CNNIC report: China's AI product user scale has reached 230 million, with broad development prospects (with original article)

On November 30, China Internet Network Information Center (CNNIC) released the Report on the Development of Generative Artificial Intelligence Applications (2024) (hereinafter referred to as the Report) to the public.

The Report shows that the scale of the core AI industry is close to 600 billion yuan, and the industrial chain covers key upstream and downstream links such as chips, algorithms, data, platforms and applications. China's generative artificial intelligence has a broad development prospect and provides new kinetic energy for high-quality development.

Currently, generative artificial intelligence products have formed a certain user scale among Internet users, and there is still significant room for growth in the future. As of June this year, the user scale of China's generative AI products reached 230 million people, accounting for 16.4% of the overall population.

This means thatAlmost one in six Chinese are using AI products.

By product.Baidu Wenxin Yiyin ranked first in the usage rate of typical domestic netizens of generative AI products, with a share of 11.5%.OpenAI's ChatGPT and Google's Gemini ranked second and third, with market shares of 71 TP4T and 3.81 TP4T, respectively.

Young, middle-aged and highly educated Internet users are the main users

In terms of users, young Internet users are the main users of AI products.By age group, Internet users aged 20-29 years old used generative AI products at the highest rate of 40.51 TP4T, followed by those aged 19 years old and below at 29.11 TP4T.

From different academic qualifications.Significantly higher usage of generative AI products among Internet users with college degree or abovewhich reached 44.01 TP4T; the utilization rate of generative AI products by Internet users with less than a college degree was 14.11 TP4T.

In terms of uses, big models are playing an increasing role in content creation.The report shows that nearly two-thirds of users use LLM (Large Language Modeling) services to answer questions, while one-third rely on them as work assistants to generate meeting notes and slides.

Intelligent body has become the mainstream application form

On the industry side, generative AI applications are also becoming more widespread. According to the Report.Cost reduction and efficiency gains are the core drivers for industries to choose to apply big models, and companies often prioritize R&D and service segments to try to upgrade intelligently.

Geographically, developed regions have become the leader of the AI industry. The data in the report shows that as of November 2024, a total of 309 generative AI products in China have completed the filing, and the number of generative AI filed products in Beijing, Shanghai, and Guangdong provinces accounted for 31.11 TP4T, 27.21 TP4T, and 11.71 TP4T, respectively.

In terms of areas of application, the Report states that.intelligences have become one of the dominant forms of generative AI applications.Become a new bridge connecting users to all types of services.

According to the Report, intelligences can work together as human assistants or independently to accomplish complex tasks. At the same time, intelligences are not limited to a single form of software, but can call upon tools and collaborate with other entities to become more powerful networks of intelligence.

As far as the technology itself is concerned, the Report states.Deep learning frameworks will be the key to iterative generative AI.

As the "operating system" of generative AI, deep learning frameworks bear various business models and industry applications, and are connected to intelligent computing chips, which have the two-way dominance of driving industrial applications and hardware adaptation, and have become the core focus of promoting the rapid iterative upgrading of AI hardware and software.

Looking ahead, the Report states thatThe four foundational capabilities of comprehension, generation, logic, and memory will be the key to moving large models towards generalized artificial intelligence (AGI).

The combined use of these four foundational capabilities forms the ability of a multimodal grand model to process, create, plan, and make decisions on multiple types of data inputs in complex task scenarios. The Report concludes that the stronger these four capabilities are, the closer the multimodal grand model will be to the goal of generalized AI.

According to Xinhua's analysis, in 2024, the big model industry entered the first year of application outbreak, in the domestic big model core battlefield, the general big model comprehensive ability, user scale, call volume, etc. is the basic factors of the big model vendors duel, determining whether the vendors can go to the endgame.

AI talent gap increases

As AI technology continues to revolutionize, there is a growing demand for high-end technical talents. During the 2023 World Conference on Artificial Intelligence, Qiu Xin, Party Secretary of Fudan University, has said:

"The total talent gap in the field of artificial intelligence in China is as high as 5 million.Shanghai is expected to have a demand of 400,000 in 2025, while the size of students enrolled in related majors in local universities is only 40,000."

This Report also specifically mentions the expanding AI talent gap.

According to the Report, while the talent gap has increased, colleges and universities lack high-level experience in building curricula for AI-related education, resulting in a certain discrepancy between the specialized knowledge that students learn and their actual employment. In addition, there is a lack of education and training for minors, whose main channel for acquiring information is to "browse for relevant knowledge on the Internet" rather than from the school's education program.

As previously reported by Nandu, the research data released by AiMedia Consulting in June showed that 91.3% of the surveyed enterprises are facing a lack of artificial intelligence talent. However, the training of talents in some universities is decoupled from the real needs, and the level of teachers is uneven and the teaching conditions are insufficient.

To crack the talent gap, the Report proposes to improve the support and guarantee mechanism for the introduction and return of overseas talents, and to carry out practical and generative AI education in colleges and universities, as well as to incorporate the basics of AI into the primary and secondary education system.