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1. Supply-side Outlook: Server DRAM and CPUs
2. Demand-side Outlook: Server Brands and CSPs
3. Server DRAM Price Trends
4. TRI's View
1. Development of Global AI Industry Chain
2. Analysis of Cross-Modal Business Opportunities in AI
3. A Breakdown of Hardware Supply Chain
4. TRI’s View
1. Global Overview of the AI Market Development
2. The Necessity of Openness in AI Development
3. Current Applications and Development of AI
4. TRI’s View
Driven by advancements in AI and Generative Content (AIGC), the role of PCs is evolving to reshape how we use technology. PCs that offer a blend of computational power, efficiency, and security are becoming the preferred environment for AI computations and machine learning, enabling personalized AI applications on a large scale. At present, AI PCs are just beginning to emerge, with their development hinging on both hardware innovation and software advancements to propel the future of AI computing forward.
Based on the application foundation of AI within the industrial field, AIGC has welcomed a robust development among industrial segments, with integration of industrial software, including CAX and EDA, in the hope of replenishing for the dislocation yielded by the innovation of process technology and AI applications. This would fully improve the substantial efficacy generated by AI, especially for fields such as visual identification and virtual reality (VR).
Edge computing involves the relocation of computing processes from centralized cloud systems to the very source where data are generated. This shift brings about several advantages, notably a significant boost in computing speed and a reinforcement of data security. For the manufacturing sector, where precision, stability, and security are prioritized, edge computing emerges as a pivotal enabler for unlocking the true potential of smart manufacturing. Furthermore, looking towards the future, it is anticipated that the development of edge computing will fully embrace the trend of edge AI.
A smart city generates a large amount of data through the Internet of Things (IoT), which will not only improve traffic and increase the efficiency of city operations but enable more precise decision-making for city managers. Currently, the sensing systems in smart cities are still in the stage of extensive deployment. As communication infrastructure improves, the connectivity and sensing networks become more intricate. Through IoT platforms, data integration is possible, and as the volume of data continues to grow, these platforms will increasingly unlock the value of the data they handle.
This report offers a comprehensive analysis of the competitive landscape in the AI server market, providing a forecast for 2024 and identifying key factors driving future trends. It further delves into the strategies adopted by China’s AI server industry to navigate the constraints on advanced AI chips, with a specific focus on developments in GPU, ASIC, and HBM chips.
Due to the close relation between vehicle safety and both traffic and personal safety, various features such as internet connectivity, communication requirements, and software-defined vehicles all contribute to an increase in potential attack vectors. Moreover, as the number of electric vehicles (EVs) rises and the charging infrastructure expands, the scope of cyberattack targets also widens accordingly. Consequently, there is a pressing need to enhance cybersecurity measures and effectively manage vulnerabilities to safeguard vehicles from multiple security threats.
In just six short months, AI has advanced from generating text, images, music, and code, to automation and generative agents, exhibiting astonishing capabilities. This report, aside from focusing on the latest developments in AI, also probes into how governments and industries are formulating strategies to ensure positive AI advancements, as well as analyzes the timeline for large-scale implementation of AIGC and its impact on the demand for AI servers.
