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The anticipation of AI-Generated Content (AIGC) applications approaching large-scale commercial deployment has triggered a sharp rise in demand for AI chips, significantly impacting the global high bandwidth (HBM) market. This report will provide analysis from two fronts: First, it will explore the development of AIGC applications and large language models (LLMs). Then, it will examine the evolving needs for ASICs, GPUs, and HBM crucial for AI-powered cloud computing.
The AI chip is undoubtedly the lifebuoy of the technology industry in 2023, creating new vitality in the industry downturn. In 2024, this wave will undoubtedly continue to sweep through the industry with more services being created under Gen AI. NVIDIA, as it dominated the AI chip market in 2023, will be facing additional challenges in 2024, including whether in-house chips from the six major CSPs, such as Microsoft, Google, and Amazon, will pose as potential threats.
Chinese players, who can only purchase downgraded versions of NVIDIA chips currently, have also turned to purchasing in-house chips from China. This report will analyze which Chinese suppliers are being driven by this trend. Advanced packaging CoWoS that was regarded as a bottleneck for the capacity of AI chips throughout 2023, as well as the additional of new suppliers for 2024, will also be covered in this report.
As global internet data transmission volume continues to reach new highs, the performance bottleneck of light communication solutions becomes increasingly apparent. This report, on the one hand, explores the shortcomings of existing light communication solutions. On the other hand, it focuses on silicon photonics and CPO technology, analyzing their competitive advantages in the field of light communication, and keeping track of the development dynamics of key manufacturers.
1. Key Developments in Generative AI Products, Services, and Regulatory Standards
2. Analysis of Major CSPs’ 4Q23 and Recent Financial Reports
3. Strategic Deployment of Generative AI by Major CSPs
4. TRI’s View
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.
