Extensions to Azure, GCP, AWS & more · hyperscaler demonstrator
AICredit.USDMS · single-file demo · works offline
The AI-Credit flywheel: $100,000 of AICredit.USDMS → $1,000,000 of AI utilization.
Raw compute is a commodity — the margin lives in the AI's intellectual property.
Businesses running AI on Azure keep 70–99% margins (this example: 90%) while compute costs
≤30% today, trending toward 1% as the business matures. When those margins are paid out as
AI credits that re-enter the ecosystem, spend recirculates: A → B → A′ → B → A″ … a geometric
series that converges — and the cloud captures every compute dollar with zero acquisition cost.
Round
A
generation 1
Credits in circulation
$100,000.00
across 7 wallets
Total AI utilization
$0.00
converges to $1,000,000
Azure compute revenue
$0.00
10% of every transaction
IP margins recirculated
$0.00
90% back into credits
Metered volume
0 MTX
1 MTX = 1,000,000 micro-tx
Σ 100,000 × 0.90ⁿ = 100,000 ⁄ (1 − 0.90) = $1,000,000 of AI utilization
· compute captured: $100,000
· IP margins earned: $900,000
[A] AI-Credit walletsAICredit.USDMS
Next-round pool [A′] — margins returning
$0.00
[A] credits ──spend──▶ [B] AI on Azure
└─ 10% → Azure compute · 90% IP margin → [A′] ─┐
▲──────────── credits recirculate ────────────┘
Press Next → to step one transaction
super-slow motion: one MTX thread at a time (1 MTX = 1,000,000 micro-transactions) · or ▶ Play
Azure compute meter (the hyperscaler's take)
$0.00
[B] AI services on Azure11 nodes · 90% IP / 10% compute
// why this makes hyperscalers sticky
Clients don't just rent VMs — they configure A, B, A′, A″…: credit wallets, AI services,
and recirculation rules that live on the platform. Every recirculated dollar is utilization the cloud
would otherwise have to win from scratch; here it returns by construction, round after round, until the
series converges. Train companies and individuals with AI credits instead of raw discounts:
the difference between raw compute and AI compute is the margin — and it stays in the ecosystem.
A $100K credit program at 90% IP margin yields $1M of metered AI utilization and
$100K of compute revenue — while every participating AI business keeps its IP margin.