Bernie Margulies
CEO, American Compute
Bernie leads program business at American Compute. His background spans technology investment, insurtech leadership, and underwriting for emerging asset classes. Previously held C-suite and senior roles at venture-backed insurance and technology companies.
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Who Has NVIDIA's Blackwell GPUs: Market Size & Fragmentation (Q2 2026)
A market-level breakdown of who bought, deployed, and clustered NVIDIA's 3.2 million Blackwell GPU packages through the end of 2025, with segment allocation, named mega-clusters, and forward projections through 2027.
The GPU Black Market that Washington Can't Shut Down
The U.S. banned AI chip exports. Billions still reached China — moved by shell companies, Southeast Asian middlemen, and operators gaming the system.
Where Data Centers Are Built in the U.S. and Why
The history of US data centers from military bunkers to AI megacampuses, and why ten states, led by Virginia, Texas, and Georgia, dominate new construction.
Compute Offtake Agreements
How compute offtake MSAs work from the seller’s perspective: contract structure, pricing models (Reserved Instances, Bulk Credits, on-demand), payment enforcement, SLA exposure, liability caps, termination economics, and customer restrictions. Based on CoreWeave’s public MSAs with Microsoft, OpenAI, Meta, and NVIDIA, plus HPE/Soluna and NVIDIA DGX Cloud terms.
What AI Infrastructure Lobbyists Are Fighting Over
Federal lobbying filings mentioning "data center" grew 7x between 2021 and 2025. Utilities, construction contractors, regional coalitions, and foreign AI startups are all filing alongside tech companies on grid cost allocation, permitting speed, energy policy, and tax treatment.
How to Finance a GPU Cluster
The practical guide to financing a GPU cluster at the $5M-$100M scale. How to structure the deal, why utilization determines your terms, and how to layer equity, senior debt, and mezzanine to close the capital stack.
GPU Tech Refresh: When to Upgrade Your AI Cluster
H100 rental rates rebounded 40% to $2.35/hr. Blackwell is sold out through September 2026. For a 256-GPU fleet: holding generates $6.6M in 3-year net cash, a full B200 refresh produces $2.3M after debt service on $3.5M equity.
Total Cost: Owning vs Renting GPU Clusters
A 256-GPU B200 cluster costs $2.31/GPU/hr to own, $2.50/GPU/hr on a long-term reserved contract, and $3.00/GPU/hr on-demand. Ownership wins when utilization stays high (above ~70%), otherwise you are paying for capacity you are not using.
What Is an AI Factory, and Why Is NVIDIA Franchising Them Out
An AI factory is just a data center full of GPUs. NVIDIA coined the term to sell complete factory configurations, from chips to full data center blueprints, bundled with $4,500/GPU/year software licensing. The model is closer to McDonald's franchising than component sales.
Why Compute Is Not a Commodity
GPU compute is not fungible. Even identical GPU models trade at 2-8x price spreads depending on networking, location, and provider. Commodity exchanges require standardized grading that compute lacks. Financial products for compute work when structured like infrastructure bonds, not futures contracts.
The Modular Data Center Opportunity
Power scarcity is pushing AI infrastructure toward networks of small, modular data centers in remote locations. Finding 2-5 MW takes months. Finding 500 MW near a metro takes years. Modular deployment has precedent in oil refining, LNG, and nuclear, and NVIDIA is formalizing it through its AI factory franchise with Bechtel.
Who Is Building Compute and Why Is It So Lucrative
Private equity firms, family offices, and entrepreneurial operators are building sub-$100M inference GPU clusters. Locked-in offtake agreements and GPU-backed debt make 2-3x MOIC achievable over a 3-5 year hold.
AI Cluster Cost Breakdown: OpEx, TCO, and Payback (2026)
Operating costs for AI clusters: power, cooling, colocation, staffing, licensing, maintenance, and total cost of ownership across different deployment scenarios.
Insurance for GPU Clusters
Four types of coverage protect a GPU cluster: all-risk property insurance, transit insurance, an OEM warranty, and residual value insurance. What each covers, how pricing works, and why standard business policies leave most of the hardware value unprotected.
How to Read Colocation Contracts for GPU Clusters
A colocation contract is a license to place equipment, not a lease. The provider can pass through power cost increases, cap its own liability at three months of fees, take a security interest in your GPUs, and charge you the full remaining term if you leave early. Here is how to read the clauses that matter for GPU deployments.
Best OEMs for AI GPU Servers: Tier List (2026)
Every AI server runs the same NVIDIA silicon. The OEM you buy from determines pricing, lead times, and support. Dell, Supermicro, HPE, Lenovo, Cisco, Gigabyte, ASUS ranked and compared, plus the Taiwanese ODMs that actually build them.
Bare Metal for AI Compute
Bare metal means renting a physical server with no virtualization layer. For GPU compute, bare metal is becoming the default because the hardware is the product, cloud premiums don't justify themselves at full utilization, and AI coding tools let any team build its own stack.
How to Underwrite AI Infrastructure Investments and Why GPU Financing Fails
Demand is easy to secure for AI infrastructure as of 2026. The real risk is deployment: power, permitting, construction, and hardware delivery. Here is how to evaluate schedule risk for data center builds and GPU cluster rollouts.
GPUs as Loan Collateral
What makes good collateral, how GPUs compare to aircraft, railcars, and other established asset classes, and what lenders should evaluate when underwriting GPU-backed loans.
Private Credit and Asset-Backed Securities for GPU Financing
How private credit, ABS, and SPVs became the primary funding mechanism for AI infrastructure. History from Ginnie Mae to GPU-backed bonds, with aircraft and taxi medallion precedents.
Data Center Tiers Explained
What data center tiers actually measure, how certification works, the history of the Uptime Institute standard, notable fraud cases, and what tiers miss about AI workloads.
AI Data Center Stakeholders
Every stakeholder in an AI data center project: power providers, lenders, colos, OEMs, VARs, brokers, consultants, ITADs, and more. Three project lifecycles show how they assemble differently for hyperscalers, neoclouds, and enterprises.
When a GPU Dies in Production
How GPU failures are detected, what causes them, what they cost in training and inference, and the full replacement workflow from RMA to validation.
AI Cluster Cost Breakdown: CapEx (2026)
What goes into the Bill of Materials for an AI cluster: GPU servers, InfiniBand networking, storage, infrastructure, and real BOMs at 16-GPU, 576-GPU, and 24,576-GPU scale.
Where to Buy GPU Servers
OEMs, brokers, used vs refurbished, warranties, and what to check before you write a $200K+ check for GPU hardware.