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China’s Big Tech: From Free Development to Strict Regulation



After a decade of explosive growth, China’s tech sector lost hundreds of billions of dollars in less than two and a half years of the state’s large-scale regulatory campaign. China’s five largest Big Tech companies lost nearly 50% of their combined market capitalization. While in 2020, Tencent had larger capitalization than Facebook and most other American companies, today America’s Apple with its market value of $2.7 trillion exceeds the capitalizations of Tencent, Alibaba, Baidu, Meituan, JD.COM, and Pinduoduo combined. Following the start of the regulator’s probe into its activities, DiDi alone lost over 90% of its market capitalization. Generally, China’s tech sector lost its former foreign investor appeal. In the first quarter of 2022, investment into it fell by 42.6% in quarterly terms or by 76,7% in annual terms. Over 200,000 employees were fired from internet companies over the last year.

Nonetheless, it would be a mistake to think that Chinese authorities wanted to stifle the development of China’s tech sector. Beijing successfully applied its regulatory measures to address almost all its problematic areas in the sector’s development. Chinese authorities demonstrate their commitment to creating a fully controlled regulatory environment for the so-called platform economy. Regulatory measures are intended to increase the social responsibility of businesses and bring companies and their activities compliant with national security demands.

Recently, due to a national economic slowdown brought by the COVID-19 pandemic, as well as uncertain external conditions, Chinese authorities are eager to show both businesses and investors that there will be no political pressure put on Big Tech. Vice Premier of the State Council Liu He supported the platform economy and expressed his hope that tech companies will play a constructive role in reviving national economy. Liu He, who is considered one of China’s top officials in charge of the economic bloc (along with Premier Li Keqiang), also welcomed businesses to attract financing at both domestic and foreign capital markets. By doing so, Beijing likely wants to revive investor optimism and demonstrate that China is far from anathematizing tech giants.

Nonetheless, the already adopted regulatory measures should not be expected to weaken. Given that for the last decade China’s tech sector has been developing practically regulation-free, it is now clear that the past development dynamics will no longer be. Using regulations, Chinese authorities drew red lines for China’s Big Tech. Chaotic capital expansion, monopolist practices, and uncontrolled use of data are categorically prohibited to businesses by rules that can no longer be broken. Those companies that want to attract financing and actively work on international markets without leaving the domestic market will likely have to look for additional compromises. One possible scenario is transferring a certain share of a company to the state and appointing party officials to the company’s board of directors, thereby granting more control leverages and making their activities more transparent.

The last decade is often called the golden era in the development of China’s technological sector. Over a short period of time, many companies have grown from small startups into international tech giants. Back in 2020, six out of the world’s ten largest unicorn companies (i.e. companies with a capitalization over $1 billio) were Chinese. ByteDance Ltd. still remains the world’s most expensive startup, with a capitalization of $140 billion. However, 2021 marked a turning point in the development of China’s Big Tech: within a year, China’s technological sector lost more than $ 2 trillion in capitalization amid toughening regulations. Although Beijing has shown some leniency to tech companies, the long-term trend for tough sectoral regulations is likely to remain. To better understand the logic behind these changes, we need to follow the transformation of the state’s development priorities that determined the regulations for tech companies.

National Innovations and National Champions

Even though China had established its “global factory” status by the late 1990s-early 2000s, the share of added value created directly in China was small: 14.5% for electronics and computers, 28.1% for telecommunication equipment, and 27.5% for home appliances. China maintained its status as a “global factory”, entrusted with overseeing “knock down” assembly, simple, labor-intensive, or environmentally harmful manufacturing. China’s authorities realized that given the growth of China’s economy and of its population’s income, this development model would inevitably drive China into a middle income trap. On average, China’s GDP per capita in 1995–2005 grew by over 10% annually, while in some years, for instance in 1994 and 1995, it reached up to 25% and 29%. Obviously, the existing economic development model (i.e. exporting finished products manufactured through an abundance of cheap labor force) ran its course. The best way out of the predicament was seen in increasing the share of added value, diversifying specific advantages, using innovations as an important economic development resource, and also gradually transforming the growth model by using the potential of China’s colossal domestic market.

In 2006, China published its 2020 Medium to Long-Term Plan for the Development of Science and Technology. This plan noted the importance of national innovations as the main goal of developing science and technology in the next 15 years. Plans involved stimulating national innovations through investment, tax benefits, and targeted funding. A major part was assigned to public procurement. Thus, China developed its first paradigmatic document defining the state’s subsequent policies and priorities focused on developing technologies and innovations. This document launched the growth of “national champions”, or private tech companies that were looked on favorably by the state and enjoyed every consequent priority in the state’s policies. This was a form of mutually advantageous cooperation: a business was given certain preferences, while local authorities, first off, demonstrated consistent compliance with the policies proclaimed by central authorities, and secondly, met their own region’s needs for economic development. Provinces competed in attracting the largest numbers of tech companies. Often, provincial authorities concluded exclusive partnership agreements with a locally headquartered company. Such a company gained direct access to the regional market and was also prioritized when it came to participating in governmental contracts. Virtually every large Chinese tech company (Alibaba, Tencent, Huawei, Inspur, etc.) had the exclusive partner status in one or even several Chinese provinces, and essentially became a monopolist provider of the goods and services it specialized in. Additionally, these companies received major subsidies from local authorities, which sometimes covered over 30% of their expenditures. Later, “national champions” became a means of self-expression not only for local authorities, but for some national regulators as well. This, in particular, explains the apparent lack of coordination between the People’s Bank of China and the China Securities Regulatory Commission. The latter approved the IPO of Ant Group, Alibaba’s financial technology subsidiary, in record time, while China’s Central Bank saw this IPO as a source of systemic risks for the stability of China’s financial system.

It would, however, be a mistake to suppose that preferences and subsidies granted by the state were the main factors for China’s growth of internet giants. The companies that subsequently grew into tech giants built their business on meeting the current market needs; they managed to predict the trends in market development. For instance, Alibaba and Tencent were founded when no more than 2% of Chinese were internet users. In 2005, the figure climbed to 10%, then to over 30% in 2010, and today, China has nearly 1 billion internet users, which is more than the combined population of the US and the EU. Alibaba correctly focused on the tremendous potential of e-commerce and on the unmet consumer demand, particularly in China’s rural areas. Tencent, in turn, adapted internet services to Chinese customer preferences, thus significantly improving customer experience. Ant Financial, Alibaba’s financial technology subsidiary, started developing mobile payments; this subsidiary was established because a trust problem between customers and suppliers necessitated creating an online version of banks’ letters of credit to be used on Alibaba’s e-commerce platform.

It is also important that China’s tech companies operated in a relatively closed domestic internet space with severely limited competition from foreign players. Nonetheless, foreign investors rated very highly the objective market prospects of China’s tech companies. For instance, Alibaba’s IPO brought in $21.8 billion, and the entire company was valued at $167.8 billion at the time it went public.

China’s authorities tried not to limit the development of tech companies in any way, sometimes even disregarding their own legislation. For instance, Chinese law prohibits involving foreign capital in China’s internet sector, yet China’s internet companies circumvented this prohibition by establishing so-called Variable Interest Entities (VIE); companies were registered mostly in offshore account, bearing the same name, along with a claim to the assets and profits of the parent corporation. China’s authorities primarily cared about tech companies handling the urgent tasks of facilitating economic growth and social development. For instance, internet companies fill in all the gaps that emerged in the online space following the ban on popular foreign internet services; they create a favorable environment for internet users and improve user experience. “China’s internet” has replicas of all popular international services such as Facebook, Google, Twitter, WhatsApp, Wikipedia, Quora, and YouTube; consequently, “China’s internet” developed as a “thing in itself”, discouraging users from using circumvention tool to access banned resources.

E-commerce services benefited small business development while also handling the important social task of creating jobs and overcoming poverty. In 2014–2017 alone, online retail in rural China grew from $27 billion to $189 billion. The so-called Taobao villages (named after Alibaba’s domestic online trading platform) helped farmers establish their own channels for selling their goods, thereby creating about 840,000 jobs. In turn, Ant Financial, Alibaba’s financial technology subsidiary, issued 100 billion yuan worth of loans to 2 million people from the poorest rural areas in a single year.

Overall, financial technology companies were helping to resolve the problem of giving several hundred million people with no credit history access to financial products. Traditional banks preferred to work with large state enterprises to whose aid the state would come should things go south, while loans to small business and individuals were issued on a leftover principle. Consequently, China’s authorities viewed financial technology companies as a quick way of handling the growth problem of small and medium-sized business that, however, accounted for nearly half of the national GDP growth and over 60% of urban jobs.

The state prioritized the role of the internet sector in furthering socioeconomic development in its Internet Plus action plan, which was first announced by Li Keqiang, the Premier of China’s State Council, in 2015. Presenting the annual report on the government’s activities, Li Keqiang said that the Internet Plus plan would entail broadly integrating internet services with traditional economic and industrial sectors. According to the Premier, this plan would guarantee the internet’s decisive role in optimizing the locations of manufacturing factors and to give economic development a new impetus. The plan envisaged lowering barriers for tech companies’ IPOs, accelerated construction of digital infrastructure and related high-tech manufacturing facilities, and introducing cloud computing technologies and big data into the work of governmental bodies.

The leaders of tech companies increasingly influenced the opinions of China’s top state officials. Tencent’s founder Ma Huateng, for instance, became a member of the National People’s Congress. Incidentally the very phrase “Internet Plus” was used by Ma Huateng even before Li Keqiang announced the program. Therefore, some speculate that the head of Tencent influenced the formation of the new concept of digitalizing the economy. His competitor, Jack Ma, the head of Alibaba, repeatedly spoke about the importance of big data as a new source of economic growth. His recommendations were allegedly reflected in the 13th five-year development plan (2016–2020). Whether or not this is true is impossible to verify, but a separate article is devoted to introducing a national big data strategy.

In any case , China’s tech companies set new world records as they developed at lightning speed during the 12th and 13th five-year plans. The P2P lending sector, for instance, grew by over 200% annually. Alibaba and Tencent virtually became monopolists on China’s mobile payment market, with each company having over 700 million users. Before the pandemic, the revenues of DiDi, China’s vehicle-for-hire company, grew by more than 10% annually. Alibaba’s Yu’e Bao, an asset management product which offered an extremely low entry threshold of just 1 yuan, became the world’s largest money market fund by the late 2010s,, managing about $9 billion. With time, it became clear that tech companies could no longer develop unsupervised as their activities began to generate systemic stability risks. The sanctions against Alibaba, which ended with the cancellation of its IPO and a record $2.8 billion fine, are often taken as the starting point of the “regulatory winter”. Indeed, Alibaba’s case became the largest in China as regards the amount of financial penalty assessed. However, the first regulatory steps had been taken long before this case. All the potential risks posed by tech companies and, accordingly, all regulatory steps taken in their regard can be divided into three parts: combating chaotic capital expansion; anti-monopoly regulations; and threats to data security.

Chaotic Capital Expansion

Back in 2017, China’s President Xi Jinping in his address to the 19th Congress of the CPC proclaimed that China had to win “three difficult battles”: a battle against poverty, a battle against environmental pollution, and a battle against financial risks. These risks began to emerge after 2008 when Beijing decided to offer $585 billion. worth in economic stimulus money. The funds were supposed to go to the economy’s real sector and to infrastructural construction. However, central authorities contributed only one third of that amount; the rest had to be contributed by local governments. Since local authorities could not legally take out loans directly from banks, they relied on affiliated companies, local government financing vehicles (LGFV) that essentially acted as creditors.

This created a colossal demand for loanable funds, and the banking sector could not fully meet it, partly because of regulatory restrictions. . Hence, so-called shadow banking began to develop. CEIC Data reports that from 2008 to2017, shadow banking in China tripled from 20% to 60% of the GDP. Shadow banking is generally understood as off-balance sheet assets of traditional banks meaning loans issued by trusts, pawnshops, and micro lenders. The general problem with these schemes is, as the name suggests, that they are conducted out of sight of banking supervision, and therefore, may pose risks to the stability of the financial system.

This is, for instance, exactly what happened with P2P lending platforms. Their numbers in China peaked at 5,000, while they only numbered in dozens in other states. After one of the largest platforms, Ezubao, defaulted and 900,000 investors lost $7.3 billion, regulators began to look closely into the specifics of China’s P2P platforms. It turned out that instead of being merely informational go-betweens connecting creditors and borrowers, as is the case everywhere else, Chinese P2P platforms acted as quasi-banking structures: they accumulated investors’ funds guaranteeing them high returns and issued their own loans. In 2018, the Executive Group’s Office for Special Risk Management in Internet Finance issued “Notifications on Greater-Intensity Normalization of Online Asset Management and Establishing Supervision.” In particular, this document notes that currently active P2P platforms must: obtain a license to work; stop creating reserves out of investor funds,;act solely as intermediaries between creditors and borrowers; cap loan total costs at 36% interest rate (China’s supreme court capped total loan cost in 2015);operate solely via a depository bank; and cap loans per single borrower at 200,000 yuan for natural persons and 1 million yuan for legal entities. Companies were given a year to ensure they were compliant with the new norms. However, not a single company could become compliant, and by 2021, China had no P2P platforms at all.

In September 2020, China’s Central Bank announced comprehensive regulatory measures to regulate the activities of all tech companies offering financial services. Under these rules, any company that is not officially a financial enterprise, but has two or more financial divisions, should be registered as a financial holding. To be licensed, a company should have registered capital of at least 5 billion yuan. The new regulations extend to non-financial companies managing commercial banking bodies with assets totaling over 500 billion yuan, and to non-financial companies managing non-banking financial bodies with assets totaling over 100 billion yuan. Such companies should request a license from China’s Central Bank and, if this license is issued, add “financial holding” to their name. If a conglomerate is denied a license, it must sell or transfer its shares and control of its financial divisions. These rules cap loans issued to natural persons at 300,000 yuan and loans issued to legal entities at 1 million yuan. Simultaneously, a loan cannot exceed one third of a person’s average income for the last three years. Finally, new rules mandate that micro lenders may not attract bank funds or stockholder funds in amounts exceeding the amount of the company’s net assets. Also, the amount of funds attracted by issuing bonds and by securitization may not be more than four times the company’s net assets. Additionally, if a micro lender or an internet finance platform issues a loan together with a bank or other financial institutions, the micro lender’s or the internet finance platform’s share in the loan should be no less than 30%.

These rules appeared before Alibaba’s founder Jack Ma delivered his seditious speech at the Bund Summit financial forum in Shanghai. So, while the cancellation of Ant Group’s $37 billion IPO is often labeled as regulators’ “revenge” for Jack Ma’s arrogance, a much more likely reason seems to be that Ant Group did not comply with the new regulatory rules. Ant Group’s placement memorandum for investors said that consumer loans and loans to small businesses brought in 39.4% of the company’s revenues. For example, as of June 2020, outstanding loans issued via Ant Group’s platforms totaled 1.73 trillion yuan (261 billion dollars.). About 98% of these funds were either underwritten by banks or securitized. In other words, Ant’s balance sheet carried only 2% of loans. Traditional banks and investors carried risks for all the other loans that had in fact been issued by Ant Group.

In December 2020, the Politburo of the Central Committee of the CPC announced at its meeting that China would combat “chaotic capital expansion.” Rénmín Rìbào, the party’s main newspaper, explained that chaotic capital expansion refers to the logic of gaining profits at any cost, when development is detrimental to public interests. Therefore, a purely economic component was augmented by a social factor motivating Beijing to regulate the tech sector. In the thinking of Chinese authorities, financial stability goes hand in hand with the needs of building a harmonious society. Therefore, regulation means not only minimizing risks for the financial system, but also eliminating factors that provoke social instability.

Steps taken to combat the online education market fit into this framework as well. China’s State Council first mentioned the need to regulate online education and reduce school studentworkload back in 2018. Already in 2021, Chinese authorities first prohibited foreign investment in education and then mandated converting all online education tech platforms into non-commercial organizations. The two largest players on the market, Yuanfudao and Zuoyebang, were fined $389,000 for misleading marketing practices. Needless to say, these restrictions came as a shock to a sector that had accumulated at least $100 billion in investment. Nevertheless, as declining birthrates create serious demographic problems, regulating the sector that averagely consumes,30% of families’ annual income, and exacerbates social stratification between urban and rural populations became a political priority.

The food delivery sector also began to pose certain social instability risks. On the one hand, it was rapidly gaining popularity: from 2016 to 2020, the number of people ordering food online doubled to 400 million people. Two companies, Meituan and, were virtually monopolists in this area. However, in an effort to take over the largest possible market share, each company tried to use its competitive edge aggressively through algorithms that optimize logistics This manifested primarily in delivery times and the range of foods offered. However, media and social networks eventually began to report horrendous labor conditions of delivery personnel who had to break traffic rules and work overtime if they wanted to meet rigid delivery deadlines; most importantly, the companies fined delivery personnel for smallest delays regardless of objective circumstances such as traffic, weather, time of day, etc. In 2021, an official from the Beijing Municipal Human Resources and Social Security Bureau went to work undercover for one of the companies and personally ascertained the harsh working conditions. Two months later, China’s State Administration for Market Regulation (SAMR) and six other state agencies developed regulations mandating that food delivery services extend basic social guarantees to their employees, including minimal wage-compliant earnings, and the ability to form trade unions. Additionally, companies were prohibited from using the harshest algorithms and were mandated to give employees more time to complete every delivery. Also, companies were mandated to set up special rest and food areas for employees and issue them special gadgets (like smart helmets) that would enable them to use their smartphones hands-free. Later, eateries complained about food delivery aggregators charging excessive fees. In February 2022, Chinese authorities mandated that companies reduce fees charged to food businesses.

Combating chaotic capital expansion applied to the online games market, too. Back in 2018, China’s authorities suspended issuance of approval for new games by relevant regulators, and in 2019, the authorities prohibited people under 18 from playing games after 10 p.m. They also mandated that companies ensure compliance with these requirements via, among other things, compulsory user identification. In August, China’s largest state media labeled games as “spiritual opium,” and soon the authorities prohibited children under 18 from playing online games for over a combined total of three hours a week. Tencent, the largest manufacturer of online games, was forced to increase its expenditures on complying with new regulations (including user verification). In 2022, the company’s revenues demonstrated negative dynamics for the first time since its 2004 IPO. Additionally, as a goodwill gesture, the company promised to earmark $7.7 billion for social “universal welfare” goals, another slogan China’s leadership frequently reiterates.

Anti-monopoly Regulation

Officially, China adopted anti-monopoly legislation back in 2008, and China’s Supreme Court heard the first anti-monopoly case of two Chinese IT-companies (Qihoo 360 Technology Co. Ltd. and Tencent Holdings Ltd.) in 2014. The two companies marketed rival products (antiviruses 360 Safeguard by Qihoo and QQ Doctor by Tencent) and used dubious competitive practices. Ultimately, Qihoo upgraded its 360 Safeguard product and it started blocking QQ’s pop-up ads. Tencent, in turn, also upgraded its QQ messenger, and it stopped working on computers that had the 360 Safeguard antivirus installed. In other words, consumers had to choose “one out of two”, a phrase that will be incorporated into Chinese antitrust law for several years… Although China’s Supreme Court recognized that these actions caused some harm to businesses, the specific economic damage, expressed in the loss of the customer base, was considered insignificant back then. The existing antimonopoly legislation of the time was too general and did not account for the specifics of internet business.

In November 2020, two weeks before an antimonopoly probe was launched against Alibaba, draft antimonopoly rules for internet companies were published. They were adopted in less than six months with minimal changes. Under these rules, a monopoly means practices, including digital platforms, that deliberately limit the compatibility of their own products with competitors’ products. Forcibly routing internet traffic and blocking a competitors’ hyperlinks for the purpose of restricting client access is prohibited. Additionally, the practice of “choosing one out of two” when online marketplaces prohibited sellers from simultaneously cooperating with other online trading platforms is held to be inadmissible. Fake advertising, paid-for client reviews, and other misleading information was prohibited as well.

Additionally, harsher measures were adopted for antimonopoly regulation of companies working with online payments, internet finance, and financial technology. Under these rules, any non-banking company holding over half the market, or two companies holding over two thirds of the market, or three companies holding over ¾ of the market will be subjected to an antimonopoly probe. Should China’s Central Bank notice any signs of monopolism undermining the principles of business security, efficiency, fairness, and reliability, it may file a grievance with relevant antimonopoly bodies and spearhead an antimonopoly probe even if the company’s business does not comply with the above criteria.

The verdict in the Alibaba case was the most high-profile outcome of an antimonopoly campaign. The company was fined a record amount of $ 2.8 billion, which totaled 4% of its 2019 annual turnover in China. China’s State Administration for Market Regulation found that Alibaba had systematically violated antimonopoly regulations: it forced sellers selling goods on its e-commerce platform to work solely with Alibaba’s platform. Trading on other e-platforms was forbidden; otherwise, the company threatened to hide the seller’s goods in its search results and to cut them from any promotion campaigns.

After the demonstrative punishment of Alibaba, top managers of all the largest Chinese internet companies were summoned for a talk with the regulator. They were reminded that monopolistic policies were inadmissible. Later, almost every one of them was fined for various violations of antimonopoly legislation: for exclusive agreements on distributing musical context (Tencent), for failure to disclose information about mergers and acquisitions (Baidu, Shenzhen Hive Box), and for promoting inaccurate information that misleads customers (JD.COM). Another major case involved food delivery service aggregator Meituan, who was fined $530 million for exclusive agreements and for using its monopoly to force customers to choose “one out of two.”

Antimonopoly regulation of China’s tech companies stemmed from the objective need to whip into shape the market environment and create conditions for healthy competition. This process was closely tied to combating “chaotic capital expansion”, analyzed above. China’s tech giants aggressively used non-competitive methods to push out smaller players. For instance, when China introduced regulations for financial technology platforms, Alibaba’s subsidiary Ant Group and Tencent’s WeChatPay service were virtually monopolists in the mobile payments market. These companies divvied up a market of 1 billion users, although officially another 233 Chinese companies were licensed to engage in the same activities. Beijing knew that without requisite regulations, tech giants would become a backbone force hard to control even at the level of state. For instance, even though China’s Central Bank mandated that all mobile payments operators process transactions using a specialized clearing platform controlled by the regulator, companies repeatedly violated requirements for relevant supervision of capital movement. Finally, looking at the global practice that involved EU and US authorities conducting antimonopoly probes against global giants such as Amazon, Beijing realized it was time to act. Some may even go so far to say that China managed to catch up with and overtake its international partners. Today, China has instituted a very strict regulatory regime for tech companies; this is particularly true for protecting, processing, and transmitting data.

Data as a National Asset

In 2013, ex-NSA employee Edward Snowden publicized information about American secret services using vulnerabilities of IT systems throughout the world to garnish intelligence information. This made China ponder the influence data may have on national security. In 2017, Cybersecurity Law went into force mandating, among other things, storing all data on Chinese users in China. Subsequently , technological confrontation with the US had an even greater influence on Beijing’s data policy.

The US has a competitive edge (fundamental research, qualified personnel, hardware/firmware) in practically all key technologies such as artificial intelligence, while China outstrips the US only in quantity and quality of data. This led to Chinese authorities placing a particular emphasis on regulating turnover of data as a crucial national asset. In 2021, China passed the “Data Security Law” and “Personal Information Protection Law” (PIPL). Under these laws, data is viewed as a national asset, another production factor on par with labor, land, capital, and technology. Data is also categorized by importance: regular data, key data, personal data. Cross-border transmission of key and personal data is rigidly regulated. This procedure may be conducted only after this data has been comprehensively checked by appropriate authorities.

Under PIPL, the confidentiality of user personal information was further stringently protected. The law mandates that the multitude of mobile apps and services have no right to deny their services to a user who refused to submit their personal information, except for the cases when this information is absolutely necessary for the proper functioning of an app. Users now have the right to receive specific information on how, where, by whom, and for what purpose their personal information is used. Companies must obtain user informed consent to use, store, and process their personal information. Users may revoke their consent at any time. The laws rigidly regulates cross-border data exchanges. If a company accumulates a large array of data about Chinese citizens, then, before conducting any data exchange with foreign partners, this company must undergo a strict cybersecurity check and obtain approval from the appropriate Chinese authorities.

China’s vehicle-for-hire company DiDi was the main “victim” of the new data protection legislation. DiDi launched its IPO on the New York Stock Exchange just when the relevant data security legislation was in the works. Merely a few days after DiDi’s $4.4 billion IPO, China launched a probe against DiDi regarding its compliance with data protection standards. The company was mandated to remove its apps from app stores and stop attracting new users. The probe against DiDi – concluded only when the company announced it was delisting itself from the American exchange.

The demands of US regulators to disclose information raises security concerns to Chinese authorities. The US demands that all companies listed on American exchanges grant the Public Company Accounting Oversight Board (PCAOB) unobstructed access to audit and accounting reports. Previously, Chinese companies ignored this demand citing Chinse legislation that prevented them from disclosing such information to international partners and regulators. In 2020, however, the US passed the Holding Foreign Companies Accountable Act (HFCAA). Under this act, should any company listed on American exchanges fail to provide data and accounting reports for three years, it will be forcibly delisted. China’s vehicle-for-hire company DiDi works on the domestic market and accumulates sensitive data concerning movements of millions of Chinese citizens. Naturally, such a company launching an IPO with the potential condition of transmitting these data to the US is a very risky step. Although the authorities did not publicly say so, from a regulator’s point of view, the main condition for companies like DiDi to continue operating is to prevent uncontrollable cross-border transmission of data.

As for domestic information security, Chinese authorities started regulating the use of algorithms by companies. The State Internet Management Office together with the Ministry of Industry and Information Technology and the Ministry of Public Security announced measures that have been in place since 2022. Under these rules, companies must not use recommendation algorithms for illegal purposes, for instance, for undermining national security. News sites whose work is based on algorithms must undergo a special licensing procedure; recommending fake news is prohibited. Additionally, companies are mandated to inform users about the recommendation service’s basic principles, purpose, and operating procedures; users should also have the option to opt out of receiving recommendations created through the use of algorithms. Companies also must provide users with the option of choosing or removing tags the algorithm uses to form recommendations. Finally, users may not be subjected to price-based discrimination based on an algorithmic analysis of their online behavior.


After a decade of explosive growth, China’s tech sector lost hundreds of billions of dollars in less than two and a half years of the state’s large-scale regulatory campaign. China’s five largest Big Tech companies lost nearly 50% of their combined market capitalization. While in 2020, Tencent had larger capitalization than Facebook and most other American companies, today America’s Apple with its market value of $2.7 trillion exceeds the capitalizations of Tencent, Alibaba, Baidu, Meituan, JD.COM, and Pinduoduo combined. Following the start of the regulator’s probe into its activities, DiDi alone lost over 90% of its market capitalization. Generally, China’s tech sector lost its former foreign investor appeal. In the first quarter of 2022, investment into it fell by 42.6% in quarterly terms or by 76,7% in annual terms. Over 200,000 employees were fired from internet companies over the last year.

Nonetheless, it would be a mistake to think that Chinese authorities wanted to stifle the development of China’s tech sector. Beijing successfully applied its regulatory measures to address almost all of its problematic areas in the sector’s development. Chinese authorities demonstrate their commitment to creating a fully controlled regulatory environment for the so-called platform economy. Regulatory measures are intended to increase the social responsibility of businesses and bring companies and their activities compliant with national security demands.

Recently, due to a national economic slowdown brought by the COVID-19 pandemic, as well as uncertain external conditions, Chinese authorities are eager to show both businesses and investors that there will be no political pressure put on Big Tech. Vice Premier of the State Council Liu He supported the platform economy and expressed his hope that tech companies will play a constructive role in reviving national economy. Liu He, who is considered one of China’s top officials in charge of the economic bloc (along with Premier Li Keqiang),also welcomed businesses to attract financing at both domestic and foreign capital markets. By doing so, Beijing likely wants to revive investor optimism and demonstrate that China is far from anathematizing tech giants.

Nonetheless, the already adopted regulatory measures should not be expected to weaken. Given that for the last decade China’s tech sector has been developing practically regulation-free , it is now clear that the past development dynamics will be no more. Using regulations, Chinese authorities drew red lines for China’s Big Tech. Chaotic capital expansion, monopolist practices, and uncontrolled use of data are categorically prohibited to businesses by rules that can no longer be broken. Those companies that want to attract financing and actively work on international markets without leaving the domestic market will likely have to look for additional compromises. One possible scenario is transferring a certain share of a company to the state and appointing party officials to the company’s board of directors, thereby granting more control leverages and making their activities more transparent.

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Artificial Intelligence and Advances in Physics in the Field of Gravitational Waves (I)

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As an important branch of natural sciences, physics studies fundamental laws and phenomena such as matter, energy, mechanics and motion, thus providing an important theoretical basis for human beings to understand and explore the natural world. To be precise, physics models nature mathematically.

With the advancement of science and technology and the fast development of Artificial Intelligence, physics is facing new challenges and opportunities. The AI application is changing the research methods and development trajectory of physics, thus offering new possibilities for progress and innovation.

Artificial Intelligence can help physicists to build more accurate and complex models and to analyse and interpret experiments and data provided by observation. We must keep in mind algorithms such as machine learning, of which deep learning is a part.

The difference lies in the fact that deep learning is more advanced: a deep learning algorithm is not conditioned by the user’s experience. Just to make an example, in non-deep machine learning, to distinguish cats and dogs you have to tell “do it by ears, hair, etc…”, while in deep learning the distinguishing features are extracted by the code itself and, often or always, they are actually patterns that we humans would never be able to have!

It does this in the following way: you give it a set of training data and the expected results. The algorithm starts to do tests on this recognition until it reaches an acceptable accuracy value based on what it should come up with by using iterative mathematics (and obviously there is the human hand in the construction of the algorithm). When it has “adjusted”, you can use it on unknown pictures of cats and dogs, not used for learning, so that it classifies them to the human without the human having to do it himself/herself. Considering the above, Artificial Intelligence can discover hidden patterns and correlations from large amounts of data, thus helping physicists to understand and predict related phenomena.

Artificial Intelligence can be applied to theoretical physics and computational physics research to improve the efficiency and accuracy of computational models and methods. For example, Artificial Intelligence can help physicists develop numerical simulation methods since machine learning is not only for classification, but also for numerical prediction, which is especially useful in the financial field, as it is more efficient at speeding up experiments and calculations.

Artificial Intelligence also has broad applications in the fields of quantum physics and quantum computing. Quantum physics is a branch of science that studies the behaviour of microscopic particles and the laws of quantum mechanics, while quantum computing is an emerging field that utilises the characteristics of quantum mechanics for information processing and calculations. Artificial Intelligence can help physicists design more complex quantum systems and algorithms and promote the development and application of computer science.

The AI application in high-energy physics and particle physics experiments is also very important. High-energy physics studies the structure and interaction of microscopic particles, while particle physics studies the origin and evolution of the universe. Artificial Intelligence can help physicists analyse and process large amounts of experimental data and discover potential new particles and physical phenomena.

Al technology can improve the efficiency of physics research and accelerate the scientific research process. Physics research often requires large amounts of experimental data and complex computational models, and Artificial Intelligence can streamline the work of physicists in discovering hidden patterns and correlations in this data. Artificial Intelligence can also provide more accurate and detailed physics models, helping physicists solve even more complex scientific problems.

Traditional physics research often relies on existing theories and experiments, while Artificial Intelligence can help physicists discover new phenomena and physics laws. By bringing to light patterns and correlations from large amounts of data, Artificial Intelligence stimulates physicists to propose new hypotheses and theories, thus promoting development and innovation.

The AI application explores unknown fields and phenomena. By analysing and extracting information from large amounts of data, Artificial Intelligence expands the scope and depth of physics research.

The development of Artificial Intelligence offers new opportunities for the integration of physics with other disciplines. For example, the combination of Artificial Intelligence and biological sciences can help physicists study complex biological systems and related phenomena. The combination of Artificial Intelligence and chemistry can help physicists study molecular structure and chemical reactions.

Although AI technology has broad application prospects in physics research, it also has to face some challenges including the acquisition and processing of data as this is the main problem, especially when dealing with new issues for which databases are scarce; the creation and verification of the physical model; and the selection and optimisation of algorithms. In this regard, it must be said that the boom in deep learning has mainly been due to the increase in available data thanks to the Internet and the advancement of hardware. The networks that anyone uses can run on their laptops, albeit slowly, but this would have been unthinkable in the 1990s, when deep learning was already being thought of in a very vague way. It is not for nothing that we speak of the “democratisation of deep learning”.

Future development requires cooperation and exchanges between physicists and AI professionals to jointly resolve these challenges and better apply this new technology to physics research and applications.

As an emerging technology, Artificial Intelligence is revolutionising traditional physics. By applying Artificial Intelligence, physicists can build more accurate and complex models, analyse and explain physics experiments and observational data. Artificial Intelligence necessarily accelerates the research process in physics and promote the development and innovation of so-called traditional physics.

Artificial Intelligence, however, still has to face some challenges and problems in physics research, which require further study and exploration. In the future, AI technology will be further utilised in physics research and applications, thus providing more opportunities and challenges for development and innovation.

AI technology is also used in gravitational wave research, whose 2017 Nobel Prize in Physics was awarded to Rainer Weiss (Germany), Barry C. Barish (USA) and Kip S. Thorne (USA).

On 14 September 2015 this group of scientists detected the gravitational wave signal of a system of two black holes merging for the first time. At that moment, it triggered a revolution in the astrophysics community: the research group involved in the discovery of gravitational waves was listed as a candidate for the Nobel Prize in Physics ever since.

The two black holes are located about 1.8 billion light years from Earth. Their masses before the merger were equivalent to 31 and 25 suns in size, respectively. After the merger, the total mass was equivalent to 53 suns in size. Three suns were converted into energy and released in the form of gravitational waves.

For some time, gravitational waves have attracted the attention and curiosity not only of scientists, but also of ordinary citizens. Despite being a weak force – a child lifting a toy amply demonstrates this – gravitational interaction has always created questions: but what are gravitational waves?

To put it simply and briefly, this concept of gravitational waves comes from Einstein’s theory of general relativity. We all know that the theory of relativity always discusses the dialectical relationship between space-time and matter, and the viewpoint of gravitational waves is that matter causes ripples and bends into space-time. The curve propagates outwards from the radiation source in the form of a wave. This wave transmits energy as gravitational radiation and the speed of gravitational waves is close to that of light. An extreme case is a black hole. Its supermass causes a distortion of space-time; light cannot escape and slips into it.

Because our basic understanding of traditional physics is based on Newton’s theory of universal gravitation, it is assumed that all objects have a mutual attraction. The size of this force is proportional to the mass of each object. Einstein believed this theory to be superficial. The reason for what appears to be the effect of gravity is due to the distortion of space and time. Hence, if Newton’s law of universal gravitation is approximate, is our current knowledge based on traditional physics going astray? The question is an awkward one. Hence let us leave it to scientists to further study who is right and who is wrong.

Having said that, however, cosmic scientific research currently uses ever more AI techniques, such as the aforementioned detection and discovery of gravitational waves.

The biggest challenge in capturing gravitational waves is that the sampling rate of LIGO (Laser Interferometer Gravitational-Wave Observatory) data is extremely high, reaching a frequency higher than 16,000 times per second, with tens of thousands of sampling channels. Hence the amount of data is extremely large. It is then understood that with AI machine learning, etc. and state-of-the-art methods in the field of data processing, research efficiency can be improved. (1. continued)

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Towards A Better World: Our Senses and How Artificial Intelligence is Replicating Them

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Our five senses help us perceive the world around us.  The sense of touch, for example, can bring loved ones closer but, on a darker note, can also frustrate amputees.  What bothers them particularly about their prosthetic arms is missing feedback.  Is what they are touching hot or cold, liquid or solid, a rose or its thorn; an aspect so universal for the able-bodied that it is not given a second thought.   

Though it has not escaped Artificial Intelligence (AI) researchers who are trying to replicate these senses (Engineering and Technology, August 2023).  They have been busy developing artificial hands with softer fingers and embedded sensors.  How long will it be before the problem is solved? 

Well, a US company Atom Limb is expecting to release a mind-controlled prosthetic limb in 2024.  In it the movement sensors in the hand section of the prosthesis send electronic signals to the wearer’s stump, where the neurons once connected to the amputated hand are still in place and capable of transmission to the brain.

Notice how we know at once when there is something crawling on our skin.  In May 2022, researchers at Stanford University’s Bao Research Group announced the invention of artificial skin that is durable, paper thin and stretchable.  This has the future potential of being wired into the wearer’s nervous system to give a real touch capability — namely, sensing temperature, pressure, vibration and location.  Thus when the finger moves from the handle to the cup itself, you sense the change in temperature and distance.

Another sense, that of hearing or rather lack thereof, is not infrequently a source of humor.  Possibly because the sufferers are able to compensate through other means.  Beethoven suffered from Paget’s disease.  It caused skull bone enlargement which pressed on the eighth cranial nerve associated with auditory function.  The loss was gradual from the age 28 to 44 when he was quite deaf.  While he could still hear a little, he would strap an ear trumpet on his head so he could conduct the orchestra with his hands.  He also carried a notebook and pencil to jot down musical brainstorms but also to converse with friends. 

Hence the somewhat morbid joke of someone seeing Beethoven sitting on his grave furiously erasing some sheet of music.  “Maestro!  Maestro!  What are you doing,” the person asks, to which he gets the reply, “I am decomposing.” 

Hearing loss when it is congenital is no joke, however.  It can inhibit language learning and speech.  Thus the words ‘deaf and dumb’ are often placed together with ‘dumb’ of late being replaced by the kinder ‘mute’. 

Here again technology comes to the rescue.  Cochlear implants have been around for quite a while.  Invented in 1957, the first implant procedure is credited to Stanford University.  A single-channel electrode was used but was found to be of limited utility for detecting speech.  It took a further 20 years to get to the modern multi-channel type. 

Hearing aids now are small enough to be barely visible.  They work for most people and only those with profound hearing loss consider the implant option. 

Our sense of sight helps us navigate the world around us, and enjoy its beauty.  For some it may be taken away gradually through macular degeneration (AMD).  It is a form of retinal deterioration that affects the sight of some 200 million people in the world.  As the photoreceptors in the central retina degenerate, it impairs the ability to read or even recognize people.  

The good news is that a prosthetic replacement is now being developed to replace the lost photoreceptors with photovoltaic pixels.  These convert light into electricity which stimulates the neurons in the retina.  While the present version leaves the recipient somewhat shortsighted, a newer one currently being tested in rats will restore 20/20 vision. 

For the future, there is Science Eye, a device employing optogenetics.  It uses gene therapy to restore optic nerve cells while an ultra-dense micro-LED display panel is inserted directly over the retina. 

There are others in the field including Cortigent which is making headway with a system that does not require genetically modifying retinal cells because it is a direct cortical (brian layer) stimulator.  Cortigent is in the process of designing a study to get their stimulator implant approved.  They have already spent five years studying the safety and reliability of their devices.

Then there are our senses of smell and taste, to some extent linked.  There is a good reason food seems bland and tasteless when a person has a bad cold — the sense of smell is absent.  Thus when chefs talk about flavor, they imply both taste and smell.

Taste receptors in the mouth sense sweet, sour, salt, bitter and savory — the latter also known as umami.  But try sucking a lemon flavored candy while pinching your nose.  You will taste the sweetness, but not the lemon flavor.  The tongue is, of course, also sensitive to cold and heat. 

A promising approach to treatment for loss of smell is to train the olfactory nerve through inhaling a set of odors (originally rose, lemon, clove and eucalyptus) twice daily for three months.  It was found to help the nerve to regenerate. 

Taste has been with humans forever.  Long before scientists and their experiments, humans knew to avoid plants that tasted bitter — it signified something harmful.  Yet there are people unfortunate enough to be without this sense. 

Having all the senses is so commonplace that we rarely ponder their absence.  So let the next gustatory and olfactory experience, or the music we hear, or the walk we take in a park where we can also smell the flowers, be all the more meaningful for valuing our senses.  Harnessing them and adding that subconscious sense of perception to enhance our understanding of the world as it is, and we need only imagination to observe the world as it could be … to be ready to take the first step on the journey to a better one, a world at peace. 

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Development of Metaverse in China: Strategies, Potential, and Challenges Part I

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In the rapid era of digitalization, the metaverse has become a hot topic among developed countries. While many nations focus on the entertainment aspect of the metaverse, China appears to have a different perspective. Adopting a more industry-oriented approach, can the Bamboo Curtain country lead the next metaverse revolution?

Why Does China Opt for an Industrial Approach?

There are several reasons why an industrial approach might be China’s key to success in the metaverse:

Real Needs

The metaverse, with its virtual simulation technology, has immense potential to revolutionize various industries like manufacturing, urban planning, and healthcare. In manufacturing, the metaverse can facilitate product design optimization, in-depth employee training, and manufacturing process optimization through virtual prototypes and real-time simulations, enabling instant collaboration between designers and engineers, thus reducing time and costs associated with physical prototypes.

Regarding urban planning, the metaverse can be applied for the visualization of city layouts and infrastructure in a 3D virtual environment, allowing urban planners to make better-informed decisions about urban development. Moreover, it enables public participation in urban development projects, offering citizens the chance to explore and provide input on proposed designs, and promoting sustainable development through the environmental impact analysis of urban designs.

In the healthcare sector, the metaverse can be used for medical training, patient rehabilitation, and remote consultations. Medical students can practice medical procedures in a risk-free virtual environment, while patients can undergo intensive virtual medical consultations and rehabilitation therapy. This technology can enhance the skills and confidence of prospective doctors and expedite patient recovery processes.

Overall, the metaverse offers innovative and interactive solutions that can address the specific needs of various industrial sectors, allowing enhanced learning, better design, optimized processes, and innovative solutions, which will ultimately contribute to the progress of these industries.

Enhanced Productivity

Metaverse technology, with its capabilities in virtual and augmented reality, opens new doors in industrial efficiency and innovation. It enables industries to develop prototypes in virtual environments, accelerating product development cycles and reducing costs associated with physical models. For instance, in the automotive industry, designers and engineers can collaborate in a 3D environment to test and modify car designs in real-time, allowing a faster response to market needs.

Additionally, the metaverse plays a crucial role in employee training and development. In the manufacturing sector, virtual simulations can be utilized for operational machine and production process training, reducing risks and enhancing employee skills while saving training time and costs. This also contributes to increased safety and reduction of incidents in the workplace.

The metaverse also supports industrial process optimization through real-time simulations and data analysis. Companies can visualize and optimize workflows, plant layouts, and production schedules to enhance productivity and reduce operational costs. This enables quicker and more accurate identification and resolution of inefficiencies and obstacles.

In conclusion, the implementation of the metaverse in industries promises a revolution in product design, employee training, and daily operations. The ability to integrate and optimize various operational aspects in a virtual environment offers opportunities for sustainable innovation and heightened competitiveness in the modern industrial era.

Government Support

History shows that the Chinese government often provides full support to strategic sectors. With financial support and progressive regulations, the metaverse industry in China has the potential to grow rapidly. China is actively exploring the metaverse, with Beijing planning to create a ‘Digital Identity System’ for the metaverse and Web 3.0, following Shanghai’s footsteps. Even though known for being cautious in adopting advanced technologies, China sees significant potential in the metaverse and strives to establish a regulatory framework to develop virtual reality and the metaverse as part of the digital economy, as detailed in the Virtual Reality Development Action Plan released in November 2022. The proposed digital identity system aims to control user anonymity and identify individual characteristics in the metaverse, allowing regulated and controlled use of this technology. The regulatory proposal discussions are underway at the International Telecommunication Union (ITU), with the involvement of technology experts and Chinese telecom operators like China Mobile. This demonstrates China’s commitment to developing the metaverse in a safe and orderly manner, aligning with the high interest of its citizens, where 78% of Chinese citizens have expressed interest in the metaverse.

Differentiation from Competitors:

In the midst of tight global competition in the metaverse, China’s focus on industrial applications could be a key differentiator. While many other countries might be focusing more on entertainment aspects, China can lead in industrial applications of the metaverse. China chooses to focus on the industrial applications of the metaverse as part of its strategy to become a global leader in technology and innovation, aligning with the country’s ambitions to build competitive advantage in high technology and strengthen its trading position on the international stage. With its broad and diverse industrial sector, from manufacturing to healthcare, the integration of the metaverse allows for significant innovation and economic growth across various fields, enabling the development of specific and value-added solutions for industrial needs. Additionally, by focusing on industrial applications, China can also address challenges and risks associated with the metaverse, such as privacy and data security issues. The development of regulatory frameworks and technical standards for the industrial metaverse will ensure that this technology is developed and used safely, responsibly, and in line with national priorities and sustainable development goals.

Domestic Technology Development

China has been making substantial investments in cutting-edge technologies such as AI, 5G, and semiconductors, integrating these technologies with the metaverse to build a strong and competitive ecosystem. The adoption of 5G technology is key to the implementation of the metaverse, and I once read a book about the Metaverse written by experts in China, stating that mass adoption of the Metaverse will occur when 60% of the population has adopted 5G. Therefore, China currently seems to be focusing on developing 5G connectivity, hoping that the industrial sector will be the first adopter of this technology due to its higher purchasing power and more specific and limited scope. In the B2B context, this is considered a realistic step before introducing this technology to the end consumer. According to data from the GSMA The Mobile Economy Report China 2023, 5G penetration in China in 2023 is 45% of the population and is expected to reach 70% by 2027. Observing this data, it can be hypothesized that the evolution of Metaverse utilization in China will experience significant progress around the year 2027. Hence, in the coming years, we can observe how the integration between AI, 5G, semiconductors, and the metaverse can form a more synergistic and competitive technology ecosystem, where the industrial sector will play a key role in early adoption, before the metaverse truly enters and is accepted by the general consumers in China.


With an approach focused on the industry, China has the opportunity to lead the metaverse revolution in the future. However, as with any innovation, there will be challenges to face. With government support, investment in R&D, and a clear vision, China is on the right track to leverage the full potential of the metaverse for industrial interests and national economic growth.

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