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Silicon Flash > Blog > Infrastructure > Adapting to the Era of Artificial Intelligence: The Transformation of Data Center Semiconductors
Infrastructure

Adapting to the Era of Artificial Intelligence: The Transformation of Data Center Semiconductors

Published August 18, 2025 By Juwan Chacko
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Adapting to the Era of Artificial Intelligence: The Transformation of Data Center Semiconductors
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The foundation of the worldwide cloud and AI infrastructure is currently experiencing a significant transformation, spearheaded by the semiconductor sector. This industry is at a crucial point, with AI’s explosive growth and fundamental shifts propelling this evolution.

The global cloud and AI infrastructure are undergoing a remarkable transformation, driven by the semiconductor industry. This market is at a critical stage, with AI’s rapid expansion and significant changes leading the way.

By 2024, the total addressable market (TAM) for data center semiconductors had reached an impressive $209 billion, encompassing compute, memory, networking, and power domains. This figure is expected to nearly double by 2030, reaching close to $500 billion. The primary drivers behind this growth are AI and high-performance computing (HPC), with generative AI playing a substantial role in boosting demand for processors and accelerators.

When it comes to AI infrastructure, GPUs continue to play a central role, with Nvidia dominating a staggering 93% of server GPU revenue by 2024. The Yole Group forecasts that GPU revenue will skyrocket from $100 billion in 2024 to $215 billion by 2030. Despite their high average selling prices, GPUs are essential for AI training and are increasingly utilized for inference tasks.

Amidst this swiftly evolving landscape, AI application-specific integrated circuits (AISCs) are gaining prominence. Tech giants such as Google, Amazon, and Microsoft are heavily investing in domain-specific silicon to boost performance and reduce dependence on Nvidia. Consequently, AI AISC revenue is projected to surge to $84.5 billion by 2030.

The advancements are not limited to computation alone. Memory architecture is also making rapid strides, with ongoing DDR5 adoption and a surge in demand for high bandwidth memory (HBM), particularly for AI training purposes. Computational express link (CXL) is becoming increasingly crucial, tackling memory disaggregation and latency challenges in emerging server architectures.

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There are also notable shifts in data center silicon leadership. While American companies like Nvidia, AMD, and Intel continue to dominate, China is bolstering its domestic capabilities through strategic investments and policies. This trend is further reinforced by export controls impacting supply chains, emphasizing the push for self-reliant development within and beyond China.

The significance of startups and new entrants in the market should not be underestimated. Companies like Groq, Cerebras, and Tenstorrent are reshaping the industry landscape, showcasing how unconventional solutions can rival established players in terms of cost-effectiveness, performance, and energy efficiency.

Eric Mounier, PhD, Chief Analyst of Photonics at Yole Group, commented, “The data center semiconductor industry is exploring various approaches today. At Yole Group, we have delved deep into this field, analyzing the innovations that are driving the sector. Current solutions are all about control. AI workloads are reshaping the design of chips, how they are packaged, and where they are manufactured.”

TAGGED: Adapting, Artificial, Center, data, Era, Intelligence, semiconductors, Transformation
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