What Are the Future AI Investment Opportunities? Current Status and Technological Barriers of the AI Chip Industry
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With the continuous advancement of technologies such as deep learning and neural networks, the performance of AI chips has been significantly improved, and they are widely used in artificial intelligence, cloud computing, data centers, edge computing, mobile terminals, and other fields. At the same time, as the demand for artificial intelligence technology in various industries continues to increase, the market demand for AI chips is also growing. The widespread application and rapid development of artificial intelligence technology.
Future AI Investment Opportunities
CITIC Securities stated that in 2024, AI-related technological advancements are expected to emerge continuously, and future investment opportunities will gradually shift from hardware and tools to software products. Guotai Junan Securities mentioned that with NVIDIA's GTC conference approaching, the humanoid robot industry is set to experience intensive catalysts. Everbright Securities believes that the acceleration of humanoid robot industrialization will open up incremental space for precision reducers.
The artificial intelligence industry is currently in a phase of rapid development, with foundational large model capabilities and their applications continuously iterating at a fast pace. Although the industry is still some distance away from widespread industrialization and the explosion of consumer-facing products, it is expected that related technological advancements will emerge continuously in 2024. Recently, NVIDIA's launch of Gear further points to embodied intelligence. As the AI industry gradually matures, future investment opportunities are expected to shift from hardware and tools to software products, with industry development trending toward the integration of software and hardware and the connection between virtual and real worlds. In the future of artificial intelligence, whether it is the currently leading OpenAI, or the continuously following Google Gemini, Facebook Llama, and Chinese AI industry companies, all are expected to keep pace.
The acceleration of humanoid robot industrialization opens up incremental space for precision reducers, and leading domestic precision reducer manufacturers are expected to benefit significantly. Currently, the mainstream reducer solution for humanoid robots is the harmonic reducer, with some robots adopting precision planetary reducers for their lower limbs. As humanoid robots gradually scale up, precision reducers, as core components with a high value proportion, are expected to see a significant increase in market size. Current Status and Future Development Trends of the AI Chip Industry
With the intelligent development of the socio-economy, continuous advancements in AI technology, the widespread adoption of 5G applications, and policy-driven initiatives, the market demand for AI chips in China is expected to grow rapidly, leading to a significant expansion in market size.
In recent years, with the strong rise of AI, people have gradually realized the importance of chips and understood the principle that 'algorithms are chips.' However, while the general idea is widely understood, developing an AI chip that fully meets descriptions and benchmark tests is no easy task. The rapid iteration of large AI models has made intelligent computing power a scarce resource, and this is no exception in the domestic market. We have reason to believe that, for a considerable period in the future, China's AI server market will face a supply-demand imbalance, presenting a critical window of opportunity for the growth of the domestic AI chip market.
Elon Musk, CEO of Tesla, has likened the AI arms race to a high-stakes poker game, stating that companies aiming to compete in this arena must invest at least billions of dollars annually in AI hardware. Only then can they ensure sufficient competitiveness. Musk revealed that in 2024, Tesla will spend over $500 million on NVIDIA chips, a necessary step to potentially surpass its competitors.
The importance of AI chips is self-evident, and the frenzy to acquire them continues to intensify.
In fact, the significance of the AI chip race is recognized by far more than just OpenAI and Sam Altman. Policy support is a crucial factor driving the development of the AI chip industry. Globally, governments are actively positioning themselves in the artificial intelligence sector by implementing a series of policies to advance the research and application of AI technologies. For instance, China's New Generation Artificial Intelligence Development Plan explicitly calls for accelerating the development and application of AI chips, providing strong support for the industry.
Market demand is another significant driver of the AI chip industry. With the widespread adoption of artificial intelligence technologies, more industries are leveraging AI to enhance productivity and reduce costs. Fields such as smart homes, autonomous driving, and intelligent security systems have substantial demand for AI chips. The growth of these sectors will further propel the development of the AI chip industry.
Additionally, technological progress plays a vital role in advancing the AI chip industry. In recent years, breakthroughs in deep learning and neural network technologies have significantly improved the performance of AI chips. Meanwhile, advancements in chip manufacturing processes have led to higher integration and lower power consumption in AI chips. These technological innovations provide robust support for the industry's growth.
AI Chip Industry's Technical Barriers
Algorithm and Model Optimization: The performance and efficiency of AI chips largely depend on the optimization of algorithms and models. Advanced algorithms and models can better handle complex AI tasks, enhancing chip performance and efficiency. Thus, possessing cutting-edge algorithm and model optimization technologies represents a major technical barrier in the AI chip industry. Chip design and manufacturing: The design and manufacturing of AI chips require highly specialized knowledge and skills. Chip design involves multiple stages such as circuit design, layout design, and logic design, demanding profound technical expertise and professional experience. Simultaneously, the manufacturing of AI chips also requires high-precision processes and equipment, which constitutes one of the technical barriers in the AI chip industry.
Data processing and analysis capabilities: AI chips need to handle vast amounts of data and extract useful information from it. Therefore, possessing robust data processing and analysis capabilities is a significant technical barrier in the AI chip industry. This includes efficient data collection, storage, processing, and analysis technologies, as well as advanced data mining and machine learning algorithms.
Packaging and testing technologies: The packaging and testing of AI chips also represent an important technical barrier. Packaging technology protects chips from external environmental interference, enhancing their reliability and stability. Testing technology ensures that chip performance and quality meet standards, providing strong guarantees for AI chip applications.
AI Chip Industry Market Size
With the continuous rise of the AI boom, traditional giants and industry newcomers are challenging Nvidia's AI chip "moat." On one hand, traditional players like Intel and AMD are advancing new rounds of AI chip development plans; on the other hand, startups like Groq are actively promoting self-developed chips. Additionally, SoftBank Group founder Masayoshi Son and OpenAI are planning to enter the market with hundreds of billions or even trillions of dollars, turning the AI chip battlefield into a fiercely competitive arena. The market size of the AI chip industry is growing rapidly. According to predictions by market research firm Gartner, the global AI chip market size will reach $67 billion in 2024, while China's AI chip market is also expected to reach a considerable level.
In the fierce market competition, the ability of enterprises and investors to make timely and effective market decisions is the key to success. The AI chip industry report compiled by China Research Network provides a detailed analysis of the development status, competitive landscape, and market supply-demand situation of China's AI chip industry. It also examines the opportunities and challenges faced by the industry from the perspectives of policy environment, economic environment, social environment, and technological environment. Additionally, it reveals potential market demands and opportunities, offering accurate market intelligence and scientific decision-making references for strategic investors to choose appropriate investment timings and for corporate leadership to formulate strategic plans. The report also holds significant reference value for government departments.