The AI track may become the main line of investment in the first half of this year and even the whole year, and there are continuous opportunities in the sector.1. BackgroundOn March 5, the latest work report pointed out that it is necessary to further promote the innovation and development of the digital economy. Formulate policies to support the high-quality development of the digital economy, actively promote digital industrialization and industrial digitization, and promote the deep integration of digital technology and the real economy. Deepen the R&D and application of big data and artificial intelligence, carry out the "artificial intelligence +" action, and build a digital industrial cluster with international competitiveness.
Artificial intelligence has become one of the key grasps and engines of industrial innovation. As early as the local two sessions held in various provinces and cities, topics such as artificial intelligence, large models, data infrastructure, and computing infrastructure development have been widely discussed. For example, Shanghai proposed that the scale of the three leading industries of integrated circuits, biomedicine, and artificial intelligence should reach 16 trillion yuan; Guangdong emphasized the need to strengthen the key technology research of large models and accelerate the formation of a 100-billion-level artificial intelligence group; Jiangsu has made it clear that artificial intelligence will empower new industrialization in an all-round way, and in-depth implementation of "intelligent transformation and digital transformation to networking".
The AI track may become the main line of investment in the first half of this year and even the whole year, and there are continuous opportunities in the sector. Benefiting from the iterative development of AI technology, industries such as industrial manufacturing and autonomous driving have accelerated their transformation. ChinaAMC** Strategy Team recommends focusing on Artificial Intelligence (AIET) (515070), Robotics ETF (562500), Smart Car ETF (159888) and Chip ETF (159995).
2. Popular interpretation
1) AI large models empower manufacturing upgrading.
As artificial intelligence technology enters the practical stage, with the deep integration of artificial intelligence and manufacturing as the main line, empowering key industrial systems with large-scale model capabilities, and promoting the upgrading of industrial digitalization to intelligence, it is becoming a new driving force for the high-quality development of China's economy and society. This year's National People's Political Consultative Conference, Zhou Hongyi, a member of the National Committee of the Chinese People's Political Consultative Conference and founder of 360 Group, brought relevant proposals on the verticalization and industrialization of general large models, and said that 2024 is the first year of large model application scenarios, and China can completely embark on a large model development path with Chinese characteristics. An important direction for China's development of large models is to combine large models with business processes and product functions with the advantages of industries and scenarios, seek vertical and industrial implementation, empower hundreds of industries, and help accelerate the formation of new quality productivity.
From the perspective of production and manufacturing, AI is expected to strengthen the information processing, perception and execution capabilities of industrial robots. The emergence of ChatGPT, a natural language processing tool, can help machines gradually realize that they can truly communicate like humans and perform a large number of tasks. With the development of generative AI, it will truly promote the intelligent and digital transformation of manufacturing links, and industrial robots and automated factories, as the core carriers of intelligent manufacturing, will serve as the intermediate bridge between generative AI and intelligent manufacturing. According to Microsoft's "ChatGPT for Robotics: Design Principles and Model Abilities", generative AI currently assists industrial robots through two levels: first, ChatGPT, as a pre-trained language model, can be applied to natural language interaction between humans and machines. The machine understands the natural language instructions of humans through ChatGPT and makes corresponding actions according to the instructions. Second, GPT can help machines make decisions when performing tasks such as path planning and object recognition.
At the same time, generative AI relies on industrial models to build engineering and manufacturing engines to continuously improve productivity, and domestic enterprises have begun to apply them in this field. For example, on April 13, 2023, the leading player of the domestic "AI + Manufacturing" solution, Qizhi Innovation has released the "Qizhi Kongming" AIGC engine (AINOGC), which is an AIGC engineering algorithm engine for vertical scenarios in the manufacturing industry, relying on Qizhi's self-developed MMOC artificial intelligence technology platform and taking industrial pre-trained large models as the core. Qizhi Kongming has five capabilities, namely content generation, intelligent Q&A, multi-round dialogue, reasoning ability, and advanced generation, which can meet the personalized needs of enterprises in the manufacturing industry. This engine will be mainly applied to the manufacturing and industrial software fields to effectively solve the exclusive needs of large customers in the industry, such as interactive dynamic business report generation, intelligent production line design, etc., breaking vertical information silos, improving productivity, and achieving more comprehensive digital transformation.
AI is reshaping the manufacturing industry, and the manufacturing industry, as the core of China's industry, will fully benefit from the deep integration with AI, further realize intelligent upgrading, and enhance global competitiveness.
Figure 1: AI+ industrial application scenarios.
Material**: Huatai**.
2) AI large models empower the rapid development of intelligent driving.
Intelligent driving is one of the most important landing scenarios of AI, and with the empowerment of large models, intelligent driving is expected to have more new possibilities. Lei Jun, founder, chairman and CEO of Xiaomi, as a representative of the 2024 National People's Congress, prepared four proposals to be submitted to the conference, among which further standardize the safe application of intelligent driving products. At the same time, He Xiaopeng, a representative of the National People's Congress and chairman and CEO of Xiaopeng Motors, suggested that policies and regulations for low-speed unmanned driving in limited scenarios should be explored, and pilot applications of low-speed unmanned driving + energy replenishment at night should be carried out in limited scenarios.
The implementation of autonomous driving functions relies on algorithms, data, and chips to close the loop.
From the perspective of the algorithm layer, deep learning has the advantages of excellent fitting ability, strong representation learning ability, and wide application range, which can effectively improve the performance of autonomous driving. In the past decade, Waymo, other technology companies, new EV manufacturers and traditional OEMs have increased their deployment in deep learning and vigorously developed autonomous driving technology.
From the perspective of the chip layer, computing power is one of the core driving forces for the development of automotive intelligence, driving the rapid growth of automotive chips. With the increasing application of AI technology in intelligent driving, the demand for computing power is gradually increasing. The application scenarios of on-board computing chips mainly include the body domain, cockpit domain, chassis domain, power domain and intelligent driving domain. Among them, the autonomous driving scenario will be one of the key scenarios for the fierce competition of on-board computing chips in the future.
At present, the smart driving chip market is divided between Mobileye and NVIDIA, and localized brands represented by Horizon and HiSilicon are taking the lead in entering the market of self-owned brand car companies by virtue of their significant advantages in the field of AI computing and large computing power, and realize the mass production of domestic chips. Driven by the growth of computing power demand, the automotive chip market may grow strongly, and the automotive computing chip market is expected to usher in a period of rapid development. According to the "China Smart Vehicle Vehicle Computing Chip Industry Report" released by Analysys, the market size of vehicle computing chips will reach 205.4 billion yuan in 2023.
In addition, AI chips with large computing power will become the mainstream development direction of autonomous driving chips, and the amount of data required for autonomous driving assistance functions of L2 and below is smaller, the algorithm model is simpler, and the strong coupling between small computing power chips and algorithms can meet the needs of OEMs. The increase in sensors and the improvement of resolution of L3 and above intelligent driving systems have increased the demand for massive data processing, increased the complexity of algorithm models, and increased the demand for computing power, making large computing power chips a key "infrastructure" for the evolution of intelligent vehicles. Optimistic about the intelligent driving industry empowered by AI, it is recommended to pay attention to investment opportunities such as domestic large computing power chips, upstream hardware manufacturers, and downstream multimodal applications.
Figure 2: Mapping of autonomous vehicle functions to AI technology.
Source**: CICC.
3. Exponential opportunities
1. Artificial Intelligence AIETF (515070) and its connection** (008585 008586).
Tracks the CSI Artificial Intelligence Thematic Index (Index**: 930713CSI, index abbreviation: CS artificial intelligence), select representative companies from the companies that provide basic resources, technology and application support for artificial intelligence as sample stocks, reflecting the overall performance of artificial intelligence theme companies.
2. Robot ETF (562500) and its connection**(018344 018345).
Tracking CSI Robot Index (index**: H30590CSI) selects system solution providers, digital workshop and production line system integrators, automation equipment manufacturers, automation parts manufacturers and other related companies as sample stocks to reflect the trend of the robot industry.
3. Smart Car ETF (159888).
Tracks the CSI Smart Car Thematic Index (Index**: 930721CSI, index abbreviation: CS Smart Auto), the index selects companies that provide terminal perception and platform applications for smart cars, as well as other representative Shanghai and Shenzhen A-shares that benefit from smart cars, as sample stocks, reflecting the overall performance of smart car industry companies.
4. Chip ETF (159995) and its connection** (008887 008888).
Tracking the CNI Semiconductor Chip Index (980017CNI, index abbreviation: CNI chip), aims to reflect the market performance of listed companies related to the chip industry in the A** field, and the index constituents are "less but fine", focusing on high-quality**, and higher liquidity, and better long-term returns. As a representative index of the semiconductor chip industry, the CNI Semiconductor Chip Index can reflect the market opportunities in the industry.
5. 5getf(515050) and its join**(008086 008087).
Tracking the CSI 5G Communication Theme Index (Index**: 931079CSI, index abbreviation: 5G communication) selects listed companies** whose products and businesses are related to 5G communication technology as sample stocks, including but not limited to sub-sectors such as telecommunication services, communication equipment, computers and electronic equipment and computer applications, aiming to reflect the overall performance of A-share listed companies in related fields, and make flexible adjustments every six months to capture the opportunities brought by 5G technology innovation.
Data**: CICC, Huatai**, Wind, as of March 4, 2024.
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