With rapid advancements in digital engineering and data architecture, we require powerful computational models. Traditional computational models, comprising of binary numbers 1s and 0s, do not have the computational power to sort exorbitant amounts of data as the world has moved toward complex digital technologies.
Imagine if you must distribute test sheets among students. You may be able to distribute 100 sheets per minute. As the number of students grows, the time to distribute the sheets would shrink. That is a classic computational model, taxing to keep pace with the changing demands of technological advancements. Now, imagine if an octopus does the same task with eight hands. An octopus would be able to distribute 800 sheets per minute. Quantum Computing (QC) would solve complex computational problems like that.
According to IBM, QC takes an innovative approach to sort complex computational problems by creating multidimensional spaces that link data patterns with individual data points.
Quantum mechanics is not a new field; it emerged as a branch of physics to explain the scale of atoms in the early 1900s. However, it gained attention in 1994 when Peter Shor developed quantum algorithms. Shor’s algorithms could find the prime factors of large numbers ‘efficiently’. Here ‘efficiently’ meant the capability beyond the state-of-the-art classic algorithms. Shor’s algorithm became the basis of present-day QC that has optimised cloud computing, blockchain, cryptography and cybersecurity, among many other domains.
Quantum Technology (QT) is a disruptive technology with numerous military applications as well. It is not a stand-alone military system like jets and missiles. Instead, it is embedded in other technologies that depend on computation to improve their effectiveness, accuracy, and precision. The first quantum revolution brought military technologies such as nuclear weapons, lasers, digital cameras, magnetic resonance imaging, and other imaging devices. The second QT revolution is characterised by the increased computational power of weapons tracking and targeting systems, making them more efficient.
Military radars with QT would be able to detect stealth aircraft by reflecting even the faintest photons. QT would enable highly efficient Global Positioning Systems (GPS), especially in terrains where satellite reception is poor such as underwater or mountainous regions. As militaries rely heavily on GPS to conduct precision strikes, QT will significantly improve precision due to its ability to pinpoint coordinates. It would also optimise maintenance, logistics and supply chains and avoid inventory wastage.
This technology would also radically upgrade Artificial Intelligence (AI), Machine Learning (ML) and Neural Networking tasks given its faster processing speed of complex datasets. Quantum-enhanced AI would be able to develop generative models that would not only be dependent on available datasets but would be able to generate predictive samples. This would further improve the performance of AI systems on the future battleground. It would improve man and machine teaming due to its quantum-enhanced intelligence to interact with humans, and at times, even take superiority over humans. According to research by the University of Vienna, robots learn faster with QT. This learning would also improve Lethal Autonomous Weapon Systems (LAWS), as with quantum-enhanced AI, LAWS could precisely select and engage targets without human supervision. In the cyber domain, QT can crack encrypted software in 10 seconds. This can cause national disruption by threatening sensitive information and communication systems. The increased efficiency due to QC has pushed states to explore the field further.
QT is expensive, and presently, the United States (US), United Kingdom (UK), China, Russia, Japan, Australia, India, Canada, France, Germany and Israel can develop fast-processing quantum algorithms. This has also initiated a QC arms race which could lead to quantum warfare. The race is between the US and China. China has invested USD 10 billion, whereas the US has invested USD 1.2 billion in QC. However, the US military has been researching QT since the 1950s and has an independent board within the Department of Defense.
An emerging player in QT is India, which has invested about 1 billion USD in QC. It has several institutes that work independently and cooperate to advance this national goal. In 2021, India’s Defense Institute of Advanced Technology (DIAT) and the Centre for Development of Advanced Computing (C-DAC) collaborated on QC tech. India’s Department of Science and Technology and 13 research institutes from the Indian Institute of Science and Research (ISSER) have launched I-Hub Quantum Technology Foundation to assist budding start-ups in QC. The Indian Army has set up a quantum lab to help its military leapfrog into next-generation communication technology. The country has also partnered with Israel and Japan to pursue joint ventures in QC. As part of the QUAD arrangement, India will have special access to cutting-edge technology, including QT. India has further welcomed IBM to create a national quantum plan roadmap. IBM has also engaged Indian students to work in the field. Similarly, in collaboration with Amazon Web Services (AWS), India opened a research lab to facilitate R&D in QC. QT is expected to add 310 billion USD to the Indian economy by 2030. Although India is at an initial stage of development, these initiatives have boosted a QC ecosystem in the country.
On the other hand, Pakistan has only started exploring the QC field. There are isolated measures to set up research labs by top universities in Pakistan, such as Lahore University of Management Sciences (LUMS) and National University of Sciences & Technology (NUST). However, attention by the government to set up Research and Development facilities for QC is needed. There is a need to raise awareness and funds to benefit from the potential of this technology. Pakistan has an ample number of talented human resource who, if trained, could lead the country in this direction. QT needs attention as it has the power to identify and counter quantum-level threats.
Quantum computers will not replace traditional computers as they are too powerful and complex to perform simple tasks such as emails. Instead, it would be reserved for technology and corporate giants, governments, and military programmes such as space programmes and nuclear Command and Control (C2) as they require faster processing speed. The future of quantum is open-ended as research is still being conducted to build more powerful quantum architectures. It has attracted visionary minds, who believe that QT will meaningfully impact the future of technology.
New archaeology dives into the mysterious demise of the Neanderthals
BY SARAH WILD
For more than 350 000 years, Neanderthals inhabited Europe and Asia until, in a sudden change by evolutionary standards, they disappeared around 40 000 years ago. This was at around the same time the anatomically modern human Homo sapiens emerged from Africa.
With their distinctive sloped forehead, large pelvis and wide noses, Neanderthals leave in their wake one of the great mysteries of human evolution.
They lived during the middle to late Pleistocene Epoch, about 400 000 to 40 000 years ago. Neanderthals lived in Eurasia with traces discovered as far north as present-day Belgium and south to the Mediterranean and southwest Asia.
They were not the only hominid (human-like) species in existence on the planet at the time. Other archaic human groups such as Homo floresiensis and Denisovans, also walked the earth.
‘At the time of the Neanderthals, there were several human species and suddenly 40 000 years ago, all disappeared but one,’ said Prof Stefano Benazzi of the University of Bologna, Italy.
He is a physical anthropologist leading the Horizon-funded SUCCESS project to research the earliest migration of Homo sapiens in Italy. ‘It’s important to understand what happened,’ he said.
We already know more about Neanderthals than any other extinct humans, thanks to thousands of excavated artefacts and fossils, as well as several nearly-complete skeletons.
There are a number of competing theories as to why the Neanderthals disappeared, such as climate change, the aggression of Homo sapiens, possible competition for resources, or even that Neanderthals disappeared because they interbred with Homo sapiens. Some human populations alive in Europe and Asia today have as much as 3% Neanderthal DNA.
Benazzi investigated what happened to Neanderthals in Italy around the time that Homo sapiens arrived out of Africa.
‘In Italy, we have a lot of (dated) archaeological sites, and we have a good overview of the different (technological) cultures falling in the time period of interest,’ he said.
A number of scholars argue that climate change may have pushed Neanderthals towards extinction. While that may have been true in other places, it was not the case in Italy, Benazzi explained.
The SUCCESS project analysed the pollen from paleolake (ancient lake) cores using minerals collected from ancient stalactites. These calcium icicles which hang inside caves are effectively climate time machines, and researchers can decode what the climate was like when they formed.
Through this approach, the SUCCESS project reconstructed the paleoclimate (prehistoric climate) between 40-60 000 years ago. In contrast to ice-core analysis from Greenland, there were no data indicating catastrophic climate change in Italy, making it unlikely to have killed off the Neanderthals.
They closely examined a period of around 3 000 years when populations of Neanderthals and humans may have co-existed by excavating seven sites they once inhabited. They investigated the cultural and tool-making differences between the last Neanderthals and the first Homo sapiens in Italy.
Homo sapiens in Italy used specific types of technology including artefacts such as shell ornaments and projectiles like arrowheads. In fact, SUCCESS unearthed the earliest evidence for mechanically delivered projectile weapons in Europe.
Neanderthals would have found themselves at a severe disadvantage to their Homo sapiens relatives in terms of weapons technology. However, that meeting in Italy may never have happened.
Recently discovered remains in southern Europe show that at least one Neanderthal had been alive 44 000 years ago while the oldest Homo sapiens remains have been dated to 43 000 years ago. It is possible that they overlapped, but none of the current evidence shows that, Benazzi said.
Each region is different. ‘The result we get here (in Italy) doesn’t mean that we’re going to get the same results elsewhere,’ he said.
In the PALEOCHAR project, Carolina Mallol, a geoarchaeologist at the University of La Laguna in Spain and currently a visiting professor at UC Davis in the United States, is raking through the ashes of time, seeking traces of Neanderthals’ lives and hints of their demise.
The goal is to study microscopic and molecular charred matter from ancient fire sediments to see what organic material they left behind.
‘The handicap of the archaeologist is that the human world is organic, and we can’t get at it,’ said Mallol, who studies Neanderthal sites such as El Salt and Abric del Pastor in Spain.
When organic matter, such as meat or plants, is thrown in a fire, the heat dehydrates it, ultimately destroying its DNA and proteins. But fatty molecules called lipids can survive if the fire does not get hotter than about 350°C, as Mallol and colleagues show in their investigations.
‘PALEOCHAR was designed to explore how far we can take the analytical techniques to squeeze molecular information from the organic black layers (in the fire),’ she said.
Paleolipidomics (the study of ancient fats) has been used to study lipids in Roman amphorae, Egyptian mummies and even prehistoric leaves.
When it comes to ancient human sediments, ‘we are the first ones to apply (these techniques) systematically,’ she said. They also expanding the known lipid biomarkers, which are like molecular “barcodes” specific to species, families or even metabolic pathways.
‘With biomarkers, you can distinguish herbivores from carnivores, conifers from angiosperms,’ she said.
Mallol and colleagues set up the world’s first AMBILAB, which stands for the Archaeological Micromorphology and Biomarkers Research Lab, based in Tenerife, Spain, which trains researchers in the techniques of soil micromorphology and lipid biomarker analysis.
The questions about Neanderthals, such as why they went extinct, are very ambitious, said Mallol. ‘Those questions require that you first determine who they were and how they lived with a lot of information –– and we don’t have that information yet,’ she said.
With each new piece of information, archaeologists and scientists burrow deeper into the mystery of why our closest relatives suddenly disappeared while Homo sapiens managed to survive.
Research in this article was funded via the EU’s European Research Council and this article was originally published in Horizon, the EU Research and Innovation Magazine.
Distributed Ledger Technologies (DLTs)- as a counter to the growing threat of Centralisation
The Cyber era which found its genesis with the advent of the global internet- through the US Department of Defense funding ARPANET experimentations in the late 1960s – embodies the liberal spirit of laissez-faire and the freedom of expression and has grown rapidly from about 3 billion internet users in 2018, to over 5,385,798,406 internet users, – or 67.9% of our total population – as of June 30, 2022. Attempts, however, have been made to curtail users ability to access what is on the internet through the development of national intranets- examples being China’s great firewall, Russia’s sovereign internet, Iran’s National Information Network, and North Korea’s Kwangmyong network. What these national intranets have in common is centralised management in terms of websites and social media that are accessible, and information that is available to the citizens. Each of these states has the ability to distort truth, to rewrite the narrative, and to determine what is fact and force-feed it to their citizens by filtering opposing content and through restricting/blocking access to alternatives. ‘Centralisation’ here refers to concentrated power in the hands of one group, that allows for unilateral decisions to be made on behalf of the entire population or network.
The threat of centralisation also persists within the private sphere/realm, with tech companies having found themselves at the centre of a new debate in the press media. While tech companies focusing on social media may have first formulated/established themselves as outlets for expression of their user base they have now been taking strides in the opposite direction by censoring user posts and content. Recent instance include Pinterest which in 2019 began blocking any and all search results concerning vaccinations. Similarly, Facebook in 2020 began deleting ‘events’ that aimed at organising protests against home quarantine during the start of the COVID pandemic. Twitter in 2021 extricated over 70,000 accounts that were linked with the ‘QAnon’ conspiracy that threatened public order. This was part of Twitter’s policy of removing posts and deleting accounts that broke their platform’s rules. While in each of these instances the concerned tech company may have arguably acted with good intention, their ability to simply flick a switch and unanimously censor content is deeply troubling. The control that social media companies exerted even over influential people culminated with the permanent suspension of U.S ex-President Donald Trump’s Twitter handle. This incident is exemplary when it comes to determining the power of web censorship that is imbued within the hands of social media companies.
How can DLTs help counteract centrality?
‘Distributed Ledger Technologies’ (DLTs) can be used to counter the growing threat of centralisation from both state actors and monolithic tech-companies. There are various kinds of DLTs- such as Directed Acyclic Graphs (DAG), Holochain, Block Lattice, and the most renowned of all being- Blockchains. Quintessentially, DLTs are distributed peer-to-peer networks that utilise a majority consensus for transactions to be verified and then stored as data on a public ledger. For simplicity sake this article will utilise blockchains to illustrate how DLT networks function.
‘Nodes’ are individual peers within a Blockchain network that maintain a record of the ledger thereby being involved in the process of storing, verifying, and distributing the full set of data with other participant nodes on the blockchain. This “ledger of records” is immutable- allowing for data, events, and transactions to be time-stamped on chain, thus creating a verifiable log of all network user’s micro-history. The key features of a DLT are that they are ‘immutable’, ‘trustless’, and ‘verifiable’ with transactions being easily accessible/viewable by anyone in the entire network and it is these qualities that become instrumental when countering centralisation.
Take for instance the ostracisation of some Iranian national banks in 2012 and Russian national banks in 2022 from the ‘Society for Worldwide Interbank Financial Telecommunications’ (SWIFT)- an international banking system which executes international financial transactions. These instances demonstrate the current weaknesses/drawbacks of our existing financial system- as failure to comply with international norms has resulted in the enforcement of ‘one-sided’ economic sanctions. This cuts off these Banks’ and thereby the nation’s access to the global market as most exchanges occur using SWIFT via the U.S. Dollar and has the secondary effect of debilitating the economic strength of the local currency. Cryptocurrencies, however, are not restricted by these same limitations and were thereby used as a hedge by citizens both in Ukraine and in Russia to save the value of their savings by transferring them from fiat currencies into digital cryptocurrencies. DLTs moreover are resistant to external influence as the transactions (here referring to both financial transactions and any information that is ingrained on-chain) occurring on them are ‘immutable’, which means that once the network/chain is set up- the data time-stamped onto the ledger can no longer be tampered with by third-parties and will continue to exist on-chain permanently. Similarly, attempts made to restrict transactions to -and- between users from a particular region will prove ineffectual as no single entity has control over the entire network.
A second advantage/strength of DLTs is that the ‘consensus mechanism’- the process through which nodes coordinate to add transactions to the network- is designed in such a way so as to allow for the entire process to be ‘trustless’. The immutability of the DLT grants participants on the network the ability to engage in transactions with one-another without having to trust one-another or rely on a third intermediary such as banks or centralised tech platforms to execute the transaction. Moreover, these financial transfer are instant- a real life example being witnessed during the 2022 Russian invasion of Ukraine where individual netizens across the world were able to make direct donations totalling $42 million in 6 days to the Ukrainian Government after they posted their verified wallet address/public key- circumventing the restrictions imposed through bureaucracy. Furthermore it can be argued that the public nature of the digital ledger of transactions grants greater transparency to the public on how exactly the donated money was and can be spent. This is due to the fact all transactions made on-chain (the sending of cryptocurrency to the donated address and the spending of this donated amount on other things) become visible through inputting the public key address on tools such as BSCscan or Etherscan which display all existing transactions. The astounding feature of this whole process is that this can be executed while granting anonymity to the donators- as the only way to identify which address belongs to whom is if the donator somehow revealed that the corresponding wallet belonged to them.
To summarise DLTs have a low barrier to entry as anyone with an internet connection and who is willing to invest time and energy into understanding how the crypto space/system works is able to utilise it. DLTs are designed to be resistant to censorship as every node is independent and the network therefore decentralised. Therefore, a good way to test the strength of a DLT is to measure/assess how easy it would be for a government, corporation, or any external third party (venture capitalist firms, hackers, hacktivists) to shut down or interfere with the network. To shut down or effectively change a decentralized network would require ownership or control of over half the nodes or systems. Even individual countries are incapable of exacting their influence on these independent networks. Algeria, Nepal, Northern Macedonia, and China have all passed laws that decreed the trading and purchase of cryptocurrencies and the utilisation of their underlying blockchains as illegal further blocking user access to websites where cryptocurrencies could be purchased or exchanged making user access difficult but not impossible. Technologies such as Virtual Private Networks (VPNs) grant users the ability to circumvent censorship and allow citizens of even the most authoritarian regimes accessibility. The immutable, anonymous, and decentralized (cross-border/international) nature of DLTs therefore make it very hard for countries to police and regulate crypto transactions. In fact, this was a point argued by Indian Finance Minister Nirmala Sitharaman who called for mutual cooperation and a common solution between countries to tackle the global dilemma posed by cryptocurrencies during a high-level panel discussion organised by the International Monetary Fund (IMF) in April, 2022.
This makes it evident that for the first time in the history of humanity a series of systems are implemented that are capable of resisting State influence which has historically enjoyed its power unperturbed. What has made all of this possible is the invention of ‘smart contracts’, which is immutable computer code, existing on-chain, that allows for the terms and conditions of an agreement between two parties to be carried out without the intervention of a third-trusted party. The contractual clause- such as the release of funds in the form of cryptocurrencies (Bitcoin, Ethereum, Monero etc.) is executed automatically when the necessary preconditions (the fulfilment of services) have been successfully met. Smart contracts allow for the development of decentralised applications and offer increased versatility.
How to discern a centralised DLT from a truly decentralised DLT
DLT networks attempt to adhere to the tenets of decentralisation, at least ideologically, however, the harsh reality is that many of them simply masquerade themselves as being decentralised while falling short of the benchmark. ‘Solana’ is a fine example of an open-source blockchain that despite utilising smart contracts, and supporting decentralised applications (‘dapps’) is still quite centralised. For consensus and for adding transactions to its blockchain Solana utilises a hybrid proof-of-stake model combined with what it has termed as ‘proof-of-history’- where ‘leader’ nodes are chosen randomly for validation for fixed periods of time- thereby lowering latency and increasing throughput. While Solana currently has 1975 validator nodes running giving the illusion of decentralisation- just 32 nodes hold a third of the total staked supply of SOL (a.k.a cumulative stake) and thereby validate a third of all transactions! This is dangerous as this implies that 32 of the largest nodes could potentially collude to halt the network. Secondly, once a DLT is up and running outages should virtually be impossible provided the DLT is decentralised enough as no one can collude to temporarily shut off the network. Solana witnessed six outages during the month of January 2022 for periods lasting longer than 8 hours, during which time they halted the entire chain to identify and fix the issues before restarting the chain- something indicative of the centralised nature of this network. Finally, according to a 2021 report by Messari over 48% of Solana’s token allocation at its genesis were allotted to venture capital firms with only a very small fraction going to the public through lock drops or pre-launch sales. Any DLT having almost half of its initial token allocation allotted to VC firms cannot be said to adhere to the ideologies of decentralisation as only a sliver of the entire allocation was even purchasable/attainable by the public. It is for these reasons that Solana can be categorised as a fairly centralised blockchain.
Bitcoin- the original progenitor of all blockchains- currently having over 15000 reachable nodes active all throughout the world- serves as a prime example of a DLT that truly mirrors the ethos of decentralisation. Bitcoin fulfils the core tenets of decentralization with its blockchain being immutable, trestles through by utilising ‘proof-of-work’ (PoW) for consensus, and transparent with all the transactions on its blockchain being verifiable through services such as BScscan. Moreover, the initial coins were distributed through the mining of blocks- which could be carried out by anyone with a Graphic Processing Unit (GPU) available within Personal Computers- further implying/meaning that bitcoins were openly accessible/earn-able by the public. Furthermore, and in direct contrast to Solana, Bitcoin is leaderless and since its inception in 2008 has never experienced any outages. To enact any change or upgrade to the Bitcoin network requires over 51% of the nodes on the network to acquiesce. Some criticisms have arisen that make reference to the top 6 (centrally managed) mining pools that when combined amount to over 75% of the total computing power in Bitcoin- a fact which would allow them to validate or cancel transactions, conduct double-spending and create coins from thin air. However, the cold-undisputed truth remains that Bitcoin has never, since its inception, witnessed any such collusion that has resulted in a 51% attack- therefore, for all intents and purposes, Bitcoin stands as the apotheosis of decentralisation.
The conveniences afforded through the proliferation of the internet have simultaneously given rise to increasing avenues of centralised control to both national governments and monolithic state companies. In fact, Twitter Founder Jack Dorsey himself has grown despondent at this centralised nature of the internet and recently announced plans to create a new decentralised platform to combat it- terming this as the new Web5. However, this article has also made clear how DLTs and their underlying crypto assets provide a unique solution to countering the growing threat of centralisation. Truly decentralised networks cannot be stopped by the government through some obscure law because the only law in crypto is ‘immutable computer code.’ Neither can cryptocurrencies on these networks be confiscated as they are private assets truly owned by the individual key holder. Governments are aware that DLTs and cryptocurrencies are a frontier they do not exercise sovereignty over and are actively adopting stances to oppose them. Therefore, it can be said that the true test of a DLTs decentralised nature will be to observe how each of them respond to increasing censorship from state and tech influence. It is the author’s opinion and belief that DLTs will remain relevant and continue to grow undeterred because digital assets and their underlying technology are firmly located at the heart of the next technological revolution that is reshaping the world across societies and economies.
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The Development of Artificial Intelligence in the People’s Republic of China
In this article, we will examine one by one the points that do not yet enable studies and developments on artificial intelligence in the People’s Republic of China to rise to 100% of the international advanced level.
I) Economic benefits come first: lack of vision
Many AI companies and some local governments lack vision and pursue short-term economic benefits, hoping to achieve clear economic returns within one-two or two-three years. This results in a large number of AI start-ups eager for quick success, albeit with lack of confidence and weak development.
Economic benefits must be pursued, but high-tech sectors or the sectors that use AI technology to promote the transformation and upgrading of other sectors and their development, should follow specific laws, as well as require a constitutive process and a certain level of success, and not a premature search for immediate profits.
II) The general level of artificial intelligence must be improved as a matter of urgency
Despite the late start of national AI and the lack of participation in the development of corresponding international AI technologies, patents and standards, in China many scientific research institutes and enterprises are participating in research and technology development and, in some areas, are basically at the same level or even leading compared to foreign countries. However, the overall capacity and level of AI in China are far from the international level and there is still a significant gap between the general level of basic AI research and the advanced level. There is still a long way to go in order to reach this level as a whole and it will take time.
III) The national decision-making process still needs to be put in place
Although China has announced a number of development plans related to artificial intelligence, such as the Intelligent Manufacturing 2025, the Robot Industry Development Plan (2016-2020) and the Three-Year Plan for implementing the Action for Artificial Intelligence on the Internet, etc., no national strategy for the global development of AI has been developed yet. The above-mentioned programme plans must also turn policy plans into targeted actions and into visible benefits.
IV) State financial support must be further improved.
As mentioned in previous articles, China has supported AI research and related science and technology projects in many national scientific research and technology development plans, and support is increasing. However, compared to AI on the Internet, as well as intelligent manufacturing and other projects, in response to the investment of some developed countries in Europe and the United States of America, China’s financial support for AI scientific research and industrial development is far from sufficient.
Moreover, compared to other projects, AI needs to analyse more problems, and involve a wider range of players – hence everything becomes harder and requires greater national support.
V) The allocation of funds for scientific research is not sufficiently fair and equitable
From time to time the allocation of funds for scientific research has long been controversial. Firstly, the limited funds have not been used for the most important and urgent projects, but have been evenly distributed – thus resulting “too equal” – between some projects that did not urgently need funds and those that, on the contrary, needed key support. Secondly, some members of the “expert group” allocating funds to projects use their power for personal gain, and sometimes even collude with each other to induce certain funding. For a while, this had become an unwritten rule. Thirdly, the evaluation and use of funds for scientific research lack effective supervision, and these problems also exist in the field of AI.
VI) Citizens are concerned about the AI development
Since AI has been conceived as a component of the civil society, its social impact has attracted widespread attention among people. Some people are concerned about the emergence and development of AI (software) and intelligent robots (hardware supported by said software), fearing that AI and intelligent machines will one day threaten the survival and development of human beings. The greatest scientist who referred to this danger was Stephen Hawking (1942-2018). As one of the world’s most influential physicists, he was concerned that the use of AI technology to create machines that could think independently would eventually threaten the survival of humanity. Hawking stated: “The full development of artificial intelligence may lead to the extinction of human beings”. The echo of his views has been grasped by many citizens, scientists and technicians. There is obviously another viewpoint of society: it is believed that although AI has made great progress after sixty years of development, the general level of AI in the near future will never be such as to surpass human intelligence. We add, however, that since progress is constant on a geometric scale, there will always be a point of no return. The question is the following: will we be able to control, but mainly to define this point of no return and block it at “-x from”?
Nevertheless, some people – in our opinion, in a reckless and senseless manner – argue that we must instead attach great importance to the impact of AI itself on human society, and not waste time on researching and formulating countermeasures – the “-x from” – to quell public concerns and ensure human security.
VII) A race can lead to wild competition
Some historians and scientists believe that there is a sort of traditional culture in Chinese society, i.e. a phenomenon that flourishes everywhere and expresses in the same way in many parts of the country. They add that these expressions are elaborate, refined and sophisticated, but they cannot guarantee the quality of the product, thus causing a huge waste of resources and manpower, and ultimately bring neither economic nor social benefits. This was the case in the past for large-scale steel production – the failure of the Great Leap Forward of 1958-1961 – as well as for large-scale jet aircraft technology and thyristor devices (the Silicon Controlled Rectifier, which is a component that, from an electrical viewpoint, is almost equivalent to the diode, with the only difference that direct conduction occurs only after applying an appropriate trigger signal on a third terminal called gate), and in the current automotive production, industrial robot parks and drone development. At present, there is not only overcapacity in the automotive sector, but most of the companies in the robotics industrial park are facing a difficult situation of wild competition and risk being wiped out in the near future.
China’s AI and its industry have currently attracted unprecedented attention from the government and all walks of society. Fortunately, the phenomenon of the AI industry popping up and flourishing everywhere without any criteria has not occurred. The threshold for the technological starting point of the AI industry is relatively high and the difficulty and risk of starting and developing a business are equally high. There may be fewer entrepreneurs with courage and strength than robot entrepreneurs, and hopefully the robot industry park will repeat the proliferation phenomenon.
VIII) Blind optimism and arrogance are detrimental to development
Many perceptive people believe that there is a big gap between the current national AI basic research, application development and international advanced level. Some national AI researchers and developers, however, overestimate their achievements, believing that national AI has surpassed the international advanced level in many respects.
In view of assessing whether a discipline has reached or surpassed the international advanced level, not only must unbiased and equal international standards be generally recognised, but also a set of convincing results. We will not specifically discuss the issue in this article, but we would like to describe the level of AI development in China from the status of the Turing Award, the highest scientific and technological award in the international computing and IT sector.
Since 1966 the US Association for Computing Machinery (ACM) has organised 55 editions of the Turing Award, with a total of 75 winners, considering that in some editions there were more than one winner.
Winners include the Chinese-American computer scientist from Shanghai, Yao Qizhi, who won the award in 2000, with the Theory of Computation, including pseudo-random number generation, cryptography and communication complexity.
China won the international supercomputer speed championship several times. This is a result which is worth celebrating, but all this is not enough to prove that China’s AI technology has reached the international advanced level. Although the AI development of many national corporate giants has made quick progress and their achievements are rewarding, China has not yet reached the level of international leadership.
Large international companies and developed countries in Europe, America and Japan have invested heavily in their efforts to reach a dominant position in such global competition. The secret lies in not being blindly optimistic and never overestimate one’s own achievements.
IX) There is a tendency to replace research on artificial intelligence with philosophical research
Artificial intelligence, though not belonging to the humanities branch, has philosophical questions to put on the table. Some scholars carry out research ranging from AI to philosophy of information or other philosophical perspectives, which are necessary and worthy of support. For a long time, however, there has been a tendency in China to replace AI research with philosophical research, as well as to exaggerate the role of philosophical issues over AI technical aspects, and even try to dominate AI disciplines with philosophy.
There is a need, instead, for down-to-earth research on the main AI issues. Prof. Wu Wenjun (1919-2017), a mathematician and academic known for his contributions in the areas of differential geometry, topology and computational geometry, once seriously warned: “Our real intention is never to argue with words, and to talk with letters. What we should do is work hard and do it skilfully. Taking advantage of the great opportunity opened up by the advent of the computer era, we should take the lead in promoting the mechanisation of mental work in the world and show our ideas to the planet with concrete results”.
10) International cooperation should be further strengthened
China has promoted considerable international cooperation in the AI field, including the organisation of international conferences, travels abroad to attend international conferences, and the sending of staff to take part in international AI research on a cooperative basis. These activities not only need to be expanded, but also the level of cooperation results needs to be improved. It must be said that international cooperation on AI must be further strengthened so that the “international” status of Chinese scholars will be further enhanced. (8. continued).
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