Summary

China

China's rapid advancement in the field of artificial intelligence (AI) has garnered significant attention worldwide. Despite geopolitical rivalries and debates over technological supremacy, it is essential to analyze China's AI development objectively. Two key drivers have shaped China's AI sector: global resource scarcity and a whole-of-government approach. This article explores these drivers, current regulatory efforts, unresolved challenges, trends in AI development, and the key players contributing to China's AI landscape. There is also much less AI doomism in China. Why?

India

India, known for its booming startup ecosystem, is actively participating in the global race of AI development. However, there are concerns about whether India's contribution to the AI sphere has materialized significantly. Despite having over 1500 AI-based startups with billions of dollars in funding, India is still considered to be falling behind in the global AI innovation race. Is it because of the “Shiny Object Syndrome”?

The UK

The UK government is actively positioning itself as a global AI leader by 2030 and is taking steps to welcome AI companies. OpenAI has chosen London as its first foreign office, reflecting the UK's efforts in this area. The government's investment in AI, including funding initiatives and infrastructure development, is aimed at boosting the economy and increasing productivity. As in many battles before that, you can hear Britain saying, “The UK will stand together with our allies to lead the way.”

China

AI battle between China and the US has been a topic for a long time. It's worth remembering AI Superpowers: China, Silicon Valley, and the New World Order, the book written in 2018 by Kai-Fu Lee. But the end of 2022 and the glorious marsh of generative AI changed the balance of power and it’s important to learn what is the current state of AI in China.

China's growing focus on AI, coupled with its significant investment and numerous AI publications, positions it as a key player in the field. To provide an unbiased analysis of China's advancements, this report incorporates both Chinese and English language sources. By offering a comprehensive understanding of the PRC's progress and contributions to AI, our goal is to present readers with a fresh and holistic perspective that goes beyond conventional comparative analysis.

China’s Political-Economy: Dreams of Self-Reliance, Realities of Globalization

Two key drivers stand out in China’s AI development: One global, and one domestic.

The first, global driver defining the state of China’s AI is insufficient resources and an excessive dependence on the global supply chain. COVID-induced supply chain disruptions and their knock-on effects have highlighted China’s desperation for everything related to AI development. From human capital for research and development to essential components like semiconductors and a coordinated push to control access to rare earth metals, China’s attempts to address and leverage scarce resources will continue to define her AI sector. Moreover, the relentless, international pursuit for supremacy in AI will only further aggravate China’s underlying scarcities, as other nations are likely to continue employing zero-sum economic controls to further undermine China’s already limited access to essential AI resources.

The second, domestic driver key to understanding China’s AI sector lies in her political, whole-of-government approach. China’s unique political and economic system, known as Socialism with Chinese Characteristics, allows for an integrated approach to AI, not limited by Western ideas of the rule of law or anti-trust legislation. Through state-owned enterprises (SOEs), military, and academic institutions, China’s one-party system uses military-civil fusion to give comprehensive prioritization to the development of AI technology – this both quicken its development and helps address the above-mentioned issues of scarcity. Unlike other countries that can only enact weak, term-limited legislation to temporarily support critical industries, the Chinese system’s dedication to Five-Year Plans is not limited by discontinuous terms or bound by opposing political parties. Plans can thereby compound upon one another, and institutions can coordinate with each other to work toward one national goal: Become a global AI leader by 2030.

A recent example illustrating this reality is China’s Dual Circulation "development paradigm." Introduced in response to the vulnerabilities exposed by the COVID-19 pandemic, this strategy aims to boost domestic demand, foster innovative capacity, and reduce reliance on foreign markets – effectively demonstrating how quick and capable the Chinese Communist Party (CCP) is at manufacturing industrial solutions to address structural scarcities. While it is still unclear whether China will be able to disentangle itself from AI’s incredibly globalized supply chains, signs of both success (or lack thereof) frequently emerge within this sector, due to its high priority among CCP bureaucrats and positioning as a newer, more exposed sector within the global economy.

Existing challenges

Pretty much everything about China LLMs today looks like mostly big talk and announcements (especially in their hopes for LLM industry application) but little action, as few can or have been able to make as big of a splash as ChatGPT. You'll notice that most either have invitation-based testing or that users must qualify for testing of the product. Could this have to do with the heavy degree of censorship in China? Are companies running a serious risk if they do not smooth out political kinks before releasing this technology to the public? For example, many of these LLMs are probably being trained with language that is either 1) not from within the PRC (and thus not filtered by the great firewall) or 2) language/data from before the large-scale implementation of the great firewall). How do you train an LLM to ignore politically sensitive questions about China's ethnic minorities, unseemly anti-government demonstrations, political controversies, or the blatant historical revisionism that occurs in China? Then how do LLM trainers ensure that the answers spit out by these LLMs are politically correct – not only in Chinese but in all applied languages? I'm afraid that these issues and all-around slow release to the general public will only exacerbate the existing issues of adoption, recognition, and efficiency of China's domestic LLMs. Worse yet, the question still remains: Can anyone really catch up with ChatGPT 4? According to a few published announcements, most Chinese are only trying to compete with ChatGPT 3.

Further exacerbating development are hardware issues. Pan Helin, Joint Director and Researcher of the Digital Economy and Financial Innovation Research Center at Zhejiang University International Business School said, "There is currently a gap in the AIGC (Artificial Intelligence General Chip) in China. The demand is there, but the products are not. Therefore, it is the right strategy for major manufacturers to seize the opportunity and enter the AIGC market."

Current Trends in AI

Q1 2023: If you can’t beat them, join them... (Then regulate them from within)

Q1 2023: January 2023

Unsurprisingly, most of China’s billionaires are C-suite executives for tech or tech-adjacent companies. Mysterious disappearances of these business tycoons (like Xiao Jianhua, Jack Ma, Ye Jianming, Bao Fan, etc.) are not unheard of in China and have been covered extensively by Western media. In January, a notable shift in Beijing’s approach became apparent. With China approaching the second and third phases of its national objective to “make breakthroughs [in AI] by 2025” written in 2018, and “establish China as the world leader in AI by 2030,” there has been an increased sense of urgency to meet those deadlines. Instead of merely making influential technologists vanish, the CCP announced in January, that it would be acquiring stakes in two major tech firms, Alibaba and Tencent, by using a special government mechanism, often referred to as “golden shares.” While these “stakes are sometimes very small, [...] they tend to give the government board seats, voting power and sway over business decisions.” This change signals a departure from coercive disappearing acts and instead allows the CCP to places its voices in tech boardrooms and hands within AI steering committees, providing a more direct influence – likely in hopes of achieving their national goals in both a timely manner and according to their own standards. It was particularly interesting to find that “Top Ten Institutions in the World by Number of AI Publications in Natural Language Processing and Speech Recognition 2021” the only two Chinese institutions found in these lists not under the direct control of the CCP were Alibaba and Tencent. It goes without saying these “golden shares” have effectively reigned them in.

February 2023

Biren and Denglin Technology join other Chinese startups in an attempt to circumvent US-led restrictions and fill the market void left by controls that have left high-end GPUs like the A100 Tensor Core GPU, upcoming H100, along with the variety of systems that incorporate them, inaccessible. China, facing restrictions on chip manufacturing technology from the US, Japan, the Netherlands, and potentially the EU, Biren has chosen to focus on general-purpose GPUs (GPGPUs) and to prioritize AI breakthroughs. Denglin’s focus on the other hand, used the Tensor engine and programmable GPGPU engine to help develop China’s first cloud-based AI computing platform with GPU as its core technology. These advancements signify a new route to commercializing GPGPU products in China, while tactfully circumventing foreign sanctions.

March 2023

Baidu, often regarded as China’s equivalent of “Google” and a prominent search engine and artificial intelligence company, unveiled Ernie Bot, an AI-powered LLM, to the public. However, the launch fell short of expectations due to a lack of real-time demonstration and the limitation that only a small trial group could access it. Despite the underwhelming debut of Ernie Bot and the subsequent decline in Baidu’s stock price, Baidu went on to set up a 1 billion yuan ($145 million) venture capital fund specifically for startups developing artificial intelligence applications later that month.

Gunning for ever-higher frequency networks, higher capacity, and lower latency, “China Unicom, China’s third-largest wireless network operator” announced that it “expects to complete technical research and launch early applications for 6G technology by 2025.” Investors, perhaps anticipating this announcement, saw China Mobile Ltd. (China’s first-largest wireless operator) become the third-largest stock listed onshore after a trading frenzy driven by AI bets and the government’s 6G ambitions. From GPUs to GPGPUs, to 6G, even before Q1 ended this year, it is becoming increasingly evident that China’s people, investors, and most-importantly government are placing a huge bet on being able to provide both the infrastructure and breakthroughs needed to both achieve its national goals of becoming a global AI leader while achieving self-reliance. Both have difficult goals on their own. But achieving both at the same time? Truly a huge bet.

Q2 2023: April 2023

Qihoo 360 (full name 360 Security Technology Inc.) announces the launch of the chatbot 360 Zhinao 4.0 LLM. Users must qualify for testing, but the firm hopes to integrate with browsers, digital assistants, intelligent marketing, and other application scenarios to enhance user productivity and creativity.

SenseTime, a leading AI startup, announces the launch of their "SenseNova" foundational model sets and declares advancing Artificial General Intelligence (AGI) with the strategy of "big model + large computing power." SenseChat is SenseTime's own LLM and is equipped with capabilities for natural language processing, content generation, automated data annotation, custom model training, reading and comprehending lengthy PDF files, and coding. Furthermore, it supports innovative applications including assisting developers in coding and debugging more efficiently, providing personalized medical advice to users, and extracting and summarizing information from complex documents.

Beijing KunLun Wanwei Technologies, a Chinese web and gaming company, announces their launch of Tiangong 3.5 LLM through the Chinese AI startup Qidian Zhuyuan. KunLun Wanwei will provide hardware support for Qidian Zhuyuan, and will begin invitation-based user testing on April 17th. It claims to be China's first domestically developed LLM to achieve "intelligent emergence."

Baichuan-Inc, an AI venture set up by the founder of the search engine Sogou, Wang Xiaochuan, unveiled a large language model called baichuan-7B. Aims to be the Chinese version of OpenAI's ChatGPT LLM and be a disruptive force in higher-level applications.

At Alibaba Cloud Summit, Zhang Yong, CEO of Alibaba Group and Alibaba Cloud Intelligence, unveils a proprietary LLM “Tongyi Qianwen” and announces that all Alibaba products will soon be integrated with it. User testing and experience invitations began on April 7th.

On the same day, the Cyberspace Administration of China (CAC) announced draft measures for managing generative AI services. These measures hold providers accountable for the accuracy of data used to train generative AI tools. Additionally, companies will need to undergo security assessments before releasing their AI tools to the public. The CAC emphasized that any content generated by generative AI must align with the country's core socialist values.

May 2023

iFLYTEK has launched its natural language processing (NLP) model "Xinghuo". Apart from a video presentation, there isn't much information available about this “potential rival” to ChatGPT.

June 2023

Baidu introduced its Ernie Bot and has already developed 11 Wenxin industry LLMs, covering fields such as power, gas, finance, aerospace, media, urban development, film and television, manufacturing, and social sciences.

Baidu claims that its Ernie 3.5 model has outperformed OpenAI's GPT-3.5 in general abilities and Chinese-language capabilities, surpassing even the more advanced GPT-4.

China is home to at least 79 large AI models with more than 1 billion parameters, most of them focusing on language and visual recognition, according to a recent report published by the Institute of Scientific and Technical Information of China, a government research agency.

Conclusion/Key Takeaways

The mentioned tensions, which include changing global perceptions of China’s ability to develop advanced technologies, China’s corresponding domestic posture, and concerns surrounding her ability to acquire AI end-use technology, will undoubtedly continue to shape the landscape in which this sector’s progress unfolds.

But while Western media has generally portrayed the US-led coalition's efforts to hinder China's access to advanced chips to be a step in the right geopolitical direction, I find it unlikely many DC strategists foresaw China's remarkable resilience and adaptability in response to this challenge.

Structural constraints like export controls and sanctions, while slowing China’s development in the field, have not stymied innovation. Instead of bemoaning their inability to import sophisticated chips, Chinese innovators recognize it merely as a structural change and work to reassess and adapt to their new constraints.

I think this reflects a cultural point that Azeem Azhar made in Exponential View. Azhar was surprised that East Asians, particularly the Chinese, do not espouse any of the AI fatalism that has gripped both the Western corporate suites and the general public.

The AI fatalism gripping the West today is a product of the inherent and incessant sense of opposition inherited through our myth and literature. This is not to say the Chinese have no sense of opposition, but rather their myth, literature, and culture emphasize how to create harmony out of the nature they are part of, rather than conquering the nature of which they are not part. Think about it: Western myth and literature often depict man in conflict with nature, God, and even against his own kin even before Genesis ends! Confucianism, Daoism, and Buddhism on the other hand emphasize the creating harmony aspect within society, nature, and oneself respectively – thus the lack of fatalism in the East.

We can see governance in China attempting to create harmony even today with its slew of AI-related legislature. It will be interesting to see if these controls create any harmony for the innovation going forward in Q3, and whether or not it will help carve out a safer sector for AI to grow in going forward. It will also be interesting to see how Q3 develops as more LLMs get rolled out – especially as they’re marketed to China’s corporate sector. Whether or not they will be able to be monetized, real monetization of LLMs will probably happen in China before other countries thanks to its relatively mature legal environment and aims toward business application/voice assistant implementation, as opposed to general public services.

Written by Anthony Edwards

India

At a recent event in India, Rajan Anandan, a former Vice President of Google in India and South East Asia and current venture capitalist, inquired OpenAI’s CEO Sam Altman about India's potential to develop a tool like ChatGPT. Explaining the dynamics at play Altman suggested, it would be challenging for Indian companies to compete with OpenAI on training foundation models. While Sam Altman's perspective is respected due to his extensive work in AI, India's tech scene doesn't view his caution as a limiting factor. "He certainly doesn't have an understanding of India's capabilities in AI," said Minister of State for IT, Rajeev Chandrasekhar.

As for the capabilities: India garnered substantial investments in 2022, as per the Stanford AI Index report. Ranking fifth globally, India surpassed formidable competitors like South Korea, Germany, Canada, and Australia, and attracted a noteworthy total investment of $3.24 billion, as reported by the National Association of Software and Service Companies (NASSCOM). In addition to its impressive investment figures, India boasts the second-largest talent pool for AI and ML on a global scale.

Responding to Altman, C.P. Gurnani, CEO of a leading Indian IT company Tech Mahindra, wrote on Twitter, "OpenAI founder Sam Altman said it’s pretty hopeless for Indian companies to try and compete with them. Dear @sama, From one CEO to another.. CHALLENGE ACCEPTED." Later, Altman clarified that his words were taken out of context.

Amid this global race, India remains dominated by AI behemoths such as OpenAI’s ChatGPT, Google Ventures–backed Anthropic, or Google’s Bard. It is worth noting that ChatGPT supports Hindi and other Indian vernacular languages such as Assamese, Kannada, Tamil, Telugu, and others which surely gave a major boost to ChatGPT’s usage in the Indian market.

Despite the existence of more than 1500 AI-based startups in India, with over $4 billion in funding, analysts suggest that India is still falling behind in the global AI innovation race.

Existing Challenges – Shiny Object Syndrome

Notably, the Indian IT which is currently wooed by generative AI seems to have a major shiny object syndrome. Since last year, the industry was betting big on Mark Zuckerberg’s darling project: the metaverse. The virtual reality dream led to a paradigm shift in the industry.

Since Facebook rebranded itself as Meta in 2021, with a $10 billion commitment, Indian IT had been hyperventilating over the virtual platform. India was expected to touch $1.1 billion by 2023 at a CAGR of 57 percent, according to a white paper released in March 2023.

In a very short amount of time, they had to change their focus completely.

Tata Consultancy Services (TCS) announced 60 metaverse projects globally. On the contrary, during its FY23 earnings announcement, the lead service provider said that it has seen an increase in interest among clients in generative AI. The company's Chief Operating Officer Ganapathy Subramaniam said that TCS has already started integrating generative AI into its portfolio of services.

During the fiscal 2023 earnings call, Infosys’ Chief Executive also stated the company's commitment to generative AI platforms.

Even though Tech Mahindra seemed to concentrate on metaverse last year (launching a Metaverse Virtual Lounge, Open Banking Sandbox environment, and several digital platforms, including 'TechMVerse), this year it’s going all-in on AI with the launch of its generative AI studio earlier in June.

As per the Stanford AI Index Report, 2023, Indian companies received $3.24 Bn in funding in 2022, securing India the fifth spot among the countries that received the most investments in AI. As India's mature startup ecosystem largely remains on the sidelines of the generative AI race, emerging startups are rising to the challenge.

Firms such as Gan, which enables large-scale video repurposing for businesses, and TrueFoundry, aiding in the construction of ChatGPT with proprietary data, are part of this new wave of companies spearheading the charge in India's AI landscape.

Among the startups that raised funding in 2022, Chennai-based conversational AI startup Uniphore raised $400 million in a Series E Round taking its valuation to $2.5 billion. Among 2023’s biggest fundraises there is US-based AI startup (but with Indian roots) Mad Street Den, which raised $30 million in a Series C round led by Avatar Growth Capital.

Several Indian organizations, including Zoho, GupShup, and Exotel have unveiled systems for building models akin to ChatGPT powered by GPT models.

All is Quiet On The Regulation Front

Currently, regulating emerging technology does not appear to be the primary priority. Rajeev Chandrasekhar, in his statement to the Parliament on April 5, 2023, acknowledged the evolving nature of generative AI and the absence of specific regulations at present.

In India, the government possesses the authority to collect and utilize data from its citizens, much like a librarian's sole authority to gather, manage, and loan out books. Additionally, the government has the power to establish rules for private entities. These powers raise significant questions about the necessary safety measures and rights for private parties and individual citizens. Policymakers are beginning to recognize the possibilities and dangers of AI, treating it like a shiny new toy. However, to create sensible rules that align with the constitution, a deep understanding of this new 'toy' - AI technology - is absolutely essential.

With India heading into an election year, the absence of regulations is concerning, considering the potential misuse of AI for spreading targeted misinformation.

India is currently in the process of reviewing how to regulate AI through the upcoming Digital Indian Bill, which will replace the Information Technology Act.

AI Doomism

Yet, amidst the nation's AI-driven optimism, significant concerns persist. Last month, Zoho co-founder Sridhar Vembu co-signed an open letter, along with former NITI Aayog vice-chairman Rajiv Kumar and iSPIRIT Foundation co-founder Sharad Sharma, calling on policymakers, academics, and stakeholders to debate AI's impact on India.

Vembu highlighted the potentially seismic disruption AI could introduce, putting millions of jobs at risk overnight and creating "unprecedented disruption of the existing social order." Without appropriate safeguards, the rapid adoption of emerging technologies could pave the way for "chaotic and potentially catastrophic consequences for humanity."

As AI continues to proliferate, India, like many nations, must grapple with an essential question: Is the risk of unregulated AI expansion — a scenario that many experts deem concerning — one the nation can afford to take?

Written by Tasmia Ansari

The UK

Since the beginning of the year, ChatGPT has faced bans and investigations from privacy regulators in Europe, prompting the European Parliament to work on the draft legislation of the EU AI Act, which aims to regulate AI technology and define different risk levels. Comparatively, the UK government acted as a welcoming partner, planning to establish a new framework to warmly invite and regulate AI to promote responsible innovation and strengthen the country’s position as an “AI World Superpower by 2030”.

As a result, on June 28, OpenAI announced its first non-US office will open in London, which will rival the UK’s current AI leader, Google DeepMind.

Aiming to play a critical role

“Time and time again throughout history, we have invented paradigm-shifting new technologies, and we have harnessed them for the good of humanity. That is what we must do again,” announced UK Prime Minister Rishi Sunak during June’s London Tech Week 2023. The UK is currently ranked fourth in the Global AI Index, just after the US, China and Singapore, respectively. It remains ahead of its EU counterparts, with the next highest rating awarded to Germany at number 8.

As such, Sunak also announced the UK will host the world’s first AI Safety Summit in the autumn later this year. “The Global Summit on AI Safety will play a critical role in bringing together government, industry, academia and civil society, and we’re looking forward to working closely with the UK Government to help make these efforts a success,” says Demis Hassabis, CEO & Co-Founder, Google DeepMind, which is developing its own LLM AlphaGo and previously Gopher; as well as Google’s Bard.

Risking to lose

At the same time, UK Broadband provider BT’s Chief Data and AI Officer Adrian Joseph declared that the UK was in an “AI arms race”. He said the country could be left behind without the right investment and government direction, telling MPs that the UK urgently needs to develop its own AI LLM to allow its start-ups, scale-ups, and enterprise companies to compete with rivals in the US and China, with companies such as Baidu, Tencent, and Alibaba which have the scale to roll-out their own LLMs quickly.

Joseph warned that the plan would be put at risk without proper investment. Indeed, the UK government’s efforts have been bolstered by recent funding initiatives. These include £110 million (USD$126 million) for the AI Tech Missions Fund, £900 million for establishing an AI Research Resource and the development of an exascale supercomputer capable of running large AI models, £8 million to create an AI Global Talent Network, and provided £117 million in existing funding to support the creation of numerous Ph.D. positions for AI researchers.

“No one country can do this alone. This is going to take a global effort. But with our vast expertise and commitment to an open, democratic international system, the UK will stand together with our allies to lead the way,” says Sunak.

Ethics concerns

On the research side, AI Ethicist Kerry McInerney from Leverhulme Centre for the Future of Intelligence and the University of Cambridge told the Turing Post: “The release of ChatGPT has brought to the surface long-running concerns among AI ethics researchers and practitioners about the risks generated by large language models. It's turned our concerns about misinformation, discrimination, and harm into a hot-button topic and very abruptly introduced a lot more people to the concept of AI ethics,” she says. “On the one hand, ChatGPT has provided a helpful avenue into talking about issues to do with race, gender, power, and discrimination in AI systems and Big Tech, making it easier to engage researchers, industry figures, and policymakers in critical conversations about AI. On the other hand, I think that the release of ChatGPT and the excitement and hype around its capabilities have set the public discussion around AI back several steps.”

Economical impact

The potential economic impact of AI development in the UK cannot be overlooked. The KPMG report highlights that UK businesses’ widespread adoption of generative AI could contribute £31 billion to the GDP and increase overall productivity by 1.2%. In the international arena, the UN Security Council’s focus on the threats of AI to international security under the UK’s presidency emphasizes the global significance of AI regulation. “These scientists and experts have called on the world to act, declaring AI an existential threat to humanity on a par with the risk of nuclear war,” said UN Secretary-General Antonio Guterres, prompting the need for a multilateral approach to address the challenges and opportunities presented by AI.

As AI continues to advance at a rapid pace, it will be crucial to strike a balance between reaping its benefits and addressing potential risks. Unresolved issues in AI research and development, such as the need for regulations, skills development, and the responsible use of AI, require ongoing attention from policymakers, regulators, and industry leaders. The current landscape calls for international cooperation, proactive measures, and continuous evaluation of the trends and impacts of AI to navigate the complex and transformative AI-driven future effectively.

Written by Elle Farrell-Kingsley