Is the Semiconductor Boom Over? Why the Chip Industry Has Runway Until the First Half of Next Year
Discover why the semiconductor industry is far from over, driven by AI, HBM demand, custom chips, and strong structural growth into next year.
The history of technology has always charted new territories amidst the sandstorms of uncertainty, and the massive tectonic shifts happening on silicon wafers today signal a civilizational transition that goes far beyond simple boom-and-bust cycles. Are we truly discussing the end of the semiconductor industry, or are we witnessing the dawn of a new golden age?
Core Insights
1. The Gap Between the Illusion of Decline and Structural Growth
The "invisible hand" in economics guides capital to its most efficient destinations while simultaneously blinding market participants with extreme short-sightedness. When mass media and non-experts get bogged down by commodity memory price fluctuations or short-term growth slowdowns to declare the peak of the semiconductor industry, a completely different dimension of massive movement is churning at the base of the real economy. As mature technological paradigms inevitably conceive internal contradictions, memory semiconductors have historically operated as pure commodities, weathering harsh cycles of oversupply and shortage. However, since the advent of artificial intelligence as a civilizational variable, semiconductors have transcended the status of mere components. They have evolved into the central nervous system determining national security and corporate survival. Therefore, concluding that fundamental demand has been compromised simply because superficial growth numbers temporarily dipped is a fatal miscalculation. Just as Roman historians failed to see the seeds of new institutions when discussing the empire's fall, today's market analysts overlook the structural qualitative leap in the high-value memory market, spearheaded by HBM. The logic of capital always chases higher returns, meaning the entire semiconductor ecosystem has entered an orbit completely distinct from the past.
"Declaring the end of semiconductors based on cyclical dips is a fatal miscalculation overlooking the structural leap of high-value memory and AI demand."
2. The Rise of Custom Semiconductors and Ecosystem Fragmentation
Just as Thomas Hobbes emphasized the necessity of the state through the war of all against all, the rapidly changing digital market is forcing big tech companies to break free from traditional supply chain constraints and forge their own paths. In the past, all big tech companies had to bow and line up before a single standard chipset designed by NVIDIA. However, as generative AI computational demands exploded exponentially and the cost-efficiency limits of general-purpose GPUs became apparent, global big tech firms began staking their lives on developing custom-designed chips (ASICs) optimized for their specialized workloads. Starting with Google's TPU, followed by Amazon's Trainium, and recently OpenAI's proprietary silicon chipset, the market is rapidly reorganizing from a single monolithic monopoly into a diversified, customized ecosystem. This phenomenon presents a monumental challenge yet unprecedented opportunity for semiconductor manufacturers because the performance they demand is no longer bound by existing standardized specifications. Google's pursuit of generalizability differs from specific model optimization, and OpenAI's requirements for massive super-scale model computations completely shatter conventional wisdom. In this process, the importance of custom memory is maximized. While markets previously accepted products passively from manufacturers, customers now pay astronomical upfront deposits or offer exceptional terms to secure supply first, reversing the traditional power dynamic.
3. Paradoxical Fortune and High-Stakes Technological Gambles
Niccolò Machiavelli emphasized 'Fortuna' (luck) as a virtue for rulers, rewarding only the prepared and the bold. Similar historical ironies frequently produce dramatic reversals in corporate management. While dominant memory market players hesitated between complacency and conservative investment, latecomer Samsung Electronics leveraged strong executive drive to completely upend the board. Initial expectations anticipated gradual improvements tailored to conservative specs from major clients like NVIDIA. However, brushing aside market skepticism and profitability concerns, Samsung executed an unprecedented "over-spec" investment from the start—applying ultra-high-spec processes well beyond market demands and utilizing a 4nm process for the base die. This was a calculated gamble, driven less by cold market analysis and more by the animal instinct born of a do-or-die crisis mindset. Yet, the gods of history frequently favor the bold adventurer over the meticulous planner. When NVIDIA drastically raised required specs while moving toward its next-generation platform, Vera Rubin, the only prepared partner in the market instantly capable of meeting that steep elevation in specs was ironically Samsung, which had most aggressively made preemptive investments. This technological edge transcends simple luck, serving as a textbook case of how long-accumulated manufacturing prowess can detonate at a critical moment.
4. AI-Accelerated Silicon Alchemy
Michael Polanyi's epistemological paradox—"we can know more than we can tell," referring to the realm of tacit knowledge—has long relied on the intuition and experience of skilled artisans. Much like veteran steelworkers determining the pouring time just by looking at molten metal color, cutting-edge semiconductor manufacturing processes have been the product of countless engineers' invisible know-how and trial-and-error. Today, however, artificial intelligence is injecting massive acceleration into analog process optimization once thought to be exclusively human domains. OpenAI utilizing AI codecs over 100 times more powerful than standard code alongside advanced Electronic Design Automation (EDA) tools to shorten design periods is merely the tip of the iceberg. AI is digitizing human intuition and converting it into explicit knowledge across the entire manufacturing process, improving yields and reducing defect rates, not just in chip design. Behind Chinese memory firms rapidly closing the gap also lies this AI-driven process simulation and optimization technology. Ironically, semiconductors built to run AI are now being designed faster and more powerfully by AI itself, completing a perfect self-replicating feedback loop. This massive feedback loop pushes the developmental speed of the semiconductor industry to heights far beyond human imagination, hurtling toward a singularity where technological progress begets further progress.
"AI designed to run semiconductors is now designing semiconductors faster, completing a self-replicating feedback loop toward a technological singularity."
5. Segmentation of the Inference Market and the Nature of Custom Strategies
Just as human language branches out endlessly according to eras and contexts, AI application areas are entering a pluralistic era where massive single markets are precisely segmented by purpose and characteristics. The public often misunderstands terms like "AI chip" or "inference chip" as a single homogenous concept, but fierce specialization and division of labor are underway internally. This is why Google develops separate chips hard-coded strictly for specific workloads of particular large language models, alongside its versatile TPUs. Meanwhile, NVIDIA's ecosystem strives to handle all computation types armed with general-purpose flexibility, while systems based on ultra-high-speed networks maximizing ultra-low latency and chips specialized for running massive super-scale models like OpenAI's projects evolve according to distinct survival laws. Such inference segmentation implies a qualitative shift in memory semiconductor demand. Past practices of mass-producing uniform products and pushing them into the market no longer work. Because each client pursues different algorithm characteristics and latency limits, corresponding memory must also evolve into thoroughly customized designs. Through this process, memory suppliers are elevated from mere subcontracted parts makers into sophisticated solution partners capable of fully understanding and supporting clients' special computational purposes, acting as the fundamental driver cementing supplier-friendly pricing power.
6. Facing the New Silicon World in the First Half of Next Year
Just as navigators of the Age of Discovery hoisted sails toward unknown new worlds despite the raging storms of the Atlantic, the upcoming first half of next year will serve as a great arena of opportunity where fear and greed intersect for semiconductor investors. While parts of the market still doubt the peak of the cycle and raise pessimistic views, behind that macroeconomic noise stands the massive rock of a structural realignment in the real economy driven by artificial intelligence. HBM market growth rates are projected to bounce back through base effects into a steep upward slope, and the "invisible war" among major big tech firms to secure premium memory while expanding proprietary chip ecosystems will intensify. Samsung's bold preemptive investments, SK Hynix's solid technological barriers, and the strategic maneuvering of big tech players like OpenAI and Google shaking up the supply chain all prove that the semiconductor industry is not a sunset industry, but the frontline battleground determining humanity's future. Ultimately, the essence of investing lies not in simple numerical aggregation, but in the discernment to read the massive civilizational direction forged by technological flows. Are we truly ready to cast off the spectacles of outdated prejudice and boldly bet on the new map drawn by silicon to become true winners of the coming boom?
This post is based on content from the YouTube channel 이효석아카데미.
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