AI & Semiconductors
The AI investment boom, chip supply chains, NVIDIA's dominance, and the infrastructure race defining the next computing cycle.
Current Situation
Last updated: August 01, 2026
The semiconductor sector experienced a violent valuation correction this week, transitioning from a risk-on posture to a steep decline as investors questioned the sustainability of AI spending. Massive liquidations hit Asian chip indices, with SK Hynix and Samsung Electronics shares falling 14% and 13.4% respectively. Despite this volatility, fundamental demand remains extreme; Samsung reported a 250-fold profit increase in its semiconductor arm and warned that supply shortages will persist through 2028. This supply-demand imbalance is further evidenced by NAND unit prices rising 70% in Q1 and Qualcomm implementing double-digit price increases.
Strategic alliances have scaled to historic levels, marked by a $500 billion AI initiative between Nvidia and SK Group and a $200 billion memory agreement between Samsung and Broadcom. Nvidia is further deepening its infrastructure role, negotiating a $250 billion financial guarantee for OpenAI's Ohio data center campus and investing $5 billion in Ilya Sutskever's Safe Superintelligence. Meanwhile, the US is attempting to localize production with the first "Made in USA" GB300 chips rolling off lines, and TSMC has accelerated its 1.4nm production timeline to 2028.
Geopolitical friction is intensifying as the sector bifurcates between US-led consolidation and Chinese resilience. China's CXMT achieved the second-largest IPO in Chinese history, raising $9.8 billion with a 472% debut surge, while Huawei expects to double its AI chip shipments to 1.5 million this year. However, legal risks are mounting for Nvidia following the detention of an employee by Taiwanese prosecutors over alleged AI accelerator smuggling into China. Additionally, a critical bottleneck has emerged in advanced packaging, according to the CEO of AT&S.
Investment implications have shifted from a broad AI trade to a bifurcated "monetization" play. Microsoft saw its biggest daily gain in 18 years driven by 43% Azure revenue growth, while Meta faced downgrades and an 8% share drop due to declining free cash flow and high capital intensity. The memory market is moving toward a minimum-pricing model, with Samsung allocating 60-70% of capacity to long-term agreements. This suggests a shift where the primary investment risk is no longer demand-side, but rather the capacity of the supply chain to meet hyperscaler requirements.
Key variable to watch: Whether the current valuation correction stabilizes or triggers a wider liquidity crisis for levered AI funds following the 67% July plunge of Situational Awareness.
Background
The Semiconductor Foundation
Semiconductors are the foundational technology of the modern economy — every digital device, every AI model, every modern weapon system runs on silicon chips. The industry is characterised by extreme capital intensity (a leading-edge fab costs $20–30 billion to build), rapid technological change (Moore's Law has driven roughly 2x transistor density every two years for six decades), and massive economies of scale (the cost per chip falls dramatically with volume). These economics produce natural oligopoly: only a handful of companies globally can manufacture the most advanced chips, and fewer still can design them.
The AI boom of 2023–26 has made the semiconductor sector the most strategically important industry in the world, displacing oil as the resource most central to both economic and military power. This has transformed the US-China chip war — previously an economic dispute — into an existential national security contest.
The Supply Chain
The semiconductor supply chain spans design (primarily US), equipment (US, Netherlands, Japan), materials (Japan, Taiwan, South Korea, Germany), and fabrication (Taiwan, South Korea, increasingly US). The extraordinary geographic concentration — Taiwan's TSMC produces ~90% of leading-edge chips — is the single largest concentration risk in the global technology economy.
Design: US dominates. NVIDIA designs the H100/H200/B200 AI accelerators that power every major AI training cluster. AMD is the second GPU player. Intel, Qualcomm, Broadcom, and Apple design their own chips. ARM Holdings (UK, Softbank-owned) provides the processor architecture used in virtually every mobile chip. The US controls the intellectual property layer of the industry.
EDA Software: Electronic Design Automation — the software used to design chips — is controlled by three US companies: Synopsys, Cadence, and Mentor Graphics (Siemens). Without EDA software, modern chip design is impossible. EDA export controls can prevent Chinese companies from designing advanced chips.
Equipment: ASML (Netherlands) is the sole producer of EUV (extreme ultraviolet) lithography machines required to manufacture chips below 7nm. Applied Materials, Lam Research, and KLA (all US) produce the deposition, etching, and inspection equipment needed alongside EUV. Japan's Tokyo Electron and Screen Holdings are also critical. Equipment is the primary chokepoint the US and Netherlands use to prevent China from reaching the leading edge.
Fabrication: TSMC (Taiwan) is the world's most important manufacturer, producing chips for Apple, NVIDIA, AMD, Qualcomm, and most other fabless designers. Samsung (South Korea) is second at the leading edge. Intel is attempting a foundry comeback. Both TSMC and Samsung have begun building fabs in the US (Arizona, Ohio), Japan, and Germany under government subsidy programmes (US CHIPS Act, EU Chips Act).
The AI Compute Race
The 2022–26 period has been defined by an unprecedented surge in demand for AI compute, driven by the scaling of large language models (LLMs) and their derivatives. GPT-4, Claude, Gemini, Llama — all require massive training compute, and inference (running the models) creates ongoing hardware demand at scale.
NVIDIA has captured the AI accelerator market with extraordinary dominance — roughly 80–90% market share in data centre AI GPUs. The H100, H200, and Blackwell (B200) architectures have sold out immediately upon production, with lead times stretching 6–12 months. NVIDIA's gross margins (~75%) and pricing power are historically unusual for a hardware company. AMD's MI300X and Intel's Gaudi are the primary challengers, though both are meaningfully behind in performance-per-dollar.
Hyperscalers (Microsoft/Azure, Amazon/AWS, Google/GCP, Meta) are spending $50–100B+ annually on AI infrastructure capex, the bulk of which goes to NVIDIA hardware. Custom silicon (Google's TPU, Amazon's Trainium/Inferentia, Meta's MTIA, Microsoft's Maia) is growing but has not yet meaningfully displaced third-party GPU demand.
The US-China Chip War
US export controls on advanced chips and chip manufacturing equipment to China began under the Trump administration (2020 Huawei restrictions) and were dramatically expanded by the Biden administration in October 2022. The controls target chips above a certain performance threshold and equipment capable of manufacturing below 14nm.
China's response has been an aggressive state-backed effort to achieve semiconductor self-sufficiency. SMIC (Semiconductor Manufacturing International Corporation) is the national foundry champion; Huawei has developed its own advanced chip (the Kirin 9000s, manufactured by SMIC at 7nm — a significant technical achievement given the export controls). The Chinese government has poured hundreds of billions into the "Big Fund" industrial policy to accelerate domestic development.
The technology gap remains large: TSMC's current leading edge is 3nm/2nm; SMIC's maximum demonstrated is 7nm, achieved through creative use of older DUV equipment in multi-patterning processes. Closing this gap without EUV access is technically difficult but not impossible given sufficient time and investment.
Historical Context
1958–1970s — Invention of the Integrated Circuit: Jack Kilby (Texas Instruments) and Robert Noyce (Fairchild) independently invented the integrated circuit in 1958. Intel was founded in 1968 by Noyce and Gordon Moore, who articulated Moore's Law in 1965.
1980s — Japan's Challenge: Japanese semiconductor manufacturers threatened US dominance in memory chips in the 1980s. The Reagan administration imposed semiconductor trade restrictions on Japan — an early precedent for the current US-China dynamic. Japan retreated from DRAM and logic chips; South Korea (Samsung, SK Hynix) emerged as the dominant memory player.
1987 — TSMC Founded: Morris Chang founded TSMC in Taiwan, pioneering the "fabless" model — companies could design chips without building fabs, with TSMC manufacturing for them. This model produced the modern semiconductor landscape.
2022 — US Export Control Escalation: The Biden administration's October 2022 chip controls were the most sweeping export restrictions since the Cold War. They banned export of advanced AI chips (above A100 class) and manufacturing equipment to China.
Market Exposure
NVIDIA (NVDA): The defining stock of the AI era. Data centre GPU revenue grew from ~$3B in 2022 to ~$90B in fiscal 2025. Valuation has been volatile but has tracked the AI investment thesis. Key risks: China export restrictions (China was ~20% of data centre revenue before controls), AMD/custom silicon competition, potential overbuilding of data centres.
TSMC (TSM): The foundational infrastructure play — virtually every AI chip requires TSMC's advanced nodes. Taiwan geopolitical risk is an inherent discount in the stock. TSMC's Arizona fabs provide partial geographic hedge but will not match Taiwan capacity for years.
ASML (ASML): The EUV monopoly. Every leading-edge chip fab in the world requires ASML machines. Sales to China have been progressively restricted. The backlog of EUV orders extends years; the company is effectively supply-constrained.
AMD, Broadcom, Marvell: AI semiconductor beneficiaries beyond NVIDIA. AMD's MI300X competes in AI training; Broadcom (AVGO) and Marvell (MRVL) design custom ASIC chips for hyperscaler internal compute.
Memory / HBM complex — Micron (MU), SK Hynix, Samsung, Kioxia, SanDisk (SNDK), Western Digital (WDC): High-bandwidth memory is the binding constraint on AI accelerator production — every H100/B200-class GPU needs stacked HBM, and SK Hynix, Micron, and Samsung are the only three suppliers. DRAM/NAND pricing cycles now move with AI capex rather than the traditional consumer-electronics cycle. Kioxia, SanDisk, and Western Digital carry NAND-side exposure to inference storage demand.
Intel (INTC) and ARM: Intel is the US-domestic-foundry policy bet (CHIPS Act money, export-control tailwinds) more than an AI-compute leader — its foundry buildout is the key variable. ARM licenses the CPU architecture in nearly every AI server head-node and edge device, giving it royalty leverage on unit growth across the whole complex.
ETFs / adjacents: SMH (VanEck Semiconductor) is the standard sector basket expression. AI data-centre adjacents trade as high-beta derivatives of the same capex cycle — Dell (DELL) on AI servers, CoreWeave (CRWV) and Nebius (NBIS) on GPU cloud capacity.
US vs Chinese Chip Stocks: SMIC, Hua Hong, and other Chinese foundries trade at significant discounts to Western peers, reflecting technology gaps and sanctions risk. They are the "China semiconductor independence" bet — high risk, uncertain timeline.