Analysis Report on the Current Status and Prospects of the AIGC Market
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What is the current status and future outlook of the AIGC industry? What are the investment trends in the AIGC market? Early AIGC technologies relied on predefined templates or rules for simple content creation and output, falling short of flexible and realistic content generation. During this period, AI algorithms lacked strong learning capabilities and mostly depended on predefined statistical models or expert systems to perform specific tasks. Through clever rule design, early AIGC technologies could generate simple lines, text, and melodies.
AIGC technology has entered a deepening phase of upgrades. The continuous iteration of AI algorithms is the driving force behind AIGC's progress. From a technological evolution perspective, AIGC can be broadly divided into two stages: the pre-deep learning stage, which relied on templates or rules, and the deep learning stage, marked by the rapid development of deep neural networks.
In addition to variational autoencoders and generative adversarial networks, other learning paradigms such as reinforcement learning, flow models, and diffusion models have also made encouraging progress. These model paradigms each have their advantages in different scenarios, enabling AIGC technology to be quickly applied to various tasks. The structural upgrades of deep neural networks are another major factor driving the rapid development of AIGC.
Analysis Report on the Current Status and Prospects of the AIGC Market
From the perspective of AIGC's industry application value, AIGC is expected to become a new engine for the innovative development of digital content, injecting fresh momentum into the digital economy.
Generative AI (AIGC) is a significant milestone marking the transition from AI 1.0 to AI 2.0. From the progression of computational intelligence to perceptual intelligence and then to cognitive intelligence, AIGC has opened the door to cognitive intelligence for human society. By training on large-scale datasets, AI has acquired knowledge across multiple domains. With appropriate adjustments, these models can now perform tasks in real-world scenarios.
A systematic evaluation has been conducted on the top ten mainstream large models in the market, including ChatGPT 3.5, ChatGPT 4, Claude-1, Claude-2, Tsinghua's ChatGLM130B, Baidu's ERNIE Bot, Alibaba's Tongyi Qianwen, iFlytek's Spark, 360's Brain, and Kunlun Wanwei's TianGong.
AIGC holds milestone significance for human society and artificial intelligence. In the short term, AIGC has transformed basic productivity tools. In the medium term, it will alter societal production relations. In the long term, it will drive qualitative breakthroughs in overall social productivity. Amid these transformations in productivity tools, production relations, and productivity, the value of data as a production factor has been greatly amplified.
This year, China's AIGC market size is projected to reach 17 billion RMB, but AIGC companies are still in the exploratory phase of monetizing business scenarios.
Before major e-commerce platforms introduced large language models, some in the e-commerce sector had already begun using tools like Midjourney (MJ) and Stable Diffusion (SD) to generate clothing and accessories and replace models. Others have leveraged various generative SaaS applications to assist in e-commerce operations.
Data shows that in 2023, the talent supply-demand ratio in the broader internet industry continued to rise, but AI talent and high-tech professionals remain scarce, with salaries climbing against the trend for three consecutive years. Algorithm researchers top the list of talent shortages with a supply-demand ratio of 0.47, meaning two companies compete for one candidate on average.
"New first-tier companies" have emerged as strong contenders. Due to robust business growth, these companies have significantly increased hiring demand and are willing to offer higher compensation, greatly enhancing their appeal in the talent market. From the perspective of job seekers, large companies are no longer the top choice for many professionals, with over a quarter of internet workers preferring fast-growing companies with around 1,000 employees.
By 2025, the core AI industry is expected to reach a scale of 300 billion RMB, maintaining a growth rate of over 10%, with the broader industry exceeding 1 trillion RMB. Leading AI companies will continue to increase R&D investments, the number of startups will grow, and the total number of companies will remain domestically leading, with 5-10 new unicorn companies emerging. The depth and breadth of AI applications will further expand, with generative products becoming mainstream in the domestic market and ecosystem platforms, driving high-end industrial development.
The industrial value of AIGC is mainly reflected in two aspects: "transforming content production methods" and "transforming human-computer interaction," both centered around large models. In the future, industries will leverage the vast array of AI production tools derived from large models to achieve leaps in content production efficiency and further lower the barriers to human-computer interaction in the digital ecosystem.
The three-tier architecture of AIGC consists of the foundational layer, model layer, and application layer. In the first half of 2023, domestic investment in the AIGC sector was primarily concentrated in the model layer, accounting for the highest proportion with a financing scale of 4.309 billion yuan, followed by the application layer at 1.154 billion yuan, while the foundational layer received the least funding at only 100 million yuan.
In the lifestyle sector, AIGC is further decentralizing content creation rights, stimulating user-generated content (UGC) enthusiasm, and accelerating content proliferation. In the production sector, large models can comprehensively enhance enterprise service software in terms of R&D processes, product capabilities, and interactions. Content distribution platforms, linking creators on one end and binding a large user base on the other, possess the most complete content consumption ecosystem, becoming the core of AIGC content consumption. AIGC technology has already been applied in the automatic generation of marketing copy, e-commerce images, and even comments.
From the perspective of talent mobility, companies with around 1,000 employees have consistently attracted professionals with over five years of experience at a higher rate than large corporations for two consecutive years. In 2022, the inflow of professionals with five years of experience into these mid-sized companies was 28.72%, surpassing the 23.72% for large corporations. In the first half of 2023, this trend continued, with mid-sized companies leading by 3.56 percentage points.
In terms of talent supply-demand ratios across different roles, high-tech talent remains in short supply. In the first half of this year, the most in-demand roles in the broader internet industry were concentrated in the AI field. Algorithm researchers topped the list with a talent supply-demand ratio of 0.47, meaning two companies on average compete for one candidate. The AI boom has also driven recruitment demand for AI engineers, natural language processing specialists, and deep learning experts, with supply-demand ratios of 0.61, 0.66, and 0.73 respectively, indicating a talent shortage.
The large model trend continues to gain momentum. Amazon Web Services has been rolling out services in areas like simple code writing, gaming, and healthcare, with a dense layout in generative AI.
On one hand, AIGC can undertake basic mechanical tasks such as information mining, material retrieval, and replication editing with capabilities superior to humans, technically meeting massive personalized demands with low marginal costs and high efficiency. Simultaneously, it can innovate content production processes and paradigms, enabling more imaginative content and diverse dissemination methods, pushing content production toward more creative directions.
On the other hand, AIGC can foster new business models and formats by supporting multidimensional interactions and integration between digital content and other industries, creating new economic growth points and providing fresh momentum for various sectors.
The 'metaverse' demonstrates development momentum beyond imagination. As the 'ultimate' digital carrier of digital-physical integration, the metaverse will feature persistence, real-time capabilities, and creativity, and will accelerate the replication of the physical world and infinite content creation through AIGC, enabling organic growth. Governance issues are becoming increasingly severe, requiring global attention to ensure the healthy development of AI. This involves both incremental changes and structural or even directional adjustments, necessitating comprehensive and systematic improvements in various capabilities to promote sustainable and healthy AI development.
The current state of China's AIGC industry market, analyzed by a professional research team through the collation and analysis of various market data, can help investors assess the market status, predict industry prospects, identify investment value, and provide recommendations on investment strategies and marketing approaches for the AIGC industry.
The analysis covers the internal and external environment of China's AIGC industry, its development status, industrial chain conditions, market supply and demand, competitive landscape, benchmark enterprises, trends, opportunities, risks, development strategies, and investment recommendations.