This interview says AI token demand is exploding, and only the most advanced models are wanted, with people willing to pay almost anything. Dylan Patel thinks supply bottlenecks (like memory and chip factories) will keep widening the gap, boosting profits for model labs like Anthropic. Key holdings: Anthropic (its new model Mythos is a huge leap, revenue jumped from $9B to $35-40B); TSMC (chip maker, capex may hit $100B by 2028); DRAM makers (memory prices could double or triple due to slow capacity growth).
Dylan Patel discussed the explosive growth in the supply and demand of AI tokens during the program. On the demand side, frontier models are the only ones widely needed, with virtually no upper limit on willingness to pay. His company SemiAnalysis has seen AI spending surge from tens of thousands of
Dylan Patel (Founder & CEO of SemiAnalysis, analyst of semiconductor supply chain and AI infrastructure) discusses with host Patrick O'Shaughnessy the explosive growth in AI token supply and demand. Dylan Patel's core judgment is that AI token demand has "completely exploded," frontier models are the only widely needed product, and willingness to pay is nearly unlimited. However, supply-side bottlenecks (memory, logic chips, fab equipment) will determine the pace of scaling — and this supply-demand gap will continue to widen, driving up profit margins for model labs.
Dylan Patel believes that demand for AI tokens is experiencing unprecedented explosive growth, with his own company's experience serving as a microcosm.
Dylan Patel emphasizes that the market only wants the most advanced models, and Anthropic's "Mythos" represents the biggest capability leap in two years.
Dylan Patel argues that supply-side bottlenecks are the key factor determining the pace of AI expansion, and these bottlenecks are more persistent than the market expects.
| Supply Side | Current Status | Key Data |
|---|---|---|
| DRAM | Capacity growth constrained | 20-30% annual growth, incremental capacity arrives in 2028 |
| TSMC CapEx | Continuously raised | ~$57 billion in 2025, potentially $100 billion by 2028 |
| GPU (H100) | Prices rising, lifespan extended | 3-4 year old clusters renewed for 3-4 years, lifespan may reach 7-8 years |
| Copper foil/PCB materials | Completely sold out | Prepayment required to secure supply |
Dylan Patel predicts large-scale anti-AI protests within the next three months, and AI industry leaders are exacerbating the problem.
| Position | Guest Sentiment | Key Data |
|---|---|---|
| Anthropic | Bullish (leading position) | Revenue from $9B → $35-40B ARR; gross margin at least 72%; Mythos model capability is the biggest leap in two years |
| OpenAI | Neutral (lagging but still has advantages) | Has massive computing resources (Oracle, CoreWeave, SoftBank, Microsoft, Amazon); "Even second-tier labs will sell out their tokens" |
| NVIDIA | Bullish (hardware layer) | Gross margin 75%+; H100 price rising, useful life extended to 7-8 years |
| TSMC | Bullish (but not fully capturing value) | CapEx ~$57B in 2025, potentially $100B by 2028; only single-digit price increases rather than triple-digit |
| DRAM Manufacturers | Bullish (prices will double or triple) | Capacity grows 20-30% annually, incremental capacity not arriving until 2028 |
| ASML | Bullish | Completely sold out, needs Carl Zeiss to expand capacity |
| Lam Research / Applied Materials | Bullish (downstream beneficiaries) | TSMC CapEx growth will create a "bullwhip effect" |
| FPGA Manufacturers | Bullish | Each next-gen AI rack requires 120 FPGAs |
| CPU Manufacturers | Bullish | Reinforcement learning environments and deployment applications have led to CPUs being completely sold out |
1. Dylan Patel: Demand for AI tokens is "completely exploding," and frontier models are the only ones needed. Evidence: SemiAnalysis’s own AI spending surged from tens of thousands of dollars to $7 million (exceeding 25% of payroll); Anthropic’s gross margin jumped from 30%+ to 72%+, proving willingness to pay is nearly unlimited.
2. Dylan Patel: Mythos represents the largest model capability leap in two years. Evidence: Anthropic advanced from an L4-level software engineer to L6-level within two months; the model is deliberately not widely released, offered only to specific clients—"they are concerned about the impact on the world."
3. Dylan Patel: DRAM prices will double or triple from here. Evidence: Capacity grows only 20-30% annually, with incremental capacity not arriving until 2028; the only way to "steal" capacity is through demand destruction via higher prices.
4. Dylan Patel: TSMC’s CapEx could reach $100 billion by 2028. Evidence: Current CapEx has been raised from $56 billion to $57.4 billion; the downstream supply chain will experience a "bullwhip effect"—demand is amplified at each stage.
5. Dylan Patel: GPU service life is severely underestimated. Evidence: 3-4 year old Hopper clusters are being renewed for another 3-4 years; A100 clusters are being renewed for several years; service life may reach 7-8 years rather than the market’s assumed 5 years.
6. Dylan Patel: Large-scale anti-AI protests will emerge in the next three months. Evidence: AI is more unpopular than ICE and politicians; a Molotov cocktail was thrown at Sam Altman’s home while social media cheered; the public behavior of AI leaders has intensified public fear.
7. Dylan Patel: If you do not use more tokens and create value from them, you will never escape the "permanent underclass." Evidence: There are three distinct problems—using more tokens, creating value from tokens, and capturing value from the created value; "AI is still not table stakes, so act now."
8. Dylan Patel: Model lab profit margins will continue to expand until the hardware supply chain realizes it can raise prices. Evidence: The economic value of frontier models is growing faster than the supply capacity of infrastructure; the supply-demand gap continues to widen, giving labs pricing power.