By Aditya Sinha & Aasheerwad Dwivedi,
In 1980, a small, nondescript garage in Palo Alto became the birthplace of what would eventually transform into Silicon Valley. This unassuming location housed two Stanford graduates who tinkered with circuit boards and computer chips, fuelled by their vision of a digital future. Their company, Hewlett-Packard, would soon become a tech giant, setting the stage for a wave of innovation that drew in engineers, scientists, and entrepreneurs from around the world.
As word spread of the groundbreaking work happening in Silicon Valley, the area became a magnet for talent and investment. Start-ups flourished, venture capitalists invested billions, and top-tier universities like Stanford and Berkeley churned out skilled graduates eager to join the tech revolution. This agglomeration of innovation created a self-sustaining ecosystem where ideas could be rapidly developed, tested, and brought to market.
Fast forward to today, and we see a similar agglomeration occurring in China, particularly in the field of generative AI. Chinese companies and research institutions have become global leaders, amassing a substantial number of patents in this cutting-edge field.
In July 2024, the World Intellectual Property Organization unveiled its Patent Landscape Report on Generative Artificial Intelligence (GenAI), revealing a monumental wave of innovation. Between 2014 and 2023, an astonishing 54,000 GenAI-related inventions (patent families) were filed, accompanied by over 75,000 scientific publications. The top 10 GenAI patent applicants are spearheaded by Tencent with 2,074 inventions, followed closely by Ping An Insurance with 1,564, Baidu with 1,234, the Chinese Academy of Sciences with 607, IBM with 601, Alibaba Group with 571, Samsung Electronics with 468, Alphabet with 443, ByteDance with 418, and Microsoft with 377. Out of these 10 highest patent filers, six are Chinese.
China’s dominance in this field is nothing short of staggering. With a commanding 38,210 GenAI inventions, China outpaces the United States, which only boasts 6,276 inventions. The Republic of Korea, Japan, and India trail even further behind with 4,155, 3,409, and 1,350 inventions respectively.
Chinese universities have achieved dominance in GenAI patent filings, with the Chinese Academy of Sciences leading the pack with nearly 600 patents. Tsinghua University and Zhejiang University follow closely, showcasing substantial contributions with over 400 and 300 patents respectively. Besides, institutions like Zhejiang University of Technology and the National Research Council of Science and Technology of the Republic of Korea are prominent. Despite this intense competition, no Indian university has made it to the top 20 list.
Chinese regulations have significantly boosted AI innovation by being among the first to legislate on GenAI shortly after ChatGPT’s launch. Initially, China implemented separate regulations for different AI products, with distinct rules for algorithmic recommendation services and deepfakes. However, in January, the ministry of industry issued draft guidelines to standardise the industry, with plans to establish over 50 national and industry-wide AI standards by 2026. The regulatory framework is crucial for emerging technologies as it provides clear guidelines, promotes uniformity, and ensures a conducive environment.
But what made China a dominant player in emerging tech, especially GenAI? First, the government has proactively fostered AI development through strategic planning and significant investments. Initiatives such as the “Next Generation Artificial Intelligence Development Plan” have laid out comprehensive road maps for AI advancement, emphasising the importance of GenAI. Additionally, regulatory measures have been fine-tuned to balance innovation and control, creating a conducive environment for AI growth.
Second, it is often said that innovation usually thrives in the absence of regulations. But the inverse can also be true. Regulatory frameworks are paramount in catalysing innovation, particularly in burgeoning fields like AI. Studies show well-designed regulations provide a structured environment, mitigating uncertainties and fostering a stable climate conducive to innovation. Porter and van der Linde (1995) suggest stringent yet flexible regulations can drive innovation by pushing firms to adopt more efficient technologies and processes. This “innovation offsets” hypothesis is backed by empirical studies demonstrating that clear regulatory standards reduce compliance costs and uncertainty. Blind (2012) highlights that regulatory clarity and consistency are essential for innovation, as they offer a predictable legal landscape and facilitate the standardisation of technologies.
Third, China has developed substantial AI infrastructure, including high-performance computing resources and extensive data-sharing platforms. Leading firms like Alibaba, Baidu, and Huawei have leveraged their robust cloud computing capabilities to support AI R&D.
Fourth, the AI sector in China benefits from a thriving ecosystem that includes a large number of start-ups, tech giants, and academic institutions. Substantial venture capital investments and government funding support this ecosystem.
Fifth, China has developed a large, skilled workforce in AI and related fields. It produces many AI researchers and engineers through its education system, emphasising STEM (science, technology, engineering, and mathematics) disciplines. Additionally, China has been successful in attracting international talent and collaborating with global AI experts.
Sixth, China’s advancements in AI-specific hardware, particularly graphic processing units and AI accelerators, have been substantial due to domestic innovation, government support, and strategic adaptation to global challenges. Companies like Huawei, Biren Technologies, and Alibaba have developed powerful chips such as Huawei’s Ascend series and Alibaba’s Hanguang 800. Specialised firms’ technologies have created custom AI accelerators for applications ranging from cloud computing to autonomous driving. State-backed initiatives, including substantial funding and policies under the “Made in China 2025” plan, have bolstered these efforts, fostering innovation and scaling up production capabilities.
India should take cues from China. To build a robust AI ecosystem, India should follow a multi-faceted approach: develop comprehensive AI strategies with significant government investment in a few centres of excellence which solely deal with AI, establish clear and flexible regulatory frameworks to foster innovation, and invest in high-performance computing infrastructure. Supporting a vibrant AI ecosystem involves backing start-ups, tech giants, and academic institutions with venture capital and government funding. We need to prioritise STEM education to cultivate a skilled workforce. This also requires rethinking the curriculum, especially in higher education institutions.
Author Aditya Sinha is OSD, research, EAC-PM, and author Aasheerwad Dwivedi is assistant professor, FMS, University of Delhi.
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