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Auf dem Weg zur Modernisierung von Wissenschaft und Technik in China

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November 16, 2024

Auf dem Weg zur Modernisierung von Wissenschaft und Technik in China

Die Modernisierung von Wissenschaft und Technologie in China ist ein zentraler Bestandteil der allgemeinen Entwicklungsziele des Landes. Die Vision des damaligen Premierministers Zhou Enlai aus dem Jahr 1964 unterstrich die Bedeutung moderner Wissenschaft und Technologie für die Entwicklung der Landwirtschaft, der Industrie und der Landesverteidigung. Später betonte Deng Xiaoping, dass Wissenschaft und Technologie der Schlüssel zur Modernisierung Chinas seien. Auch Staatspräsident Xi Jinping betont heute die Rolle der Innovation als Motor für eine hochqualitative Entwicklung. Von der Übernahme westlicher Wissenschaften zu Beginn des 20. Jahrhunderts bis zum heutigen Fokus auf Eigenständigkeit war der wissenschaftliche Fortschritt Chinas ein wesentlicher Bestandteil der nationalen Modernisierung.

Grundlagen und frühes Wachstum der wissenschaftlich-technischen Modernisierung (1949-1976)

Von 1949 bis 1976 konzentrierte sich die wissenschaftliche Modernisierung Chinas auf die Sicherung des sozialistischen Aufbaus und der Landesverteidigung im Rahmen einer Planwirtschaft. Die 1949 gegründete Chinesische Akademie der Wissenschaften (Chinese Academy of Sciences, CAS) wurde zu einer zentralen Institution, die sich rasch ausdehnte und maßgeblich das Forschungssystem des Landes prägte. Die frühe Politik, die sich an der Sowjetunion orientierte, betonte die Ausrichtung der wissenschaftlichen Forschung auf praktische Bedürfnisse, woraufhin China Studenten in die UdSSR schickte, um etwas über Forschungsplanung und akademische Zusammenarbeit zu lernen.

In den 1950er Jahren führte das CAS Postgraduiertenprogramme ein, die eine neue Generation von Wissenschaftlern hervorbrachten. Der erste nationale Fünfjahresplan (1953) kurbelte die Nachfrage nach Wissenschaft und Technologie an und mündete in den “Plan zur wissenschaftlichen und technologischen Entwicklung für die Jahre 1956-1967”, der darauf abzielte, Chinas wissenschaftlichen Rückstand gegenüber der Welt aufzuholen. Dieser „aufgabenbasierte“ Ansatz konzentrierte sich auf 57 wesentliche Bedürfnisse des Landes und förderte Schlüsselsektoren wie Atomenergie, Elektronik und Automatisierung. Trotz Rückschlägen durch politische Kampagnen trugen die Reformen von 1961 zur Wiederbelebung der chinesischen Wissenschaftsgemeinschaft bei.

Der „Plan für die Entwicklung von Wissenschaft und Technologie 1963-1972“ legte den Schwerpunkt auf Autonomie und Innovation und erzielte bemerkenswerte Fortschritte in der Verteidigungstechnologie und der industriellen Infrastruktur. Obwohl die Kulturrevolution den wissenschaftlichen Fortschritt unterbrach, wurden weiterhin bedeutende Durchbrüche erzielt, darunter Satellitenstarts, die Entwicklung von Hybridreis und die Entdeckung von Artemisinin.

Die internationale Wissenschaftskooperation Chinas begann mit der Sowjetunion und weitete sich auf Osteuropa, westliche Länder und später Japan und die USA aus. Dieser internationale Austausch, einschließlich des Auslandsstudienprogramms in der UdSSR, spielte eine Schlüsselrolle für den wissenschaftlichen Fortschritt Chinas.

Transformation in der Reform- und Öffnungsperiode (1977-1994)

Mit dem Nationalen Wissenschaftskongress im März 1978, auf dem Deng Xiaoping die Bedeutung von Wissenschaft und Technologie für die Modernisierung betonte, begann die wissenschaftliche Transformation Chinas. Dies führte zu Wirtschaftsreformen, bei denen Wissenschaft und Technologie in die nationale Entwicklung integriert wurden.

Der Achtjahresplan (1978-1985) zielte darauf ab, die wissenschaftliche Lücke zu schließen, stieß jedoch aufgrund der mangelnden Integration in das Wirtschaftswachstum auf Schwierigkeiten. 1980 wurde eine neue Politik eingeführt, die Wissenschaft und Technologie mit der wirtschaftlichen Entwicklung in Einklang brachte. Bis 1982 konzentrierten sich die nationalen Programme auf Schlüsselbereiche wie Landwirtschaft und Energie.

Die internationale Zusammenarbeit spielte eine entscheidende Rolle, einschließlich der Kooperation zwischen den USA und China beim Beijing Positron Negative Electron Collider (BPEC), der Chinas Einstieg in die Hochenergiephysik markierte. Dengs Vision von Hochtechnologie wurde durch Projekte wie der BPEC und erhebliche Investitionen in die Infrastruktur Wirklichkeit.

In den 1980er Jahren reformierte China sein Wissenschaftssystem und gründete 1986 die National Natural Science Foundation of China (NSFC) zur Finanzierung der Grundlagenforschung. Private Wissenschafts- und Technologieunternehmen wie Lenovo wurden gegründet, um die technologische Modernisierung zu unterstützen.

Hochtechnologie, einschließlich IT, Biotechnologie und neue Materialien, wurde zu einem entscheidenden Faktor im globalen Wettbewerb. Als Reaktion auf Initiativen wie die US Strategic Defense Initiative startete China 1987 den „863“-Plan, um Hochtechnologie auf nationaler Ebene zu entwickeln.

Die Chinesische Akademie der Wissenschaften (CAS) spielte eine Schlüsselrolle in der Politikgestaltung, während gesetzliche Änderungen, darunter das Gesetz zum wissenschaftlichen und technologischen Fortschritt von 1993, einen rechtlichen Rahmen für Innovationen und Technologietransaktionen schufen.

Umstrukturierung und Reform des chinesischen Wissenschafts- und Technologiesystems (1995-2005)

1992 brachte Deng Xiaopings Dialog mit dem Süden die Reform Chinas voran und leitete eine neue Phase der Modernisierung ein. 1995 fassten das Zentralkomitee der Kommunistischen Partei Chinas und der Staatsrat einen Beschluss zur Beschleunigung von Wissenschaft und Technologie und betonten die Strategie der Wiederbelebung des Landes durch Wissenschaft und Bildung. 1996 nahm der Staatsrat eine umfassende Reform des Wissenschafts- und Technologiesystems vor und konzentrierte sich dabei auf die Forschungseinrichtungen der Zentralregierung.

In den 1990er Jahren gab es eine zunehmende Diskussion über Reformen in Wissenschaft und Technologie, beeinflusst durch das Konzept des Nationalen Innovationssystems (NIS), das 1995 von der Nationalen Kommission für Wissenschaft und Technologie und dem kanadischen IDRC eingeführt wurde. 1997 legte die Chinesische Akademie der Wissenschaften (CAS) einen Bericht über den Aufbau eines nationalen Innovationssystems vor, der vom Zentralkomitee der Kommunistischen Partei Chinas gebilligt wurde. Das 1998 gestartete „Knowledge Innovation Project“ reformierte die Chinesische Akademie der Wissenschaften und wurde zum Vorbild für andere Institutionen.

1995 startete China das „211-Projekt“ zur Stärkung der Universitäten. Das 1999 gestartete „985 Project“ zielte auf die Schaffung von Universitäten von Weltrang ab und umfasste bis 2004 39 Hochschulen. Darüber hinaus hat China in den Jahren 1999 und 2000 über 240 Forschungsinstitute umstrukturiert, ein Prozess, der die Entwicklung von Schlüsseltechnologien zwar gebremst, aber das Wirtschaftswachstum angekurbelt hat.

1997 wurde der Nationale Plan zur Entwicklung der Grundlagenforschung (973-Plan) formuliert, der sich auf langfristige nationale Bedürfnisse und wissenschaftliche Herausforderungen konzentrierte. Bis 2008 war der Erfolg des 973-Plans offensichtlich, da er die Grundlagenforschung in die nationale Strategie integrierte, das Niveau der wissenschaftlichen Forschung anhob und einen starken Pool an Forschungstalenten schuf, der die interdisziplinäre und angewandte Forschung förderte.

Aufbau des Systems zur Modernisierung von Wissenschaft und Technologie (2006-2020)

Mit dem 2006 verabschiedeten Entwurf des Nationalen Mittel- und Langfristigen Plans zur Entwicklung von Wissenschaft und Technologie (2006-2020) wurden die Voraussetzungen für Chinas nationales Innovationssystem geschaffen, mit dem Ziel, ein innovationsstarkes Land zu werden. Es folgten verschiedene Strategiepapiere wie die „Ansichten zur Vertiefung der Reform des Wissenschafts- und Technologiesystems“ (2012) und die „Skizze der nationalen Strategie für innovationsgetriebene Entwicklung“ (2016), in denen die Bedeutung des Aufbaus dieses Innovationssystems unterstrichen wurde.

Der Entwurf des Plans von 2006 knüpft an frühere langfristige Wissenschafts- und Technologiestrategien an. Er betont die Ziele der unabhängigen Innovation, der strategischen Entwicklungssprünge, der Förderung von Entwicklung und der zukünftigen Führung in Wissenschaft und Technologie. Die Ausarbeitung des Plans wurde durch umfangreiche Forschungsarbeiten unter Beteiligung von mehr als 2.000 Experten und Bewertungen durch renommierte akademische Institutionen unterstützt. Diese Forschung schuf eine solide Grundlage für die Entwicklung, die auf der aufstrebenden sozialistischen Marktwirtschaft, der industriellen Basis und der internationalen Zusammenarbeit Chinas beruhte.

Der Plan setzte verschiedene Handlungsinstrumente erfolgreich um, darunter Fünfjahrespläne für Wissenschaft und Technologie, Forschungsprogramme und Großprojekte. Bemerkenswerte Erfolge sind die bemannte Raumfahrt und die Initiativen zur Erforschung des Mondes. Weitere Schwerpunkte des Plans waren der Aufbau eines nationalen Innovationssystems, die Förderung der sektorübergreifenden Zusammenarbeit und die Stärkung der technologischen Basis Chinas.

Im Jahr 2014 leitete der Staatsrat eine Reform der Verwaltung der Wissenschafts- und Technologieprogramme ein, um die Ressourcenallokation und Effizienz zu verbessern. Darauf folgte der 13. Fünfjahresplan (2016), der eine nachhaltige Unterstützung der interdisziplinären und kooperativen Forschung vorschlug, um strategische wissenschaftliche Kräfte von Weltklasse aufzubauen.

Darüber hinaus wurden durch die Einrichtung großer nationaler Wissenschaftszentren in Städten wie Shanghai, Hefei und Peking Innovationsplattformen gestärkt und das nationale Innovationssystem unterstützt. Die chinesische Regierung hat auch der Entwicklung neuer Denkfabriken zur Unterstützung der wissenschaftlichen Entscheidungsfindung Priorität eingeräumt.

Insgesamt wurde die nationale Innovationsstrategie Chinas kontinuierlich verfeinert, wobei der Schwerpunkt zunehmend auf Zusammenarbeit, strategischer Führung und dem Aufbau eines robusten wissenschaftlichen und technologischen Beratungssystems zur Unterstützung politischer Entscheidungen lag. Dieser umfassende Ansatz hat China geholfen, sowohl beim wissenschaftlichen Fortschritt als auch bei der Technologieführerschaft bedeutende Fortschritte zu erzielen.

Förderung der Modernisierung von Wissenschaft und Technologie zur Stärkung der Nation (seit 2021)

Der im März 2021 verabschiedete 14. Fünfjahresplan und die Vision 2035 legen den Hauptakzent auf Innovation und positionieren die wissenschaftliche und technologische Autonomie als zentralen Schwerpunkt der chinesischen Entwicklungsstrategie. Er befürwortet eine strategische Ausrichtung auf Wissenschaft und Technologie, um das Wirtschaftswachstum zu fördern und die Lebensqualität der Bevölkerung zu verbessern. Der Schlüssel zu dieser Vision ist die Entwicklung eines robusten nationalen Innovationssystems und die Schaffung eines starken Wissenschafts- und Technologielandes.

Der 20. Parteitag der KPCh im Oktober 2022 hat das Ziel unterstrichen, China zu einer weltweit führenden Kraft in Wissenschaft und Technologie zu machen. Um dieses Ziel zu erreichen, müssen nicht nur die technologischen Fähigkeiten verbessert, sondern auch ein Umfeld geschaffen werden, in dem Bildung, Wissenschaft und Humanressourcen als Grundlage für Modernisierung und nationale Stärke dienen.

Die strategische Ausrichtung für die nächsten fünf Jahre konzentriert sich auf vier Schlüsselbereiche:

1. Stärkung der strategischen wissenschaftlichen und technologischen Kapazitäten des Landes.

2. Verbesserung der Innovationsfähigkeit der Unternehmen

3. Förderung des Innovationspotenzials von Talenten.

4. Verbesserung des wissenschaftlichen und technologischen Systems und der Prozesse.

Zu den wichtigsten Initiativen gehört die Einrichtung nationaler Laboratorien und hochrangiger Forschungseinrichtungen. Die Chinesische Akademie der Wissenschaften (CAS) und führende Universitäten wie die Tsinghua-Universität und die Peking-Universität nehmen in den weltweiten wissenschaftlichen Rankings herausragende Positionen ein, was die Fortschritte Chinas auf dem Weg zur Technologieführerschaft unterstreicht.

Das Thema ethische Governance in Wissenschaft und Technologie gewinnt zunehmend an Aufmerksamkeit, insbesondere in innovativen Bereichen wie der künstlichen Intelligenz (KI). China hat sich proaktiv an der Entwicklung globaler ethischer KI-Standards beteiligt, darunter der New Generation AI Code of Ethics von 2019 und die Global Initiative on AI von 2023.

Die Reform der Wissenschafts- und Technologiepolitik, die sich im Reformprogramm des Staatsrats von 2023 widerspiegelt, zielt darauf ab, die Führung zu zentralisieren und gleichzeitig die Managementverantwortung zu dezentralisieren, um die Effizienz des technologischen Fortschritts zu steigern.

Die letzten 75 Jahre der wissenschaftlichen Entwicklung Chinas haben gezeigt, dass ein Gleichgewicht zwischen Autonomie und internationaler Zusammenarbeit von entscheidender Bedeutung ist. In Zukunft wird es für China von zentraler Relevanz sein, einheimische Talente zu fördern, solide rechtliche Rahmenbedingungen zu gewährleisten und ein innovationsfreundliches Umfeld zu schaffen. Daher wird sich die Modernisierung von Wissenschaft und Technologie in China weiterhin auf die Bewältigung nationaler Herausforderungen konzentrieren und gleichzeitig zum globalen Fortschritt beitragen.

Quelle: OMFIF, CGTN, Xinhua

Chinese Company Earns $55.31 Million from Selling Second-hand Clothes in Africa

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November 15, 2024

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Chinese Company Earns $55.31 Million from Selling Second-hand Clothes in Africa

Walking through the streets of Africa, one will often spot striking Chinese phrases on clothing. A young man selling goods on the side wears a blue T-shirt with the phrase, “Order takeout, go to Ele.me” on the back, while a girl on a bicycle sports a light yellow shirt that says, “Cross Shenzhen,” and black pants with “Run, Brothers.” These bold Chinese characters are not local designs—they’re second-hand clothes from China that have made their way across the ocean.

Every year, millions of tons of discarded clothes flood Africa’s market, supporting a business worth billions. In 2023, global second-hand clothing sales hit $211 billion, growing by 19% from the previous year. By 2024, Africa’s clothing market alone reached $70.58 billion, growing at a rate of 5.16% annually.

This booming market has attracted many Chinese entrepreneurs. In 2010, Guo Song, a college student, began collecting discarded military training uniforms from classmates and reselling them to training centers. This side hustle ignited his interest in the second-hand clothing business.

In 2016, Guo Song and his team founded Gracer in Guangzhou. They use big data and logistics networks to collect, sort, and package domestic textiles, then export them to Africa, Southeast Asia, and beyond. Gracer processes tens of thousands of tons of second-hand clothing each year, with over 60% of its exports going to Africa. In 2023, the company’s transactions exceeded $55.31 million.

Africa has become the world’s largest market for second-hand clothing. In Kenya, for example, Nairobi’s bustling second-hand market is a central hub, with clothes passing through daily. In 2021, China became the largest exporter of second-hand clothing to Africa, accounting for over 40% of Kenya’s imports. With new clothes often out of reach for most African consumers, second-hand items have become a staple. In countries like Uganda and Tanzania, second-hand clothing not only meets basic needs but provides jobs and sustains local economies.

Despite opposition from some governments, which argue that second-hand imports harm local industries, the demand for affordable clothes is undeniable. In economically struggling regions, second-hand clothes are a lifeline. Guo Song notes that the market will persist as long as there’s demand—until people can afford new clothes, second-hand items will always be necessary.

But doing business in Africa isn’t without its challenges. Guo Song faced resistance when he expanded Gracer into Uganda, where local dealers felt threatened by foreign competition. Despite initial setbacks, including issues with customs and local collaboration, Guo Song’s team managed to scale to a monthly revenue of $1.38 million within six months. Yet, after three years, the Uganda operation collapsed, prompting a return to China.

The complexities of managing staff and operations abroad, combined with the lack of a compliant business environment, made it clear to Guo Song that while the product could thrive in Africa, building a sustainable operation there was far more difficult. In the end, he focused on refining the domestic supply chain to improve product quality and streamline logistics.

Now, Gracer has established a robust recycling and processing network across China, handling over 200 varieties of clothing in 245 cities. Guo Song remains committed to eventually re-entering Africa, once the company’s domestic operations are fully digitized. After all, a successful overseas venture requires deep local engagement—something he still plans to pursue.

Source: Gracer

The Dark Link Between Sexual Misogyny and Deepfake Pornography in South Korea

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November 14, 2024

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The Dark Link Between Sexual Misogyny and Deepfake Pornography in South Korea

The Deepfake Crisis in South Korea, which came to light through a tweet by S.K Feminist on 25 August 2024, reveals a growing crisis involving the use of artificial intelligence to create pornographic videos that exploit the images of ordinary people. The victims include military personnel, students, and healthcare workers, with the issue extending from previous scandals such as the Nth Room case of 2022 and a related incident at Seoul National University in 2024. The public outcry following the exposure of these deepfake crimes has attracted global attention, especially after coverage on Korean TV and in newspapers.

In response, President Yoon Suk-yeol called for an investigation into the matter, and the National Assembly passed an amendment to the Act on Special Cases Concerning the Punishment of Sexual Crimes on 26 September 2024. The law, once approved by the president, aims to punish the possession, distribution, and consumption of AI-generated deepfake pornography with up to three years in prison or a fine of up to $21,000. The punishment for producers of such videos will increase, with sentences potentially reaching up to seven years following the amendment. However, the law’s effectiveness remains uncertain, as it is unclear whether it can address the underlying social and cultural issues at play.

The flow of events in South Korea often follows a predictable pattern of social crises, dramatic responses, and subsequent legislative measures. While legislation is an important step, its ability to bring about real change remains questionable. This raises the existential question: if such measures fail to protect individuals and prevent harm, can they ultimately save the fabric of South Korean society?

South Korea’s problem with Internet-based sexual exploitation is deeply ingrained and difficult to eradicate. The country’s high-speed internet, widespread access, and large percentage of users provide an environment where such crimes thrive. This is compounded by a culture of small groups and social conformity, where the widespread use of social software, including image sharing and deepfake videos, facilitates exploitation. Despite technological advances, the legal framework in South Korea has been slow to address issues like consent in sexual crimes, offering lenient penalties and enabling repeated offenses. Additionally, South Korea’s historical tolerance of sex work and distorted sexual values have not fundamentally shifted with legal reforms, leaving the sex trade and exploitation in a gray area.

Socially influential groups, such as entertainers, also struggle to address the lack of deterrents for exploitation, as the regulation of their image rights remains weak. Even when deepfake pornography first emerged in 2017, prominent victims like Scarlett Johansson chose not to pursue legal action, with similar responses from Korean celebrities, further perpetuating the normalization of such crimes. This reluctance to recognize the harm caused by deepfake pornography has shaped public perception, with many dismissing it as “fake” and thus harmless.

As a result, South Korea has become a hotspot for deepfake pornography, with a significant portion of global victims being Korean women. The number of such cases has steadily increased, with underage involvement rising sharply in recent years. The root cause of this issue lies in a society steeped in misogyny, where changing the legal framework and increasing penalties may not be enough. Only a radical shift in South Korea’s political and social systems can truly address the deep-seated nature of these crimes.

The issue of internet sexual exploitation crimes in South Korea, particularly deepfake pornography, is closely intertwined with the country’s complex socio-political dynamics. These crimes are a manifestation of the deep-seated misogyny that permeates South Korean society, stemming from both traditional Confucian values and the exacerbating influence of wartime military nationalism. The normalization of male dominance, coupled with the proliferation of deepfake technology, allows for the sexual exploitation of women without direct physical involvement, creating a dangerous global reach for these crimes.

The rise of such crimes coincided with significant political changes in South Korea, particularly following the election of President Moon Jae-in in 2017. With the feminist movement gaining momentum globally, the backlash from conservative and anti-feminist groups intensified, particularly targeting the increasing recognition of women’s rights. This backlash was amplified by the spread of deepfake pornography and the creation of online forums where these exploitative materials were shared. In this context, technology became a tool for perpetuating gender-based violence, allowing men to coerce and exploit women remotely, bypassing traditional societal structures.

In parallel, South Korea’s mandatory military service system, which is a unique aspect of the country’s gendered social structure, further entrenches male privilege. Military service, viewed as a form of patriotism and a rite of passage for men, elevates male status in society. However, the rigid and often violent nature of military life, combined with the economic challenges faced by men after service, has led to resentment and a growing sense of male victimhood. This sentiment has contributed to the growing opposition to feminist movements, as men feel they are being unfairly disadvantaged by policies that promote gender equality.

The complex interplay of these factors has created a cyclical pattern of misogyny and gender-based violence in South Korea. The rise of deepfake pornography crimes, in particular, reflects a societal shift where technology is exploited to amplify traditional gender hierarchies and male power dynamics. This phenomenon is further compounded by the political manipulation of gender conflicts, with some political leaders using the divisive issue of gender equality to rally male voters.

The long-term consequences of these trends are far-reaching. South Korea’s declining fertility rate, driven by economic pressures and unresolved gender conflicts, threatens the country’s future stability. The government’s failure to address these issues from a gender-sensitive perspective has deepened the divide, leaving women caught between multiple sources of oppression. Ultimately, to break the cycle of misogyny and combat the exploitation enabled by deepfake technology, a fundamental shift in South Korea’s social, political, and cultural structures is necessary. This includes dismantling the systems that perpetuate gender inequality and ensuring that women’s rights and voices are given due recognition in both policy and society.

Source: BBC, Nikkei Asia

How China Chenghai Commands a Third of Global Toy Production

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November 13, 2024

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How China Chenghai Commands a Third of Global Toy Production

The global toy industry looks to China, and China’s toy industry looks to Chenghai. Walking through Chenghai, toy brand stores line the streets, and rows of towering buildings house over 50,000 toy production and management units, cultivating industry leaders like Sunfun Toys, Alpha Animation and Culture, Rastar Group, and Sembao Blocks. In 2023, the industry’s revenue exceeded $6.98 billion.

Known as China’s Toy and Gift Capital, Chenghai has developed a comprehensive industry chain from R&D and design to manufacturing and trade. The district produces half of China’s plastic toys, with the nation’s highest number of authorized brands, IPs, and patents, launching over 300,000 new toys annually for export to more than 120 countries. In 2024, Chenghai’s Toy Creative Industry Cluster was recognized as a specialty industrial cluster in Guangdong Province for small and medium-sized enterprises.

Despite this success, Chenghai’s toy industry faces challenges of low overall quality and homogeneous competition. As international competition intensifies, many Chenghai companies are shifting from contract manufacturing to building their own brands, moving up the value chain to higher-end segments.

Toy Factories Embrace Digital Intelligence

In Moyu Cube’s exhibition hall, there is an array of Rubik’s Cubes, including various types like traditional, anisotropic, magnetic, maglev, and AI-enhanced models, spanning hundreds of styles. “We’ve embedded Bluetooth chips, sensors, and gyroscopes in our Rubik’s Cubes, allowing users to follow guided steps for solving the cube and learning formulas,” explained Yang Jiandong, Moyu Cube’s marketing director. Since 2016, the company has utilized a fully automated production line, where AI-enabled machines have boosted production efficiency by 80 times. Moyu Cube’s digital upgrades reflect the broader transformation underway in Chenghai’s toy industry.

Huang Liang, Executive Vice President of the Shantou Chenghai District Toy Association, highlighted that in the 21st century, Chenghai’s toy sector adopted CNC machine tools, automated CNC injection molding machines, and other advanced equipment, resulting in large-scale production and industry clustering. Today, Chenghai has developed China’s most complete toy production chain, covering raw materials, R&D, IP creation, manufacturing, sales, and trade. The city’s products span early education, blocks, video games, and remote-controlled toys, producing one-third of the world’s and nearly half of China’s plastic toys.

Data from Shantou’s Bureau of Industry and Information Technology show that in 2023, Shantou’s 264 toy and creative companies generated an industrial output value of $4.31 billion, accounting for 8.8% of the city’s regulated industries, with an added value of $990 million.

Hong Kong’s Chen Hsong Holdings, a global leader in injection molding machinery, entered Chenghai in 2000. Over two decades, Chen Hsong’s machines have evolved from quantitative and variable injection models to servo and all-electric versions, aligning with Chenghai’s toy industry’s advancements. In 2016, Chen Hsong launched a specialized machine for building blocks and educational toys, capturing 50% of the local market and establishing Chenghai’s first smart factory in 2019 with local partners.

“With 12,000 injection molding machines in Chenghai, the toy industry has largely automated and is moving toward digital, intelligent production,” noted Chen Jianbo, a senior manager at Chen Hsong. Chen Hsong now holds a 60% local market share and up to 85% in sectors like blocks and Rubik’s Cubes. The company is exploring AI models for the toy industry, aiming to improve quality and yield by using big data for real-time adjustments and enhanced process intelligence.

Moving from Product to IP Overseas

Globally, nearly 75% of toys are IP-based, with popular IPs often driving growth across related industries. Recognizing this potential, Chenghai companies began exploring IP’s value over a decade ago. In 2009, Alpha Animation and Culture went public on the Shenzhen Stock Exchange, pioneering the “IP + industry chain” model with popular animation series like Super Wings, Balala the Fairies, Pleasant Goat and Big Big Wolf, and others.

Chenghai’s toy manufacturers are leveraging the domestic animation IP boom, expanding brands internationally. “Our foreign sales increased 35% this year, reaching $42–56 million,” shared Xie Yipeng, assistant general manager of Guangdong Jianjian Intelligent Technology. By tapping into markets in North America, Europe, and Asia, the company has doubled its overseas sales, responding to demand for remote-controlled vehicles with 30–40 new models annually.

Chenghai exports toys to over 120 countries through multiple channels, controlling about one-third of the world’s toy production. Sembao Blocks, a local leader in block-based toys, has grown through both independent IP and licensed partnerships since 2019, collaborating on themes like the Wandering Earth, Shandong aircraft carrier, CASCI, and Forbidden City Culture. Popular series such as Huayan Tea Language Flower sold 1 million units immediately after launch, achieving $2.8 million in single-product sales.

Chenghai’s “toys + IP” model has fostered numerous top IP-based toy companies, like Sembao Blocks and Rastar Group, giving the district the largest concentration of toy patents in China, with over 10,000 patents authorized each year.

To support this industry, Chenghai’s government has strengthened IP protections, establishing the country’s only dedicated rapid intellectual property rights center for toys. “Ordinary patent applications take three to five months, but our center’s fast track reduces this to just ten days, a critical advantage for product development and sales,” explained Chen Shunli, Director of Shantou’s (Toys) Intellectual Property Rights Center. This support helps Chenghai’s toy manufacturers thrive in a competitive global market.

Building a New Industrial Ecosystem through Chain Innovation

In the Guangdong Yuxing Technology, a streamlined process unfolds: blocks are sorted into barcode-labeled boxes by 36 robots, while an intelligent platform collects and analyzes production data in the cloud. Six years ago, company founder Xie Weichun, with nearly 20 years in toy manufacturing, saw an urgent need for automation due to labor shortages and quality control challenges. In response, Yuxing partnered with Shantou Gooders Precision Technology in 2018 to create an automated production line, marking a pivotal shift toward intelligent manufacturing.

Michael Porter’s competitive strategy model underscores the importance of new production factors—like skilled talent and research facilities—in bolstering industrial clusters. Chenghai exemplifies this model, evolving from traditional competition to collaborative innovation. Shantou Gooders Precision Technology, founded by Du Kehong in 2017, epitomizes this shift by specializing in precision block toy production through advanced mould-making and large-scale manufacturing. By adopting industrial-scale production and sharing resources like public warehouses, Chenghai’s toy industry has fostered a cooperative, resource-efficient ecosystem.

This collaborative model drives cost-effectiveness and competitiveness: Huang Liang notes that mass production enables Gooders to lower the cost per block to as little as 0.0014 dollar, reducing overall manufacturing costs by over 20%. Through initiatives like shared design spaces and a “community of destiny” for brands, Gooders has positioned Chenghai as a hub for high-end, scalable, and digitally advanced toy manufacturing. Sembao Blocks, one of Gooders’ first partners, leverages this model to sustain a 200-person design team and launch 500 new products annually, achieving a 102% increase in revenue in 2022.

In a broader push for industrial modernization, Shantou Chenghai has formed a plastic precision manufacturing alliance and China Telecom’s Toy Industry Digital Intelligence R&D Center, supporting automated production methods, where factories operate with minimal lighting and human intervention. Chenghai now hosts 78 national high-tech creative toy enterprises and over 40,000 support units, further solidifying its leadership in smart toy manufacturing.

Chenghai is driving digital and green transformations, integrating new information technology and digital trade networks. This chain innovation approach is propelling Chenghai up the “smile curve” of high-value production, reinforcing its status as a global leader in the toy industry’s digital future.

Source: amazon, aliexpress, CGTN, xinhua, guangdong news

Why Has India Struggled to Develop an Electric Car in Eight Years?

East Asia

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November 12, 2024

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Why Has India Struggled to Develop an Electric Car in Eight Years?

On October 12, Ratan Tata, a titan of Indian business, passed away. From Tetley Tea to Jaguar Land Rover and Air India, he fulfilled nearly every goal on his life’s wish list—except for one: the Tata Nano EV. This car became his only regret.

Tata’s ambition throughout his career was to provide affordable, efficient transportation to millions of Indian families. Had the Tata Nano EV succeeded, it could have been a groundbreaking achievement for both India and the global electric vehicle (EV) market.

In 2015, the Tata Group, in partnership with Indian automotive company Jayem, sought to develop a low-cost electric car, the Jayem Neo EV, which later became known as the Tata Nano EV. Ratan Tata personally oversaw the project, and hopes were high. The Nano EV was designed in two versions: a 48-volt and a 72-volt model. By 2018, Jayem produced 400 units, selling them to Ola Cabs for use in Hyderabad and Bengaluru during the early stages of the pandemic. However, despite the anticipation, the car was never officially launched, and Tata’s company never publicly explained why it was withheld.

Speculation surrounds the reasons for the Nano EV’s failure, but one key factor is India’s slow pace in adopting electric vehicles. Bhavish Aggarwal, the founder of Ola, has credited Tata as his guiding influence. He recalls a pivotal moment when Tata personally invited him to Coimbatore to test drive the Nano EV prototype. This experience inspired Aggarwal to launch Ola Electric, which today commands a third of India’s electric two-wheeler market, having sold over 300,000 units within three years. In contrast, the electric four-wheeler market has not seen similar growth.

The Nano EV, if it had materialized, would have been positioned as an affordable, compact car with an estimated price range of INR 400,000 to INR 600,000, a speed of 60-70 km/h, and a range of 300 km. Despite these appealing specifications, the car never came to market, leaving behind only unanswered questions.

The Nano EV’s failure is particularly striking given the legacy of its predecessor, the Tata Nano, which was launched in 2009 as one of the world’s cheapest cars, priced at around $9,000 today. The Nano was born from Tata’s vision to provide an affordable alternative to unsafe two-wheelers, sparked by a personal experience where he saw a family riding in the rain on a motorcycle.

The Nano’s design was a testament to cost-saving innovation: metal was replaced with plastic where possible, glue was substituted for welding, and features were minimal—only one rear-view mirror, hand-cranked windows, no airbags, and a sealed boot. Despite the strong initial demand, with nearly 70% of sales occurring in the first three to four years, fewer than 300,000 units were sold over a decade, in a country with over 1.4 billion people.

Many analysts argue that the Nano’s failure wasn’t due to its simplicity or safety features, but because of its stigma. In a class-conscious society like India, owning the “cheapest car” was seen as a social liability. Some believe the Nano EV, launched under the same name, would have been similarly tainted. Puneet Gupta, an automotive analyst, suggests that consumer preferences have shifted away from small cars, as reflected in the decline of sales in India’s fuel-car market.

J Anand of Jayem Motors, a key partner in the Nano EV project, has been reluctant to discuss its failure. He cites factors such as government regulations, the COVID-19 pandemic, and stringent crash standards as impediments. While reports suggest that engineers struggled to reduce the cost of the 72-volt version and that the car failed crash tests, Anand has stated that there are no plans to revisit the Nano EV project.

India, with its vast population and growing market, was once seen as a blue ocean for the automotive industry, but this notion has proven to be false for many international brands. Tesla has yet to deliver an electric car, and Chinese brands, after several attempts, have withdrawn from the market. Despite these struggles, India remains a highly attractive market for electric vehicles. By 2030, the Indian government aims to have 50 million EVs on its roads, with the market size projected to reach $48.6 billion, and electric vehicles expected to account for nearly one-third of the passenger car market.

While the government has expressed strong support for the growth of EVs, the reality is mixed. The highest penetration is in the three-wheeler segment (54%), followed by two-wheelers (6%), while electric four-wheelers account for a negligible share of the market. In FY2023, electric four-wheeler sales were just 90,000 units, or 2% of total vehicle sales, despite doubling year-on-year.

India’s electric vehicle market lags far behind China, which has rapidly expanded its EV offerings. As of July 2024, only 13 Indian automakers had at least one EV model, compared to China’s far more extensive range. Tata, BMW, and Audi lead the Indian market, with Tata capturing nearly two-thirds of the electric passenger car market. However, Maruti Suzuki, the leader of India’s passenger car market, has yet to launch any EV models. Moreover, the electric taxi market in India is underdeveloped, with BluSmart scaling back its ambitious plans for 100,000 electric taxis by 2025 to just 10,000 by early 2024.

Despite these challenges, India’s shift to electrification is inevitable. Hyundai’s new unit in India is set to launch a compact electric car, and Tata is planning to expand its EV lineup in the near future.

China, as a leader in the global electric transition, demonstrated how affordable EVs could become mainstream. The Wuling Hongguang MINI EV, priced at around $4,152, played a key role in this transition. In contrast, India’s EV market still lacks such affordability.

However, in early 2024, as battery costs fell, India began taking steps to make electric vehicles more accessible. The MG Comet EV became the cheapest EV in India, priced at approximately $60,000, while the Tiago EV is priced at around $68,486. Despite these price reductions, the Nano EV remains a highly anticipated model, with rumors circulating that Tata might soon release it.

Reports suggest that Tata could partner with Jayem, an unknown company, to release the Nano EV. While the design, interiors, and exteriors may be identical to the petrol-powered Nano, the logo would change from Tata to Neo. Since Jayem is largely unknown, the Nano EV will likely carry Tata’s legacy. If successful, it would be a triumph for Tata, but if it fails, Jayem would bear the blame, with Tata’s reputation and stock price unaffected.

The new Nano EV represents a significant departure from its predecessor. It includes modern features such as an infotainment system, Bluetooth, six speakers, power steering, power windows, ABS with EBD, and a 7-inch touchscreen. With a range of 100-120 km per charge and a top speed of 80-90 km/h, the Nano EV would be an excellent choice for daily commuting. Moreover, with an expected starting price of about $38,000, it is set to be one of the most affordable options in the Indian EV market.

Eight years after its initial unveiling, questions remain: will the Nano EV fulfill its promise? Can it become India’s answer to the Wuling Hongguang MINI EV, or is the Indian EV market still a distant dream? The success or failure of the Nano EV will determine whether Ratan Tata’s vision—and his regrets—can be redeemed.

Source: Times of India, Shifting Gears

Who Remembers That AI Was Never Meant to Replace People?

THINKVIEWS

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November 11, 2024

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Who Remembers That AI Was Never Meant to Replace People?

When OpenAI released Sora, a Vincentian video AI tool, on February 15, 2024, its video results amazed many. However, once the novelty wore off, the question arose: who will watch short, emotionless videos that lack a storyline? Similar to the metaverse, technologies that don’t address real-world needs or lack a stable business model eventually fade into hype. Sora, contrary to claims of advancing General AI, is a product of computing driven by heavy capital, lacking true technological innovation.

Technically, Sora’s foundation relies on innovations like the Transformer, Diffusion, and GAN models. But these breakthroughs are not unique to OpenAI. Their success stems from scaling algorithms, data, and computing power, reflecting the political economy effects of Moore’s and Metcalfe’s Laws. Big models rely on massive computing through high-performance GPUs processing massive data sets, with companies like Microsoft investing heavily in supercomputing infrastructure, such as tens of thousands of NVIDIA A100 chips, providing immense computing power for training models like ChatGPT.

The training of big models is energy- and capital-intensive, raising the question: do the benefits outweigh the costs? A cost-benefit analysis should consider overlooked externalities, such as environmental impact and systemic risks, which are borne by the public. While big models can boost productivity by automating tasks like content creation, diagnosis, research, and legal reviews, they also risk replacing human workers, especially when ordinary consumers and content creators lack influence over the technology’s deployment. Thus, AI is not just a technological issue but a public one, shaped by political, economic, and legal forces beyond technology itself.

Human labor is being devalued, reduced to auxiliary services for machines. The AI-generated content from tools like ChatGPT and Sora, which lacks emotion or a storyline, is often praised, while human-created work is criticized or ignored. This shift is influencing education and the future of humanity, with parents questioning the value of traditional education when many future jobs may not require human workers. While experts know this isn’t true, the industry’s promotion of AI as a solution may lead to a self-fulfilling prophecy. Teenagers might increasingly rely on AI, leading to a decline in the quality of human work, which could ultimately justify replacing humans with machines.

To avoid this downward spiral, AI education must include humanistic and social science perspectives, rather than solely following narratives set by industry giants. The public must understand that AI is not a neutral technology; it is embedded within political, economic, and legal structures. While AI can learn and evolve, it remains a tool designed to achieve human-defined goals. We cannot abandon the pursuit of purpose, or our future could be shaped by those who control AI, like Microsoft and OpenAI.

OpenAI, once a non-profit aiming to “create value for everyone,” has shifted toward a for-profit model after its 2019 decision to abandon its non-profit status. Despite its initial promises of openness, OpenAI’s focus on protecting intellectual property grew stronger, particularly after Microsoft’s $1 billion investment. Now, OpenAI is effectively a research division of Microsoft, which strengthens its monopoly in operating systems and productivity tools. Microsoft’s strategy of acquiring platforms like GitHub and integrating AI into its products, such as Office Copilot and Bing, ensures its continued dominance.

Monopolies can lead to arbitrary pricing and decreased service quality, harming consumers. Microsoft’s strategy of subsidizing users and later imposing higher prices and lower quality is a common pattern in digital markets. In such cases, public oversight and regulation are necessary to protect consumer welfare. This includes price regulation, minimum service standards, and data security requirements.

Institutional leadership is essential to ensure AI development aligns with human values. Some argue for abandoning the human-centered approach, envisioning a future where AI surpasses human intelligence. However, this view, akin to extreme ecological beliefs, is not widely accepted. A humanistic stance is necessary, where AI remains a tool that supports human activities and is developed with human needs at the forefront.

In the era of artificial intelligence, machines are increasingly taking over tasks that once required human intellect, leaving humans with work that relies more on instinct. This shift, driven by a blend of technical, political, and economic forces, reflects a desire to reduce labor costs. For example, in industries like takeaway and express delivery, AI-driven algorithms are now performing managerial tasks, optimizing routes and schedules for human laborers. This allows capitalists to replace expensive brain work with cheaper automation.

The true purpose of creating machines is not to replicate human beings, as there are already billions of people on Earth, but to assist in tasks that are repetitive, tiresome, or beyond human capacity. AI’s role is to enhance productivity, not to fulfill emotional or existential needs. Therefore, the goal of AI development should be to create tools that help us perform necessary but monotonous tasks or to do things that are difficult or inefficient without AI.

From a humanistic perspective, the current direction of generative AI, such as OpenAI’s tools, is misguided. Generative AI tools like ChatGPT and Sora replicate what human creators can already do but lack the contextual depth, purpose, and adaptability that human-created content offers. As a result, they often only serve to entertain or confuse, rather than contribute to meaningful, authentic, or rigorous content creation.

There are three primary models of digital economy regulation shaped by distinct political and economic systems: the U.S. market-driven model, which fosters innovation and supports winner-takes-all dynamics; the state-driven model of China, which balances development and stability; and the rights-based model of the European Union, which strives to protect human dignity, privacy, and autonomy. The competition among these digital powers plays out across two dimensions: horizontally, between countries, in terms of technology, business models, and norms; and vertically, between countries and enterprises, particularly concerning foreign versus domestic tech companies.

The global expansion of digital technologies, including AI, has led to the U.S. advocating for the free flow of data and AI deployment across borders, a strategy known as digital imperialism. This allows U.S. companies to dominate the global digital market. On the other hand, countries that lack powerful local digital giants, such as those in the European Union, emphasize data sovereignty and restrict cross-border data flows to protect personal data rights and limit foreign companies’ access to local data.

Meanwhile, China’s approach to AI regulation is walking a tightrope—balancing progress and stability while facing immense pressure. This delicate balance may be essential for AI regulation, as allowing the market to drive AI development could lead to exploitation by digital giants and exacerbate fears of runaway AI, as expressed by figures like Elon Musk.

However, maintaining an individual rights-based approach may stifle AI development, hindering the industry from progressing. In either case, the result could be exploitation, with digital giants like those in the U.S. reaping the benefits of AI without adequate oversight or regulation.

Source: softwarium, tech co, the job blog

Donald Trump Was Elected To Continue His Imaginary Second Revolution

Interview

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November 10, 2024

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Donald Trump Was Elected To Continue His Imaginary Second Revolution

Republican candidate Donald Trump declared an early victory on the morning of the 6th. Trump’s previous term was marked by unpredictable and controversial policies, both domestically and internationally. Once he returns to the White House, his brand of governance—dubbed the “Trump revolution”—will likely intensify. This raises questions: Could such a “revolution” reshape the U.S., or deepen its divisions? And how will social and economic powers influence this trajectory?

Zheng Yongnian, a prominent Chinese political economist and professor at the Chinese University of Hong Kong (Shenzhen), shared insights on the potential implications of Trump’s return..

Where does the current American ‘anger’ stem from, and what are the profound changes shaping the U.S. today?

Elections capture the core of U.S. politics, which are now deeply linked with global dynamics. American politics, shaped by decades of globalization, in turn, affects global developments. Today, nations view the U.S. through varied lenses, with reactions split along personal biases—some favoring Trump, others Harris. However, a shared concern is palpable, driven by what some term as the second revolution in the U.S., mirroring the transformative impact of its Independence War.

While Harris symbolizes continuity from an elite political tradition, Trump’s populist approach alarms many, especially given his promise of a Trump Revolution. This potential revolution signifies not violent upheaval, but radical policy shifts reshaping diverse interest groups.

Zheng identifies several groups, both domestic and international, deeply anxious about Trump’s potential return. Domestically, this includes political elites within both parties, marginalized social groups, and corporate leaders wary of his unpredictability. Internationally, close U.S. allies like Japan and South Korea, as well as global powers such as China and Russia, are concerned about possible isolationist policies.

Zheng draws parallels with historical revolutions, noting that unlike the French Revolution, driven by economic stagnation, the U.S. faces a crisis stemming from a thriving economy but misaligned governance structures. Figures like Elon Musk, supporting Trump, illustrate the divide between the economic base and outdated political systems. This “revolution” arises from dissonance between America’s economic forces and its political framework.

In Zheng’s view, the U.S. intelligentsia is largely detached from societal realities, clinging to ideals of democracy as the “end of history” without acknowledging the need for reform. This elite blindness echoes pre-Renaissance clerical defense of tradition. Today’s American revolution is not merely partisan but involves clashes between traditional and tech-driven industries, and between diverse social and racial groups.

So how has such a profound internal revolution for the United States changed its external policy?

As the world’s leading power, U.S. domestic shifts have substantial international effects. Internally, the U.S. has seen a “Trumpification” of its politics, where Trump’s influence permeates both major parties. While initially reshaping the Republican Party, Trump’s approach has gradually pushed the Democrats to adopt similar stances on key issues, such as tariffs and immigration.

In foreign policy, the U.S. prioritizes national interests under both administrations. Trump’s “America First” agenda and Biden’s “middle-class diplomacy” differ little in their focus on protective trade measures like tariffs. Immigration is another area where the Democrats are adjusting, reflecting broader public concerns, though Democrats maintain an emphasis on political correctness, covering issues like minority rights and climate change, where Trump diverges sharply.

On global cooperation, Trump’s exit from climate agreements contrasted with Biden’s re-engagement, but the commitment remains limited, as seen in the U.S.’s reduced climate actions amid the Russia-Ukraine conflict. Despite nuanced differences, the “Trumpification” of U.S. policies highlights a domestic and diplomatic convergence shaped by Trump’s legacy.

What do you make of the phenomenon where Trump is held in similar esteem to Reagan in recent Republican polls, especially considering his opposition to government corruption and alignment with anti-establishment sentiments?

The American spirit, often depicted in Hollywood’s hero narratives, has long celebrated figures who arise to meet societal needs. Figures like Reagan and Trump reflect this archetype, each arriving at critical junctures to appeal to citizens’ desires for decisive change. Reagan embodied a hero who tackled the era’s economic excesses through deregulation and tax cuts, championing globalization. Trump, by contrast, appeals to an anti-establishment, populist sentiment, opposing globalization’s outcomes, such as income inequality, that have alienated middle- and working-class Americans.

The fusion of labor and advanced technology interests in the U.S. today represents a synthesis unprecedented in American history. This restructuring reflects a new era where traditional political alignments of left and right are blurred. Trump’s brand of populism attempts to unify high-tech industry and labor, breaking with past political distinctions. This shift raises critical questions about the future of U.S. politics as AI and automation transform economic power dynamics.

Traditional Marxist ideas—where capital opposes labor—face challenges in explaining this alignment. With technological advances reducing the need for a large workforce, the emergence of a “pastoralist” social structure is possible, where economic elites support a reduced, “managed” labor class. This potential structure suggests that U.S. political reorganization is underpinned by profound economic shifts, where social structure, influenced by the economic base, shapes the political landscape. This reorientation highlights a moment in American society that defies traditional frameworks, suggesting that we are witnessing a unique transformation in U.S. socio-political structures.

Trump attempted to disrupt the U.S. foreign policy establishment during his first term but failed. With another chance at the White House, could he dismantle this establishment in his second term? If so, how would that impact the international order?

We’ve been examining U.S. internal dynamics, but it’s crucial to consider the international ripple effects as well. America’s allies, particularly those closely tied to the U.S., are the most concerned. Trump’s approach, including withdrawing from international treaties and offering limited support to allies, signaled a clear shift. Yet, even under Biden, with his Democratic platform, the dynamics of these alliances are not reverting to previous norms.

Historically, access to U.S. markets was a primary incentive for many allies. However, Biden’s focus on “middle-class diplomacy” does not involve significant market openings, even under initiatives like the Indo-Pacific Economic Framework, which lacks provisions for U.S. market access. This approach reflects a broader trend of economic protectionism and cautious immigration policies that address U.S. domestic priorities.

In the context of the Russia-Ukraine war, the U.S. support has largely translated to indirect costs for the EU, who bears much of the immediate impact, while the U.S. benefits economically, particularly in arms sales. This underscores a strategic shift where the U.S. appears less inclined to shoulder the costs of global leadership, focusing instead on pragmatic economic gains. Regardless of the administration—whether Trump or a future Democratic leader like Harris—the U.S. is likely to continue shrinking its international commitments, albeit with different rhetorical styles. Trump’s diplomacy is blunt, while Biden (or Harris) might maintain a more traditional, yet perhaps less transparent, diplomatic front.

The essence of U.S. foreign policy now seems increasingly rooted in pragmatism, as it balances domestic demands with scaled-back global engagement, leaving allies to recalibrate their expectations of American leadership.

Source: Guancha, CNews

Chinese Scientists Successfully Transform Corn into Clothing in Eight Years, Where Others Have Failed

East Asia

Tendenzblick

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November 9, 2024

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Chinese Scientists Successfully Transform Corn into Clothing in Eight Years, Where Others Have Failed

China is a powerhouse in the global amino acid market, producing approximately 60% of the world’s supply. Despite this significant contribution, the country grappled with challenges related to production efficiency and innovation, primarily stemming from underdeveloped microbial fermentation strains and a limited number of domestic patents.

Wen Tingyi, Principal Investigator at the Institute of Microbiology of the Chinese Academy of Sciences, has been pivotal in addressing these issues since joining the institute in November 2005.

Upon entering the institute, Wen quickly recognized that China was predominantly relying on traditional mutagenesis breeding techniques, which employed ultraviolet rays and chemical agents like diethyl sulfate (DES) to induce genetic mutations in microorganisms. This method was time-consuming and uncertain, requiring extensive screening to identify viable strains.

At the same time, foreign researchers were advancing rapidly with synthetic biology, allowing for precise gene editing at the DNA level. This technological gap motivated Wen to adopt gene editing techniques he learned abroad, aiming to create a platform for personalized strain transformation and innovation in industrial microorganisms.

Wen’s innovative approach involved creating a comprehensive network model of bacterial metabolic pathways by inputting all relevant genes into a computer system. This model enabled predictions about which genes needed transformation. By iteratively applying synthetic biology techniques—designing, building, testing, and learning—Wen and his team managed to increase the yield of production strains while minimizing unwanted byproducts.

In 2007, a company in Ningxia approached Wen, seeking assistance with their lysine production strain, which was yielding unsatisfactory results. The company, then a mid-level player in the domestic amino acid market, was looking to cut costs and boost profits. Utilizing the synthetic biology platform he had developed, Wen meticulously modified the strain through computer simulations, altering a total of 17 genes. This process dramatically improved the sugar-acid conversion rate and output, elevating the company’s production capabilities to international standards.

However, the landscape shifted once again. In 2005, lysine prices were around 30,000 yuan per ton, but by 2020, excess production capacity had surged, driving prices down to as low as 5,400 yuan per ton. This decline significantly impacted profit margins, leaving many companies struggling to remain viable.

Amid these challenges, Wen had a revelation. He discovered that by removing a carboxyl group from lysine, it could be transformed into 1,5-pentanediamine, a key precursor for nylon production, particularly in high-demand markets. The historical context of nylon production is notable; DuPont’s development of nylon involved 5-carbon pentamethylenediamine, later switching to a more cost-effective 6-carbon variant—hexamethylenediamine. This shift underscored the need for an alternative pathway for producing pentamethylenediamine that would not be hindered by foreign monopolies on the essential precursor, adiponitrile.

In 2021, the global nylon market surpassed 10 million tons, valued at approximately 1.5 to 1.8 trillion yuan, yet more than 90% of production was dominated by nylon 6 and nylon 66, with the latter’s precursor being largely controlled by international corporations. This left Chinese manufacturers at a disadvantage, primarily receiving only a fraction of the profits.

To tackle this issue, Wen decided to use E. coli as a production strain due to its rapid reproduction cycle of just 17 minutes, complete genetic information, and established metabolic pathways. However, E. coli inherently lacked the ability to utilize lysine for synthesizing pentamethylenediamine. Therefore, the first step was to genetically modify E. coli to incorporate foreign genes, enabling it to synthesize the desired compound.

The project faced additional challenges when it became apparent that pentamethylenediamine was cytotoxic to E. coli, inhibiting its growth once a certain concentration was reached. To overcome this, the team engineered a transport pump to expel pentamethylenediamine from the cells, allowing E. coli to thrive while continuously producing the compound.

After numerous experiments and refinements, the output of pentamethylenediamine reached world-leading levels, with nearly 100% conversion of lysine to pentamethylenediamine. Purification processes yielded a product with over 99% purity, making it suitable for industrial applications. The successful laboratory results led to plans for pilot production.

Initially, the laboratory utilized a rotary evaporator with a capacity of 5 to 20 liters, correlating to fermentation liquids produced by a 50-liter fermentation tank. However, scaling up to commercial production required significantly larger fermentation systems, presenting challenges in cost and energy efficiency. Over three years of intensive development reduced the pilot production cost of pentamethylenediamine from over 90,000 yuan to about 20,000 yuan.

By August 2020, the project culminated in the establishment of the world’s first 10,000-ton pentamethylenediamine production line in Daqing City, Heilongjiang Province. This facility utilized a distillation tower, drastically lowering production costs and improving efficiency. Following this, the team successfully polymerized pentamethylenediamine into nylon 56, producing both long and short fibers suitable for various textile applications.

Nylon 56 boasts several advantages over nylon 66, including enhanced moisture retention, ease of dyeing, flame resistance, and improved wear resistance. The resulting fabric is soft, cool to wear, and exhibits superior performance, making it ideal for activewear, underwear, and protective clothing. Collaborative ventures with leading brands have further solidified nylon 56’s market position, paving the way for its adoption in high-end products.

As demand for bio-based materials rises, Wen Tingyi’s work exemplifies a significant shift in sustainable manufacturing. The journey from corn to clothing symbolizes a broader movement towards bio-based nylon production, setting China on a path distinct from traditional petroleum-based nylon production. This innovative approach not only addresses local industry challenges but also enhances China’s competitive edge in the global market, positioning the country as a leader in sustainable textile solutions.

Source: zshq, jiemian, biotechnologyforbiofuels

China Proposes 13 Fertility Support Measures

Uncategorized

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November 8, 2024

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China Proposes 13 Fertility Support Measures

The results of China’s seventh national census indicate that the total fertility rate (TFR) for women of childbearing age in my country was just 1.3 in 2020, reflecting a concerningly low level.

The TFR represents the average number of children born to each couple, with an international benchmark of 2.1 for generational replacement. This figure accounts for mortality risk, indicating that couples need to have about 2.1 children to maintain population levels.

A TFR of around 1.5 is viewed as a critical threshold; falling below this level raises the risk of entering a low fertility trap. While updated data has yet to be released, experts predict that the TFR may have declined further. This sustained low fertility rate contributes to a declining population and an aging demographic, undermining economic and social development potential.

Du Peng, Dean of School of Population and Health, and Director, Institute of Gerontology of Renmin University of China, emphasizes that recent birth statistics suggest the TFR is now even lower than in 2020, indicating an extreme decline. If this trend persists, it will have long-lasting effects on society, including a reduced birth cohort that exacerbates negative population growth.

The shrinking population will influence future educational needs, labor supply, and the distribution of social resources. Moreover, while the willingness to have children remains higher than the current TFR, many families face challenges related to childbirth, child-rearing, and education, indicating that the TFR does not accurately reflect societal intentions regarding childbearing.

To assist families wishing to have one or two children, it is essential to cultivate a fertility-friendly environment that genuinely reduces the costs of childbirth, child-rearing, and education. This support is vital for stabilizing and potentially increasing the TFR, which is crucial for the social and economic development of the country.

Since implementing the universal two-child policy in 2016, followed by the three-child policy in 2021, the Chinese government has been actively promoting fertility support measures to enhance reproductive health and prenatal care services. A preliminary system of fertility support policies has been established. According to officials from China’s National Health Commission, provinces typically offer over 60 days of extended maternity leave, approximately 15 days of spouse maternity leave, and 5 to 20 days of parental leave, with maternity leave extended to over 158 days in all provinces.

Additionally, the country’s capacity for preventing birth defects has improved significantly. National rates for pre-pregnancy examinations and prenatal screenings now exceed 90%, with screening for neonatal genetic disorders and hearing impairments reaching over 98%. The optimization of fertility policies extends beyond service enhancements to economic support as well.

In January 2022, the government began including care for children under three in personal income tax deductions. In 2023, the deduction standard increased from 1,000 yuan to 2,000 yuan per child per month, benefiting many families with young children.

In August 2022, the National Health Commission, alongside 17 other departments, issued guiding opinions to focus on optimizing the maternity leave system, enhancing hospitalization and delivery conditions, and expanding labor analgesia options.

On October 28, the General Office of the State Council released the Several Measures for Accelerating Improvement of Reproduction Policy Support Systems and Promoting the Establishment of a Reproduction-friendly Society.

These measures propose a comprehensive approach to fertility support through four key areas:

Strengthening Fertility Services: Enhancing maternity insurance coverage to include flexible workers, migrant workers, and new employment forms, ensuring that maternity and paternity leave are fully implemented, and establishing a maternity subsidy system. Local governments are encouraged to improve reproductive health services and include appropriate labor analgesia and assisted reproductive technologies in medical insurance.

Enhancing Childcare Services: Improving children’s medical services and incorporating eligible children’s medications into medical insurance. Increasing the availability of inclusive childcare services and supporting diverse childcare models, while also enhancing policies to provide operational subsidies for inclusive child care institutions.

Supporting Education, Housing, and Employment: Expanding access to quality educational resources, encouraging after-school services and social projects, and implementing policies to support multi-child families in housing and employment, including flexible work arrangements.

Creating a Fertility-Friendly Social Atmosphere: Promoting a new culture of marriage and childbearing that emphasizes positive views on family life, enhancing public awareness of high-quality population development, and integrating education on national population policies into school curricula.

The Measures stress the importance of improving political commitment and responsibility among all stakeholders, including governments, employers, and individuals, to ensure the effective implementation of fertility support policies.

Source: Xinhua, CCTV13, CGTN, guandian

Can trade secrets become an alternative means of intellectual property protection in the AI era?

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November 7, 2024

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Can trade secrets become an alternative means of intellectual property protection in the AI era?

With generative AI technology advancing, the industry faces new challenges to the intellectual property system, from AI algorithm patentability and copyright implications of AI-assisted creations to AI’s role as a potential patent inventor and the handling of vast commercially valuable data generated by large models.

These developments heavily impact traditional IP protections. Trade secrets, a defensive IP right, bypass statutory authorization and the restrictive requirements of patents and copyrights, potentially offering a natural protection barrier for AI technology and applications.

Unique Trade Secret Challenges of Generative AI

Generative AI learns patterns from data to generate new outputs, using iterative training to improve accuracy. This process relies on algorithms and big data to conduct inductive reasoning, find rules, make predictions, and deliver results.

Data and algorithms are critical for accurate outputs, especially the weights generated during training, but they pose challenges for traditional copyright protection due to disputes over their status as copyrightable expressions. These elements, hidden in the model’s “black box,” align closely with trade secret confidentiality requirements.

In practice, users create new content by inputting prompts, which generative AI uses to predict results. If the input includes trade secrets, AI providers may inadvertently access these secrets. For example, Samsung faced a data breach when an employee used ChatGPT for work purposes, and Cyber Haven found that 11% of employee-pasted data into ChatGPT was confidential. Consequently, companies using generative AI are increasingly focused on protecting their trade secrets.

Given these issues, this article will analyze trade secret protection in AI research, development, and application from the perspectives of both AI technology providers and users.

Protecting Trade Secrets in AI Technology

Trade secrets are defined as technical, business, and commercial information not publicly known, holding commercial value and safeguarded by the right holder. To claim a trade secret, the right holder must show that the information is non-public, commercially valuable, and subject to reasonable confidentiality measures.

Generative AI often relies on data like public works, personal data, and trade secrets, assuming legal acquisition of training data. This article evaluates whether the data created through generative AI development, including model training and algorithm adjustments, qualifies for trade secret protection.

Generative AI development involves raw, labeled, and weighted data, mostly derived from public sources like books, academic papers, and media. While raw data is public and thus non-confidential, processed training data, weights, and other enterprise-handled data may qualify as trade secrets if confidentiality is maintained. However, trade secrets are vulnerable; any leakage undermines their value.

Moreover, right holders face challenges in defining the distinctive and non-public aspects and proving the information’s proprietary nature, particularly for large data sets where comparison is complex. To mitigate these vulnerabilities, data ownership rights may offer alternative protections.

Large AI models often build on open-source projects. Open-source code lacks trade secret protection due to public access, but modifications made by the enterprise may qualify if they remain confidential. However, certain open-source licenses require disclosure of derivative works, potentially complicating a company’s IP strategy. To avoid conflicts, R&D entities should review open-source license obligations carefully before using such models.

Algorithms, defined as rules for transforming input into output, may not qualify for copyright or patent protections, as they fall under intellectual activity methods. However, algorithm trade secrets face a unique challenge: transparency requirements. Regulatory frameworks like China’s Personal Information Protection Law, the EU’s AI Act, and the U.S. NIST’s Four Principles of Explainable AI require AI providers to explain their decision-making logic without full disclosure of proprietary details. China’s first algorithm trade secret case highlighted that even publicly known algorithms may be trade secrets if the enterprise has developed distinctive methods, such as unique settings and weights, that are commercially valuable and not publicly known.

Trade Secret Protection in AI Application Processes

When artificial intelligence processes user input containing trade secrets, it may generate content that builds on this input, potentially embodying trade secrets. Some argue that AI could even create trade secrets independently. Since AI service providers might access input data for model improvements, input content containing trade secrets risks exposure. Likewise, if output content with trade secrets is shared online, network security concerns may also pose a risk.

Despite these risks, AI’s efficiency gains make it essential to enterprise competitiveness, prompting businesses to pursue compliant, secure applications of AI. Enterprises should create comprehensive solutions addressing both input and output content handling, with special attention to personnel and systems involved in data flow. Determining if AI-generated content meets trade secret criteria is crucial.

In line with reasonable measures for trade secret protection, enterprises could adopt several strategies:

1. Using localized or internally deployed AI systems enables control over storage, processing, and generation within a secure, private cloud. Measures like data isolation, permission controls, and download restrictions enhance content confidentiality.

2. Guidance and training on compliant AI use are essential, especially as private deployment can be costly and limit real-time model updates. Training should cover trade secret scope, protection methods, risks, and benefits, detailing work content, desensitization, and storage practices as permitted.

3. Updating confidentiality clauses in procurement contracts ensures AI-specific terms are included. These should clarify input/output information’s confidentiality, ownership, and purpose restrictions, prohibiting use for model training, and define network security measures for storage, processing, and deletion.

4. Other technical measures, such as custom trade secret filtering tools, could be implemented to screen content before AI processing, offering an added layer of protection for enterprises with stringent confidentiality needs.

Source: Linkedin, Medium