Samsung is doubling down on high-bandwidth memory (HBM) production with a KRW 6 trillion (approximately $4.8 billion USD) investment in a new fab, but industry experts say the real challenge isn't making chips faster,it's keeping them cool. As AI data centers consume more power and semiconductor designs stack components vertically to boost density, thermal management has emerged as the critical bottleneck that could constrain the entire AI infrastructure buildout.

Why Is Heat Becoming AI's Biggest Problem?

The shift toward three-dimensional chip architectures is creating a thermal crisis. Individual AI chips from NVIDIA, AMD, and Google now exceed 1 kilowatt of thermal design power (TDP), while entire data center racks consume hundreds of kilowatts. As memory chips stack higher to increase density, heat dissipation becomes exponentially harder.

KAIST Professor Kim Joung-ho warned that thermal challenges could constrain AI expansion as both system semiconductors and memory increasingly adopt three-dimensional stacking. Beyond HBM, which stacks DRAM, he expects next-generation memory technologies like HBF (stacked NAND flash) and HBS (stacked SRAM) to emerge for the AI era, each presenting even greater thermal management challenges.

"AI-driven design automation could help optimize structures for heat dissipation," noted Kim Joung-ho, Professor at KAIST, citing an "HBM Design AI Agent" currently used in his laboratory as an example of how AI itself could become part of the solution.

Kim Joung-ho, Professor at KAIST

Samsung is already addressing this challenge with its zHBM technology, which stacks memory vertically above AI accelerators using wafer-bonding technology. The approach is expected to deliver over 10 times the memory density of HBM5, three times the energy efficiency, and more than 50% lower thermal resistance compared to conventional designs.

How Are Chipmakers Tackling the Thermal Crisis?

• Liquid Cooling Adoption: Liquid cooling penetration among AI chips is projected to rise from around 33% in 2025 to 53% in 2026 and approach 60% in 2027, becoming the standard for high-end AI infrastructure rather than a niche solution.
• Co-Packaged Optics (CPO): This technology converts electrical signals into optical signals, improving performance and power efficiency while reducing heat generation compared with conventional copper-based interconnects.
• System-Technology Co-Optimization (STCO): Rather than optimizing individual components, STCO aims to optimize overall system performance including thermal management, with the industry accelerating technology development and commercialization efforts around this approach.

Seoul National University of Science and Technology Professor Kim Sung-dong emphasized that the AI industry is increasingly prioritizing thermal management over further performance gains. He noted that physics-informed neural networks (PINNs) and deep reinforcement learning are rapidly emerging as tools to autonomously design and optimize substrate warpage and power delivery networks, which are critical for managing heat in complex chip architectures.

What Does Samsung's Expansion Tell Us About AI's Future?

Samsung's aggressive capacity expansion signals confidence in sustained AI demand, but it also reveals the industry's recognition that thermal constraints are real and urgent. The company plans to break ground in September on the new HBM fab at its Onyang Campus in South Chungcheong Province, with the project receiving approval a month ahead of schedule after provincial authorities streamlined consultations.

The expansion comes as Samsung stabilizes HBM4 production at scale. Sources indicate that Samsung's HBM4 yield has recently approached 80%, up from below 60% when mass production began in February. As yields improve and volumes ramp, the company is accelerating near-term capacity expansion at its Hwaseong and Pyeongtaek campuses to meet surging demand from global tech companies.

Beyond the new Onyang fab, Samsung is planning a major expansion at its Pyeongtaek Campus by adopting a triple-fab structure instead of the traditional double-fab design. If approved, P5-1 and P5-2 will accommodate up to six cleanrooms, increasing the cleanroom count by 50% and production capacity by more than 1.5 times. Construction began in 2022, with final completion targeted for 2030.

The shift to triple-fab designs reflects a broader industry trend. SK hynix is also planning triple-fab structures for all new fabs at its Yongin Semiconductor Cluster, signaling that this approach is becoming the standard for next-generation semiconductor manufacturing.

Why This Matters for AI Infrastructure

The thermal bottleneck is reshaping how the entire semiconductor industry approaches AI chip design. Rather than simply making chips faster or denser, engineers are now forced to innovate around heat management, which requires new materials, packaging techniques, and system-level optimization. This shift has profound implications for data center design, energy consumption, and the pace at which AI infrastructure can scale.

Samsung's massive investment in HBM capacity demonstrates that companies believe AI demand will remain robust despite recent investor skepticism about data center spending durability. However, the emphasis on thermal management technologies suggests that the industry recognizes a hard physical limit: without solving the heat problem, even the most advanced chips cannot deliver their full potential.