AI Switch Silicon Procurement · Monte Carlo · Nash Equilibrium · Causal Inference
Pay Premium Switch
DISABLED
List price · 90d lead time · Standard queue
DRAM Cost Spike — Q3
Runs 10,000 Monte Carlo scenarios instantly
Simulated Impact
Gross Margin Δ
+0.0%
TTM Saved
—
Nash Strategy
conservative
Alloc. Probability
24%
| Scenario | TH5 — P(Stockout) | TH6 — P(Stockout) | TH5 — Margin | TH6 — Margin |
|---|---|---|---|---|
| OpenAI 1.6T Buildout | 18% MED | 52% HIGH | 32.4% | 30.3% |
| Google Gemini Scale | 14% MED | 44% HIGH | 32.4% | 30.3% |
| Anthropic Claude Infra | 12% MED | 38% HIGH | 32.4% | 30.3% |
| Base Demand | 6% LOW | 18% MED | 32.4% | 30.3% |
| Demand Surge (+2σ) | 31% HIGH | 71% CRIT | 32.4% | 30.3% |
| Supply Crunch | 45% HIGH | 83% CRIT | 32.4% | 30.3% |
ECN Mark Rate (%)
Buffer Utilization (%)
Throughput (Gbps)
ECN Rate
4.4%
Buffer
50%
Throughput
39G
Mean Gross Margin
32.4%
P5: 26.2% · P95: 38.2%
VaR 95% Loss
$1.0M
Max expected downside
Nash Optimal Bid
$19.4K
Strategy: conservative
P(Positive Margin)
96%
Across all scenarios
CausalIQ by netcausal.ai · Demo mode — connect backend at api.netcausal.ai for live data