenAI’s Universe, Computers Learn to Use Apps Like Humans Do“, 12 May 2016, Wired). For example, Universe, developed by OpenAI (the AI Lab backed by Tesla CEO Elon Musk) is a software platform where scientists can train their AI to interact with applications and programs, many of them open source (Ibid).
DeepMind Lab is a similar platform offered by Google’s DeepMind (Ibid). The older ImageNet, created in 2009, helped AI agents to learn to “see” (Ibid.). Is this the birth of a truly new AI-activity, similar to education, and which is to be part of the emerging AI-governance?
How will these two types of activities, classical AI-powered activities and new AI-activities, be integrated within AI-management and, in the area of politics that primarily concerns us, AI-governance? How are AI-management and AI-governance be organised? How will AI-governance interact with older remaining state, regime and government structures and processes?
Further, how will be organised a world that has been so far dominated by the quest for relative competitive advantage? Is the notion of competitive advantage even still relevant? What will happen when so far competing actors, from states to companies, are each using AI-DL in such a way that management and governance are all near-perfect? The first phase will most probably be a race to obtain this AI-DL advantage, while trying possibly to deprive others. But what will happen when two or more actors reach the same AI-stage of development? As the example give in introduction points out, shall will also see competition regarding who can access to citizens’ data rise?
This is nothing less than a completely new world that is possibly being created.
We shall, however, also have to wonder if and how such developments could fail.
We shall now take a deeper dive in the world of Deep Learning, which will allow us then, throughout the series, to better understand which activities are susceptible to be impacted by AI-DL, to start envisioning which new AI-activities could be born, as well as to map out how the likely race for AI-power status could take place and around which elements.
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Featured image: Neurons by Geralt, Pixabay, Public Domain – Cropped and re-colorized.
Silver, David Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, Yutian Chen, Timothy Lillicrap, Fan Hui, Laurent Sifre, George van den Driessche, Thore Graepel & Demis Hassabis, “Mastering the game of Go without human knowledge“, Nature550, 354–359, 19 October 2017, doi:10.1038/nature24270
Silver, David Aja Huang, Chris J. Maddison, Arthur Guez, Laurent Sifre, George van den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, Sander Dieleman, Dominik Grewe, John Nham, Nal Kalchbrenner, Ilya Sutskever, Timothy Lillicrap, Madeleine Leach, Koray Kavukcuoglu, Thore Graepel & Demis Hassabis, “Mastering the game of Go with deep neural networks and tree search” Nature 529, 484–489, 28 January 2016, doi:10.1038/nature16961.
Resulting from the Google AI China Center’s opening and then operations, we estimate rising likelihoods to see :
Redrawing of the power map of the world along AI-power status lines
Rising competition regarding AI between U.S. and Chinese mammoth Companies
Human talents as stake in rising AI competition
“Forced” introduction of “open source” AI work in China
AI further progress and developments
Rising U.S. ability to stem the declining tide in terms of AI
Rising China’s influence in terms of AI
Rising China’s strength and capability to further develop AI
Strengthening capability of Chinese government and State to “keep in check” mammoth IT companies
Strengthening of Chinese political authorities
Increased China’s influence
China’s rise to top major power status
US decline from sole superpower to major power status (in relative terms, the U.S. capability to stem decline out of this specific signal does not compensate for the corresponding Chinese gains)
Escalating Tension U.S. – China
(The corresponding symbolic board is located after the “facts and analysis section)
Facts and analysis
On 13 December 2017 during the 13 and 14 December Google Developer Days event in Shanghai, Fei-Fei Li Chief Scientist AI/ML *Artificial Intelligence/Machine Learning), Google Cloud announced the creation of the Google AI China Center, their “first such center in Asia”. the center will focus on basic AI research, and is located in Beijing to attract as many talents as possible.
It follows logically from Eric Schmidt, Executive Chairman, Alphabet Inc. (Google) and Chair, Defense Innovation Board’s perception and assessment we singled out in a previous signal, according to which
“These Chinese people are good… It’s pretty simple. By 2020, they will have caught up; by 2025, they will be better than us; and by 2030, they will dominate the industries of AI.” (Eric Schmidt, Artificial Intelligence and Global Security Summit, CNAS, 1 Nov 2017)
As a result Google is positioning itself to be present on a market that they see as being dominant in the future. In the meantime, by attracting these Chinese AI talents, they also potentially slow the AI development of their Chinese competitors, which are Alibaba, Huawei, TenCent or Baidu.
As underlined by the Chinese official viewpoint, such a competition may only be healthy and stimulating and promote innovation at Chinese level, notably in a field that is so close to the heart of China, which aims at becoming leader in AI. The Google AI Center shows the attractiveness of China, and will help China attracting notably Asian talents to China, de facto favouring China’s goals.
Finally, Google is certainly an interesting actor for the Chinese government as it is allowed on the Chinese-Global AI board, in as much as it can be also possibly used to check the mammoth power garnered by the IT Chinese giants. For example, according to a Huawei Director there is a Chinese lag in “developing open-source software”. Assuming that this position is shared by the Chinese political authorities, allowing Google to enter the AI competition in China is likely to be a perfect way to force Chinese companies towards more open-source efforts (yet of course without overestimating Google open efforts, as we are dealing here with for profit companies).
The Chinese government and state thus ensures it strengthens its hand in remaining master of China’s destiny.
Impact on Issues and Uncertainties
? How threatening would a leadership of China in terms of artificial intelligence (AI) be perceived? What would mean escalating tensions between China and the U.S. involving AI and how would they play out? Are mammoth U.S. companies first global or American? (Critical uncertainties)
➚➚ Redrawing of the power map of the world along AI-power status lines
➚ Rising competition regarding AI between U.S. and Chinese mammoth companies ➚ Human talents as stake in rising AI competition
➚ “Forced” introduction of “open source” AI work in China ➚ AI further progress and developments
➚ U.S. ability to stem the declining tide in terms of AI ➚ China’s influence in terms of AI ➚ China’s strength and capability to further develop AI
➚ Capability of Chinese government and State to “keep in check” mammoth IT companies ➚ Strengthening of Chinese political authorities
➚ China influence ➚ China rise to top major power status ➙➚ US decline from sole superpower to major power status
Since becoming a professor 12 years ago and joining Google a year ago, I’ve had the good fortune to work with many talented Chinese engineers, researchers and technologists. China is home to many of the world’s top experts in artificial intelligence (AI) and machine learning.
Google announced Wednesday that it is opening an artificial intelligence (AI) research center in Beijing. This may serve as a springboard for China to attract top-ranking talent from around the world.
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Bitcoin, however, is just the tip of the iceberg. Underneath there is a whole universe of cryptocurrencies (nearly 1400) which value and market capitalization has skyrocketed in the last months of 2017. At the time of writing, on 8 January 2018, 40 cryptocurrencies have a market capitalization of 1 billion US dollars or more. 
Global Times, Nov 02, 2017). This deal bestows a new dimension to the already massive cooperation between these two very large powers. Indeed, as we shall explore below, the Russia – China space cooperation is a de facto synergy about a new definition of industrial and strategic power. Space industry evolutions as well as the convergence of Chinese and Russian artificial intelligence strategies and robot development strategies overdetermine the emergence and settling in of this definition.
