Ideas
Nvidia locked up logic and memory.
Nvidia has locked up a majority of leading-edge logic and memory supply: it is TSMC's largest customer, is getting roughly 70 percent of N3 wafer capacity by 2027, has signed long-term contracts, and has been far more aggressive than Google or Amazon in signaling demand across PCB, memory, and packaging supply. This lets Nvidia capture margin in a compute-constrained world, and the utility of its installed H100s is rising rather than depreciating.
Memory prices surge as supply lags.
Memory is a major bottleneck: DRAM/HBM/NAND prices are inflecting up, memory vendors are raising prices again, and roughly a third of Big Tech capex may go to memory. No meaningful new fabs arrive until late 2027 or 2028 because memory makers underinvested after losing money in 2023, while AI long context and KV cache demand is absorbing capacity and forcing consumer demand destruction.
TSMC sold out, can prebook capacity.
TSMC is sold out on leading-edge logic for 2026, can only offer incremental 5 to 10 percent to latecomers like Google, and is prioritizing the higher-margin HPC/AI market over mobile. As AI demand explodes, TSMC can force customers to prebook and prepay for capacity while Apple becomes a smaller and less important customer.
Google woke up to AI demand.
Google initially under-allocated AI compute and sold TPU capacity to Anthropic before Gemini demand inflected. Gemini reached about $5 billion ARR in Q4 and management is now aggressively buying energy companies, turbine deposits, powered land, and utility agreements. This AI awakening supports a much more aggressive Google AI buildout.
EUV bottleneck gives ASML pricing power.
By 2028-2029 the ultimate bottleneck for scaling AI compute shifts to ASML EUV lithography tools. ASML can produce roughly 70 EUV tools this year, 80 next year, and only a bit above 100 by end of decade; each gigawatt of Rubin requires about 3.5 EUV tools. No competitor has anything close to EUV and ASML has not raised prices as fast as tool capability, leaving large pricing power and upside in a capacity-constrained market.
China scales indigenous chip production.
China is aggressively building an indigenous semiconductor supply chain and Dylan is quite bullish over five to ten years. By 2030 China should have fully indigenized DUV tools and working EUV tools, with more engineers and state capital than the West, and could scale chip production even if process technology lags. On long AI timelines, China's vertically integrated scale advantage grows.
Memory costs squeeze Apple's iPhone margins.
Apple is squeezed by the memory and NAND price spike because iPhone bill-of-materials costs are rising by roughly $100 to $150 and consumers may not fully absorb higher prices. At the same time, Apple is becoming a smaller part of TSMC and is being crowded out of leading-edge capacity by AI/HPC chips, reducing its favorable supply-chain position.
Memory costs crush low-end phone makers.
The memory cost spike is crushing low- and mid-range smartphone makers with thin margins and no long-term memory agreements. Xiaomi and Oppo are already cutting low-end and mid-range smartphone volumes by half, and smartphone volumes could fall from about 1.1 billion to 500 to 600 million next year as memory costs consume the bill of materials.
Power equipment orders surge, supply scales.
Power is not the ultimate scaling bottleneck. The gas turbine and power equipment complex has huge data center orders; GE Vernova, Mitsubishi, and Siemens turbine capacity has been locked up by early movers who can now charge excess returns, and behind-the-meter gas, aeroderivatives, ship engines, and reciprocating engines can together add hundreds of gigawatts by the end of the decade.
Bloom fuel cells scale fast.
Bloom Energy fuel cells are a behind-the-meter power solution for data centers. SemiAnalysis has been positive on Bloom for a year and a half because its production payback period is very fast and it can increase production quickly, even though fuel cells are more expensive than combined-cycle gas turbines.
This Dwarkesh Patel video, published March 13, 2026,
features Dylan Patel
discussing NVDA, 005930.KS, 000660.KS, MU, TSM, GOOG, ASML, CHIK, AAPL, 1810.HK, ENR.DE, 7011.T, GEV, BE.
10 trade ideas extracted by AI with direction and confidence scoring.
Speakers:
Dylan Patel
· Tickers:
NVDA,
005930.KS,
000660.KS,
MU,
TSM,
GOOG,
ASML,
CHIK,
AAPL,
1810.HK,
ENR.DE,
7011.T,
GEV,
BE
