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As AI compute demand grows exponentially, the physical limits of traditional silicon-based chips are rapidly becoming apparent. The world is accelerating into a disruptive “post-GPU era,” in which quantum computing is no longer confined to laboratory theory but is emerging as a double-edged force capable of reshaping drug discovery and financial risk management—even triggering a “quantum crisis” by undermining national-level encryption systems.
From NVIDIA’s hybrid-computing strategy to the competing technical roadmaps of IonQ and Rigetti, and from the national-level arms race unfolding across the United States, China, Europe, and Japan, the next decade will be defined by a high-stakes contest for computational supremacy. Against this backdrop, Taiwan’s supply chain faces a defining question: how will it position itself in the era of quantum computing?
The global AI hardware market continues to expand, driven by increasing CSP capital expenditures and accelerated procurement of advanced computing resources. In response, companies are partnering with Google to adopt TPUs, while TPU technology evolves with enhanced architectures and supply chain strategies to support next-generation AI models. AI applications are increasingly recognized as a key enabler of high-performance transformation.
The global satellite market is expected to reach $392 billion in 2026. Competition will intensify as Starlink continues expanding satellite broadband and direct-to-cell (D2C) services into emerging markets, prompting MEO/HEO/GEO satellite operators to accelerate multi-orbit deployment strategies to counter Starlink’s growing influence.
Meanwhile, early-stage 6G deployment is underway. As global satellite service markets rapidly scale, Taiwanese manufacturers are shifting production bases to Southeast Asia while increasing shipments of key satellite components.
The rise of AI and HPC workloads has significantly increased GPU power consumption, from a few hundred watts to over 2,300W in the Rubin generation. This evolution has elevated cooling from a mere support component to a critical factor for maximizing computational performance. As traditional liquid-cooling methods near their physical limits, the industry is turning to a next-generation solution: Microchannel Lids (MCL). Quietly, a new “cooling revolution” is underway.
A clear uptrend is taking shape for 2026, with tighter DRAM supply and broad-based price increases now firmly in sight. The primary growth catalyst is CSPs, which are accelerating data center expansion to support AI workloads. This is not only driving higher global server shipments but also a notable increase in memory content per server.
In the NAND Flash market, enterprise demand will serve as the core growth engine in 2026, while the consumer segment is expected to remain muted until a more visible economic recovery boosts purchasing power and revitalizes demand.
Looking ahead to 2026, continued strength in AI server demand—combined with suppliers' profitability-first strategy—will keep both DRAM and NAND Flash prices on an upward trajectory, reinforcing a structural pricing shift across the memory industry.
Given the complexity and diversity of the challenges faced by urban transportation, the parallel development of intelligent transportation systems (ITS) and autonomous driving aims to address congestion and enhance system resilience. AI-powered ITS will toward greater proactivity, strengthening real-time sensing and decision-making capabilities as regulations and technologies for autonomous vehicles evolve. However, data standardization and platform integration remain critical challenges that must be resolved.
Current progress in humanoid robotics is centered on optimizing vision-language-action (VLA) models, integrating multimodal data, and enhancing instruction comprehension as well as the ability to interpret human intent. Training relies heavily on world models, human video data, and VR-based remote training, with increasing emphasis on first-person perspectives to strengthen perception. While the ultimate goal is to achieve general-purpose humanoids, development remains constrained by significant challenges, leading Western and Chinese companies to pursue divergent technological pathways.
In its endeavor to bolster its global leadership, the United States is actively promoting the reorganization of supply chains and the repatriation of manufacturing through the implementation of reciprocal tariffs and a significant increase in strategic investments. This report provides a comprehensive examination of the U.S. smart manufacturing landscape, with specific attention to the semiconductor, automotive, and fast-moving consumer goods (FMCG) sectors. It delves into the strategic postures of key companies and their deployments in hardware (e.g., chips and sensors), software, and integrated systems.
Global tech powerhouses are actively advancing the integration and development of AI and quantum computing, ushering in the next wave of computing power revolution. Quantum computing, with its inherent advantages in handling high-dimensional optimization, many-body simulation, and stochastic combination problems, has become a key complement to HPC and AI computing architectures. Quantum computing particularly demonstrates practical potential in areas such as model compression, inference acceleration, and bandwidth optimization.
As power consumption and thermal density in AI servers soar, traditional air-cooling methods are increasingly inadequate when it comes to meeting the demand of high-performance computing (HPC). Liquid cooling, with its superior heat dissipation capabilities, is rapidly emerging as a key solution for supporting the next generation of high-performance systems.
The explosive growth of the AI server market has not only driven urgent demand for high-density thermal management but also transformed liquid cooling from a niche technology into a mainstream battleground—becoming a critical force behind data center upgrades.
