AI Infrastructure & Compute
Technical reference for GPU rental markets, data center capacity economics, decentralized compute networks, and AI infrastructure financing structures.
Revenue Models & Economics
Pricing structures, utilization optimization, and market dynamics for GPU compute and data center capacity.
GPU Rental Economics
Spot, reserved, and dedicated pricing models for GPU compute—utilization optimization, provider margins, and market segmentation.
Compute Token Mechanics
Token-based payment systems, staking mechanisms, and rewards structures in decentralized GPU networks like Render and io.net.
Data Center Capacity Markets
Wholesale versus retail colocation pricing, power constraints, and geographic capacity allocation for AI deployments.
Colocation Lease
Data-center contracts for power, cooling, rack capacity, connectivity, and customer-owned AI infrastructure.
Rack Density
Power and compute capacity per rack, and why AI-ready facilities are constrained by more than square footage.
AI Inference vs Training Economics
Cost structures and margin profiles for model training versus inference serving—capital intensity and operational differences.
GPU Utilization Rate
How active usage, reserved capacity, and idle time determine real asset yield.
Take-or-Pay Contracts
Minimum payment commitments that convert volatile usage into financeable contracted revenue.
Power Purchase Agreements
Electricity contracts shaping data center margins, power availability, and price-risk exposure.
Power Usage Effectiveness
Facility efficiency metric showing how much power reaches IT equipment versus cooling and overhead.
Infrastructure Structures & Agreements
Financing mechanisms, hosting agreements, and facility leasing structures for AI infrastructure deployment.
GPU Collateralization
Asset-based lending using GPUs as collateral—advance rates, CoreWeave's $7.5B facility, and liquidation mechanics.
Decentralized Compute Networks
Architecture and economics of distributed GPU marketplaces—Render, io.net, Akash coordination mechanisms and node incentives.
AI Model Hosting Agreements
Revenue sharing structures, SLA requirements, and liability allocation in model deployment contracts.
Hyperscale Data Center Leasing
Triple-net lease structures, power purchase agreements, and economics of 20MW-200MW facilities for AI infrastructure.
Liquid Cooling
Direct-to-chip and immersion cooling systems used to support high-density GPU deployments.
Grid Interconnection
Utility approval, upgrade, and connection mechanics that gate data-center power availability.
Interconnection Queue
The grid-operator and utility pipeline that determines when large data-center loads can connect.
Risk Analysis & Market Dynamics
Hardware depreciation patterns, demand volatility, and capacity planning challenges in AI infrastructure markets.
GPU Refresh Cycle
Hardware replacement and redeployment timelines as newer accelerators change performance and residual value.
Curtailment Risk
Risk that grid constraints, interruptible power, or contract terms reduce usable compute capacity.
GPU Depreciation & Obsolescence Risk
Hardware lifecycle economics and generation transitions—H100 to B200 depreciation curves and residual value analysis.
Compute Demand Volatility
Training surge patterns versus inference steady-state consumption—capacity planning challenges in nascent markets.