Artificial intelligence in China is facing unprecedented development opportunities and has many advantages in terms of development. Let us make a few considerations in this regard.
1) International trends
Significant progress has been made in the IT environment and the technological level of human society between big data, cloud computing and the Internet, which are closely related to AI and have developed quickly. AI has started to have a significant impact on the structure of human society and the dual human-machine environment is gradually developing into the third human-machine-intelligent machine environment. The cooperation and coexistence of humans, machines and intelligent machines will become the new normal of the social structure. Such harmonious coexistence is hopefully not only a need for social development, but also provides a distinct place for AI.
Throughout the international community, the development trend of science and technology, as well as AI, is an important sign for human society to keep moving forward after entering the IT field at every level, and is the general trend of international scientific and technological development. Recovery and development inject positive energy into China, and this is also a period of unique development opportunities for China’s AI.
2) AI must be guided by the national strategy
Looking back to the process of AI development in China, we can see that the public’s understanding of AI, the development of its industry, and the government’s emphasis on it have all undergone major changes.
As mentioned above, the State’s top leadership encourages the development of artificial intelligence. President Xi Jinping, Prime Minister Li Keqiang and others have provided great support and clear instructions to the development of AI and robotics in China and have defined target requirements. The State Council, the government and the relevant departments have formulated and released relevant strategic and development plans, such as the three-year Internet+ Implementation Plan, Intelligent Manufacturing 2025 and, in the past, the Robotics Industry Development Plan 2016-2020, etc. The national strategy and government promotion are the source of the healthy development of China’s AI technology and industry. Without the country’s overall political coordination, AI will be impossible to achieve since it is only with the Chinese strategic support that it will be able to make great strides.
3) Internal development needs
AI development is a need for the transformation and upgrading of national industries. The development of intelligent industry and economy requires the continuous innovation of AI. The AI industrialisation is the general trend of national development.
China’s economic and social growth is facing new opportunities and challenges. The lack of dividends in labour, the advent of a society with a rising average age, the needs for elite talents and the development of key technologies must be solved one by one through development. The development of AI and intelligent machines can lead to the “replacement of humans by machines” and to industrial transformation and upgrading. It will provide new momentum and become a new trend for innovation. It cannot be said, however, that the development of AI can solve all economic and social problems, but it is safe to say that the AI industry can create good opportunities to solve the existing economic and social problems. The Chinese social progress and economic development urgently need the effective presence and participation of AI. The industrial transformation, upgrading and reconstruction of China’s growth also provide a “useful place” for the development of AI technology and industry.
4) The advantage of intellectual resources
Although China’s AI has started late and has gone through a long and winding development path, it has unique advantages in terms of intellectual resources.
Firstly, AI focuses on software and the Chinese have a good tradition and special wisdom in this regard. Wu Wenjun, known as the father of Chinese Artificial Intelligence, has emphasised that China is not only suitable ground for the mechanisation of mathematics as a typical mental work, but also fertile ground for the mechanisation of all kinds of AI. Ancient China was the birthplace of the transformation of mental work into factual achievement – although it was seen as an intellectual achievement and not as a practical application: suffice it to say that gunpowder was not used in wars, but was mostly used in recreational events.
Secondly, China currently has sound foundations, effective means and a wealth of experience necessary to develop the true mechanisation of mental work. The shushu method (by “art of predictions” we mean a series of methods for predicting the future developed in pre-imperial China, which played a significant role in the history and culture of the country), used to study even mathematics in Chinese history, is similar to the algorithm currently used to study AI.
China has a huge Internet user base, the largest number of netizens and talents, who form an important advantage in terms of resources of the AI group. Netizens are people who share a common interest and active engagement in improving the Internet, thus making it an intellectual and social resource. The term was widely adopted in the mid-1990s as a way to describe those who inhabit the new geography of the Internet. Internet pioneer and author Michael F. Hauben is credited with coining and popularising the term.
Thirdly, a large number of repatriated experts sent by China to study AI abroad have become the cornerstone and the academics of research and development on the subject, and are also extremely important for the industrial application and training of a new generation of teachers and professors.
Fourthly, China’s pro-reform and opening-up development environment will continue to attract more overseas students and foreign experts engaged in this field to join the common path of improving AI on a global scale.
China’s AI technology and industry is in the best period of development opportunities, provided that the talent strategy is well formulated and implemented, so that there is no longer the need to go abroad to learn, and a national school can be created.
5) The preliminary foundation of the industry
Compared with the robot industry, China’s AI industry started very late, but in recent years it has made great progress in its research achievements and industrial transformation, which is not in the same situation as it was years ago. In the current context of deep development and wide application of big data, cloud computing and the mobile Internet, national and foreign IT companies have seized the opportunity to implement the AI industry. Taking the smart voice sector as an example, its potential market is worth 10 billion US dollars: China’s Baidu, and the US Amazon and Google are conquering the top positions, and competition from smart voice cards of technology giants has begun to take shape.
The increase in the size of China’s voice industry is mainly due to the following three reasons: (i) the government’s political and financial support for the research, development and industrialisation of intelligent voice technology has created a favourable environment for the development of the voice industry; (ii) voice technology suppliers continue to optimise product performance, further deepening the application of intelligent voice in vehicle information service systems, smart homes and other fields; and (iii) the popularisation of 5G networks (5th Generation), big data development and cloud computing provide a strong guarantee for intelligent voice applications. These three reasons are also the fundamental basis for the development of this industry in China.
At present, information technology giants take intelligent voice as an entry point and proactively implement development in the field of AI. Internationally, Internet companies such as Google, Apple, Microsoft, Amazon, IBM, Facebook, etc., which have proactively promoted the research, development and application of intelligent voice technology, have taken this as an entry point to initiate the scheme of the entire AI field. At the same time, Chinese national companies such as Baidu, Tencent, Alibaba, iFLYTEK, Xiaoi Robot, Spichi, Yunzhisheng, BGI and Jietong Huasheng are proactively implementing AI based on intelligent interaction (voice and text).
Besides the intelligent voice industry, China also has some innovative products and industries in other aspects of natural language processing. Furthermore, image processing, machine learning, smart driving, smart home, smart sensors and other fields have also been planning the arrangement of elements that will make China’s related software independent. China’s AI industry is gradually taking shape and its standardisation also needs to be strengthened.
6) Financial Assistance
With the fast development of the economy and the unprecedented improvement of national strength, China’s monetary and financial supply has a respectable international status and has invested massively at home and abroad. In recent years, the national capital market has paved the way for the development of the AI sector. With such progress, it will be able to create cutting-edge industries. These new giants of national entrepreneurship could evolve exponentially in a short time. At the same time, a talent or a business idea could sprout from even a small company or a single, as yet unknown manufacturer.
The capital market’s enthusiasm for intelligent robots has caused the stock horizon to show a rare pattern. Investment in the robotics industry has increased and the amount of robotics industry’s financing has more than tripled. At the same time, the number of mergers and acquisitions in the robotics industry is also increasing year by year. Many listed companies have been involved in the mergers and acquisitions of robotics companies. Some national companies have started to turn to foreign markets, thus giving way to a larger scale of development.
With the further implementation of the Made in China 2025 plan, the potential energy of China’s robotics industry will be further released. There are signs that once the country has fully introduced an AI strategy, national and foreign financial capital will be invested in the AI industrial chain with the same enthusiasm as for intelligent robots. (9. continued)
The Promise of Blockchain in Mega Sport Events
Authors: Dr. Aiman Erbad and Dr. Mohamed Abdallah
Amid the excitement and anticipation of the FIFA World Cup Qatar 2022TM, sport remains a business. Like other global industries, the adoption of technology innovations is driving greater efficiency and transparency to generate benefits for sports organizations, leagues, clubs, and fans.
Researchers at the College of Science and Engineering (CSE), Hamad Bin Khalifa University (HBKU), make the case for adopting blockchain-powered solutions in delivering seamless sport mega events by outlining some of the top use cases.
“Blockchain can solve many real-world problems,” explains Dr. Mohamed Abdallah, Associate Professor in the Division of Information and Computing Technology (ICT) at CSE.
“For mega sport events, the benefits can be exceptional. Because of its transparent data structure, blockchain can facilitate secure and reliable data exchange at the individual, institutional, or national systems level as needed, without the need for intermediaries to ensure mutual trust and the authenticity of the data exchanged.”
The chaos of the UEFA Champions League final between English team Liverpool and Spanish club Real Madrid in May 2022, which resulted from the illegal distribution of non-validated tickets, is likely to have accelerated the recognition of blockchain’s benefits for the sport industry. The ensuing government inquiry unequivocally called for using blockchain for ticketing to prevent a similar fiasco at future events. A closer look at the nature of this cutting-edge technology reveals why.
How blockchain works
By its functional nature, a blockchain is a distributed (or shared) digital ledger that stores encrypted blocks of transaction data securely chained together in chronological order. Unlike other ledgers or databases, blockchain combines unique security features based on cryptographic techniques and its chronological chain structure.
In its standard form, blockchain provides immutability (data entered is permanently recorded), transparency (data is visible to everyone involved), and decentralization (all computers in the network have a copy of the blockchain to collectively maintain control). These features facilitate a tamper-proof, reliable way of storing, exchanging, and tracking information.
A key use case for mega events: preventing ticketing scandals
Dr. Abdallah and Dr. Aiman Erbad, Associate Professor and Head of ICT at CSE, add their expert voices to arguments that the UEFA Champions League final chaos could have been prevented using a blockchain platform with a self-enforcing contract capability to facilitate a secure ticket purchase process.
In practical terms, tickets can be stored on the blockchain denoted with unique cryptographic tokens. Each ticket can be linked to the authentic owner, providing traceability and accountability that prevents forgery. In this way, it can effectively reduce the impact of bots and/or scammers buying large numbers of tickets for illegal resale.
Using blockchain-based “smart contract” technology, ticketing entities can set the required resale rules to ensure a fair and secure market. These digital contracts can facilitate transactions between buyers and sellers while maintaining data accountability and traceability.
A related use case is storing the chain of ticket ownership. These records cannot be forged since changes are verified and tracked, ensuring data integrity. It can help customers validate the authenticity of tickets to avoid being trapped by ticketing scams.
Other use cases in sport
Blockchain-powered fan engagement is a growing use case for the sports industry. Several professional leagues and clubs are using blockchain to establish trustworthy fan databases that facilitate the distribution of “fan tokens”. With the status of a digital asset (created on a blockchain), the tokens can be redeemed by fans for rewards such as VIP experiences or ticket promotions. The increased fan engagement can potentially create new revenue streams for clubs; for example, incentivizing them to attend more events in person. Fan tokens have been rolled out by professional sports teams all over the world, including Paris Saint-Germain and FC Barcelona.
In another use case, the market for sports collectibles and memorabilia can leverage blockchain to establish trust and traceability. Experts have warned that fraud is rampant in the sports collectibles and memorabilia market. Blockchain can ensure the authenticity of special items through the use of digital identities.
CSE’s own blockchain-based applications
CSE faculty members are developing innovative use cases for blockchain in a range of applied settings.
“Our research focuses on the applicability of blockchain in solving real-world problems, such as securing data access in healthcare and decentralized trading,” says Dr. Erbad.
“We also study the technical aspects of blockchain to enhance its security, privacy, and efficiency. We have investigated the possibility of reducing energy consumption in public blockchains and developed an energy-efficient consensus algorithm. In other areas, we have also investigated using artificial intelligence in combination with blockchain smart contracts, called Rational Contracts, to provide smart resource trading with optimal prices in smart city applications.”
Among CSE’s blockchain-based applications are a trading platform for electric vehicle charging in smart cities, a decentralized ride-sharing service, a privacy-preserving decentralized stock exchange platform, a scalable energy trading sealed-bid auction mechanism, real-time secure health data exchange system, and a cooperative spectrum management system for 5G networks.
A national blueprint for Qatar
CSE had a leading role in developing the Qatar National Blockchain Blueprint in collaboration with the Communications Regulatory Authority and Qatar University. The blueprint highlights how blockchain can advance Qatar’s innovative and growing IT sector.
Essential blockchain requirements and recommendations for building a solid regulatory framework drive its pivotal goal of facilitating blockchain’s adoption at the national level, in support of Qatar National Vision 2030 and Qatar National Development Strategy. To achieve this, the blueprint outlines the conditions and incentives each sector must provide for the level of technology adoption needed to allow start-ups, pilot projects, and new companies to emerge. The strategy is an important step for Qatar, its sports, and other leading industries, to reap the societal benefits of this innovative technology.
For more information on the work of the College of Science and Engineering, please visit cse.hbku.edu.qa. To know more about Qatar National Blockchain Blueprint, please visit: https://www.cra.gov.qa/document/national-blockchain-blueprint
Interesting archaeological discovery in Israel
An ancient scarab from three thousand years ago was surprisingly discovered during a school trip to Azor, near Tel Aviv, Israel. The scene depicted on the scarab probably represents the conferral of legitimate power and authority on a local ruler.
“We were wandering around, when I saw something that looked like a small toy on the ground,” told Gilad Stern of the Education Centre of the Israeli Antiquities Authorityntre, who was leading the school trip. “An inner voice told me: ‘Pick it up and turn it over.’ I was amazed: it was a scarab with a clearly engraved scene, the dream of every amateur archaeologist. The pupils were really enthusiastic!”.
The visit of the Rabin Middle School eight graders took place as part of a tour guide course organised by the Education Centre of the Israel Antiquities Authority for the third consecutive year. The course enables students to teach the residents of Azor about the local archaeological heritage.
The scarab was designed in the shape of the common dung beetle. The ancient Egyptians saw in the gesture of the tiny scarab, which rolls a ball of dung twice its size where it stores its future offspring, the embodiment of creation and regeneration, similar to the gesture of the Creator God.
According to Dr. Amir Golani, an expert of the Israeli Antiquities Authority specialized in the Bronze Age period, “the scarab was used as a seal and was a symbol of power and status. It could be inserted into a necklace or a ring. It is made of silicate earthenware covered with a bluish-green glaze. It could have fallen from the hands of an important and influential personage passing through the area, or it could have been deliberately buried in the ground with other objects and after thousands of years returned to the surface. It is difficult to determine the precise original context.”
The lower, flat part of the scarab seal depicts a figure seated on a chair in front of a standing figure, whose arm is raised above that of the seated person. The standing figure has an elongated head, which seems to represent the crown of an Egyptian pharaoh. It is possible that we are seeing here a snapshot of a scene in which the Egyptian pharaoh confers power and authority on a local Canaanite.
“This scene fundamentally reflects the geopolitical reality that prevailed in the Land of Canaan during the Late Bronze Age (approx. 1500-1000 BC), when local Canaanite rulers lived under Egypt’s political and cultural hegemony (and sometimes rebelled against it)” – said Dr. Golani. “It is therefore very likely that the seal dates back to the Late Bronze Age, when the local Canaanites were ruled by the Egyptian Empire”.
Scarab seals are indeed distinctly Egyptian, but their widespread use extended beyond the borders of ancient Egypt. Hundreds of scarabs were discovered in the Land of ancient Israel, mostly in tombs, but also in settlement layers. Some of them were imported from Egypt, many others were imitated in ancient Israel by local craftsmen under Egyptian influence. The level of workmanship of the particular scarab found is not typical of Egypt and may be a product of local craftsmen.
Towards Efficient Matrix Multiplication
Algorithms have, over the years, helped mathematicians/scientists solve numerous fundamental operations. From the early use of simple algorithms by Egyptian, Greek, and Persian mathematicians to the shift towards more robust AI-enabled algorithms, their evolution has manifested incredible progress in the technological realm. While Artificial Intelligence (AI) and Machine Learning (ML) are extending their reach and contributions in various military and civilian domains, it is interesting to witness the application of the technology on itself, i.e., using ML to improve the effectiveness of its underlying algorithms.
Despite the increased familiarisation with algorithms over time, it remains fairly strenuous to find new algorithms that can prove reliable and accurate. Interestingly, ‘Discovering faster matrix multiplication algorithms with reinforcement learning,’ a recent study by DeepMind, a British AI subsidiary in London, published in Nature, has demonstrated some interesting findings in this regard. It revealed new shortcuts simulated by AI for faster mathematical calculations vis-à-vis matrix multiplication.
DeepMind developed an AI system called ‘AlphaTensor’, to expedite matrix multiplication. Matrix multiplication – which uses two grids of numbers multiplied together – is a simple algebraic expression often taught in high school. However, its ubiquitous use in the digital world and computing has considerable influence.
‘AlphaTensor’ was tasked with creating novel, correct, and efficient algorithms to carry out matrix multiplication with the least number of steps possible. The algorithm discovery process was treated as a single-player game. It used AlphaZero – the same AI agent which gained global traction when it displayed extraordinary intelligence in board games like Chess and Go.
AlphaTensor conceptualised the board into a 3-D array of numbers which, through a limited number of moves, tried to find the correct multiplication algorithms. It uses reinforcement learning, where the neural networks interact with the environment toward a specific goal. If the results are favourable, the internal parameters are updated. It also uses Tree Search, in which the ML explores the results of branching possibilities to choose the next action. It seeks to identify the most promising action at each step. The outcomes are used to sharpen neural networks, further helping the tree search, and providing more successes to learn from.
As per the paper’s findings, AlphaTensor discovered thousands of algorithms for various sizes for multiplication matrices, some of which were able to break decades-long computational efficiency records of the previously existing algorithms. They overshadowed the towering complexity of the best-known Strassen’s two-level algorithm for multiplying matrix. For example, AlphaTensor found an algorithm for solving a 4 x 4 matrice in 47 steps overperforming the Strassen algorithm, which used 49 steps for the same operation. Similarly, if a set of matrices was solved using 80 multiplication steps, AlphaTensor reduced it to only 76 steps. This development has caused quite a stir in the tech world as it is being claimed that a fifty-year old record has been broken in Computer Science.
However, the episode underlines some important implications. Given that matrix multiplication is a core component of the digital world, companies around the world have invested considerable time and resources in computer hardware for matrix multiplication. Since it is used across a wide range of domains, including computing, processing images, generating graphics, running simulations, digital communication, and neural networks etc. – to name a few, even minor improvements in matrix multiplication’s efficiency could have a notable and widespread impact in the concerned fields.
The findings manifest the potential of ML to solve even more complicated mathematical problems. The automatic discovery of algorithms via ML offers new capacities to surpass the existing best human-designed algorithms. It introduces new ML techniques, which have the potential to increase computing speed by 20 percent leading to much more feasible timelines. It is pertinent to mention that a lesser number of operations lead to not only lesser time but also less amount of energy spent.
The finding has presented a model to gamify ML to solve mathematical operations. It exhibited that AlphaZero is a potent algorithm that could be used beyond winning traditional games and be applied to solving complex mathematical operations/tasks.
This DeepMind discovery can pave the way for future research on understanding matrix multiplication algorithms and be an inspiration to use AI for algorithm discovery for other computing tasks and set the stage for a possible breakthrough in the field.
The increased efficiency of matrix multiplication has once again brought into light the ever-expanding potential of AI. To be fair, such developments do not infer that human programmers would be out of the job soon; rather, at least for now, it should be seen as an addition of an optimisation tool in the coder’s arsenal, which could lead to more innovative discoveries in the future with remarkable implications for the world.
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