It’s hard to overstate just how valuable and convenient a portable generator can be. They can provide emergency backup power during an outage or blackout or make a camping trip a lot more comfortable. They can even potentially save lives in times of catastrophic power grid failure. Whole-home generators have become increasingly popular over the years as well, with Consumer Reports saying they can potentially increase the value of your property between 3% to 5%. All that aside, generators also pose an inherent safety risk if not installed or used properly.
According to the United States Consumer Product Safety Commission, about 100 people a year die from non-fire related carbon monoxide poisoning associated with portable generators. Portable generators continue to be the most dangerous fuel-burning consumer product on the market as it relates to carbon monoxide poisoning –- even more so than gas-powered furnaces or stoves. While portable generators and other gas-powered tools should never be operated indoors, simply placing them outside isn’t enough — they need to be at least 20 feet away from your home.
The generator 20-foot rule helps protect against carbon monoxide poisoning
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When using a portable generator, maintaining a minimum of 20 feet from the home is of paramount importance. This may not be guidance you’ll see from a generator manufacturer, but both the CDC and the US CPSC recommend it. As critical weather events continue to rise alongside the world’s drastically changing weather, carbon monoxide related deaths and injuries usually crop up in their wake. The February 2021 winter storm (Winter Storm Uri) that left millions without power in Texas also resulted in what many experts believe is the worst carbon monoxide poisoning event in years, as desperate people made dangerous home heating mistakes in a bid to keep warm.
Some state governments –- like Texas –- have not formally required CO alarms by law in the past, but after the 2021 storm and epidemic of carbon monoxide poisoning that followed, renewed interest and scrutiny into protecting people from carbon monoxide has sparked some amount of reform. The federal government has known about the CO hazards generators pose for years, and the CPSC has required warning labels on them since 2007, in hopes of curtailing carbon monoxide related deaths. However, the warning labels were never intended to replace greater federal regulation, which has categorically failed over the years as the generator industry continues to mostly regulate itself.
How to protect yourself while using portable generators
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Until such a time that greater laws exist to help protect and educate consumers, when using a portable generator, you need to be your own first line of defense. That starts with making sure you have CO alarms in your home. The National Fire Protection Agency calls for CO alarms to be installed in a centralized location outside of bedrooms, on every floor of the home, and anywhere else as applicable by state and local codes. CO alarms should be tested monthly and interconnected, if possible. In the absence of hardwired alarms, there are wireless options available.
When it comes time to shop for a portable generator, opt for one that has an integrated shut-off switch that will kill the generator if high carbon monoxide levels are detected. Many generator makers have started using this technology, like Harbor Freight’s Predator series and its CO Secure feature. However, not all generator brands do, and there is no legal requirement for them to do so –- shop accordingly.
No matter what the product manual says, the safest thing is to set the generator up at least 20 feet from the property; a heavy duty power cord can be used to close the distance. Set the generator up on a stable, non-flammable surface, and try to keep it out of the elements –- by using some type of open, canopy-like structure. Under no circumstances should you backfeed your electrical system with a “suicide cord” or similar option. If you don’t have an interlock or a transfer switch, you need to use an extension cord to plug in your load(s) directly into the generator. If anything prevents you from using a generator safely, then you should not use one.
Europe would like digital sovereignty to be a jurisdictional problem. It would be much easier for EU bureaucrats if the path to frontier AI ran through Brussels, could be secured by certification, and depended mainly on where a given cloud provider is incorporated. Unfortunately, the binding constraints are less cooperative: GPUs, chips, memory, power, capital, and the inconvenient fact that much of the relevant capacity is already spoken for.
On May 27, after repeated delays, the European Commission is expected to unveil the Cloud and AI Development Act (CAIDA), the centerpiece of its broader “Tech Sovereignty” package. In a new International Center for Law & Economics (ICLE) issue brief published today, I argue that the stricter versions of CAIDA favored by some stakeholders would impose most of their costs on European users, businesses, and public institutions. The package’s implied objective—legal immunity from non-European Union legal systems accessing EU data—is also unlikely to be achievable in practice.
The empirical backbone of the brief comes from SemiAnalysis’ research on the artificial-intelligence infrastructure market. Their numbers, more than the political messaging surrounding the package, make the clearest case against a categorical version of CAIDA.
This post puts those numbers front and center, while pointing readers to the full brief for the legal and policy analysis that follows from them.
The Market Did Not Wait for Europe
Three market realities all point to the same uncomfortable conclusion. None is something the EU can plausibly change fast enough to matter during this regulatory cycle.
Sovereignty Is Not a Compute Cluster
First, Europe does not host the top tier of rentable artificial-intelligence compute infrastructure. SemiAnalysis’ April 2026 “ClusterMAX 2.1” ranking evaluates graphics-processing-unit (GPU) cloud providers on the operational metrics that actually matter for frontier-AI development: how reliably a cluster performs useful work, and how quickly customers can deploy large-scale training jobs.
Across the entire Platinum-through-Silver range—the only tiers where serious frontier-model work happens consistently—the EU accounts for just three providers: Scaleway (France), Gcore (Luxembourg), and Nebius. Nebius, moreover, exists in its current form only because of the 2024 corporate split from Yandex, the Russian technology company.
GPU cloud providers in each tier of SemiAnalysis ClusterMAX 2.1 (April 2026), grouped by country of headquarters. The EU band (highlighted) contains one Gold-tier provider (Nebius, the post-Yandex Dutch entity), one Silver-tier provider in France (Scaleway) and one in Luxembourg (GCORE), and the rest in “Not Recommended.” Country-of-origin classification mine, not SemiAnalysis’s.
Cross-reference those rankings with the Cloud Sovereignty Framework procurement the European Commission completed last month: €180 million over six years, evaluated under the Commission’s Security and Eligibility Assurance Levels (SEAL) framework for legal and operational sovereignty. Only one of the four winning “sovereign” providers ranks in ClusterMAX’s top three tiers.
To be fair, SEAL and ClusterMAX are measuring different things. That is precisely the problem. A provider can score highly on legal sovereignty while performing poorly on the operational metrics that determine whether advanced AI systems can actually be trained and deployed effectively.
The Bottleneck Is a Cleanroom, Not a White Paper
Second, the semiconductor and memory supply chains are already effectively locked in. SemiAnalysis’ “Great AI Silicon Shortage” analysis finds that nearly every major AI-accelerator family has converged on Taiwan Semiconductor Manufacturing Co.’s (TSMC) N3 manufacturing process. AI demand is projected to consume 86% of N3 wafer output by 2027, with effective utilization exceeding 100% in the second half of 2026.
The bottleneck is not money. It is cleanroom capacity, which takes years to build.
The memory market tells a similar story through a different mechanism. SemiAnalysis describes a “once-in-four-decades” high-bandwidth-memory (HBM) supercycle, dominated by just three suppliers worldwide: Samsung, SK Hynix, and Micron. Customers are already signing long-term agreements backed by prepayments simply to secure future allocation.
None of these constraints responds, on any meaningful timeline, to directives from Brussels or the capitals of EU member states. Industrial policy cannot conjure advanced semiconductor fabs out of thin air—at least, not before this regulatory cycle ends.
You Are Not Outbidding Anthropic
Third, the rental market is already sold out, and frontier-AI customers are not about to be outbid. SemiAnalysis’ “Great GPU Shortage” analysis reports that on-demand GPU rental capacity is exhausted across both Nvidia’s Hopper and Blackwell architectures. Capacity scheduled to come online through August and September 2026 is already fully booked.
Prices reflect that scarcity. The H100 one-year contract-price index rose from $1.70 per GPU-hour in October 2025 to $2.35 by March 2026—a roughly 40% increase in just five months for what is now effectively a previous-generation chip.
Meanwhile, Hopper contracts originally due to expire this year are being renewed at the same rates customers agreed to two or three years ago, with terms extended through 2028.
Why are buyers willing to commit at that scale? Because the economics of frontier models have detached from the rest of the market. SemiAnalysis reports that Anthropic’s annualized revenue grew from roughly $9 billion at the end of 2025 to more than $44 billion by spring 2026. During the same period, inference gross margins rose from below 40% to above 70%.
A European entrant into this market—“sovereign” or otherwise—does not arrive as a market-maker. It arrives as a price-taker.
The Price of Sovereignty Is Paid by Users
If those three facts hold, then a version of CAIDA that pushes European users away from non-EU compute providers and application-programming interfaces (APIs) would not create meaningful European capability fast enough to matter during this regulatory cycle. It would, however, raise costs and reduce the quality of the AI systems European users can actually deploy.
Those costs vary by workload, which is worth unpacking separately.
SemiAnalysis’ “Cluster Total Cost of Ownership” methodology estimates that a Silver-tier cluster carries roughly 15% higher total cost of ownership than a Gold-tier cluster for a representative large-language-model (LLM) pretraining workload, even assuming identical GPU-hour pricing.
For any European lab trying to compete at the frontier, that translates into a research-velocity penalty measured in months of engineering time.
Inference workloads—the process by which trained AI models generate outputs for users—look somewhat different. There, the same methodology places the equal-priced Gold-versus-Silver gap below 1%. As the brief explains in greater detail, frontier-model training and frontier-model access through APIs bear sovereignty-related costs differently.
For European businesses and public institutions using Claude, GPT-5, or Gemini through an API, the binding sovereignty constraint is not where a request physically lands. It is whether users retain legal access to the API at all. That is the layer at which most European users actually encounter frontier AI.
The broader problem, developed at length in the brief, is that the categorical approach does not even deliver the legal immunity it implicitly promises.
The “immunity from non-EU law” standard embedded in the European Cybersecurity Certification Scheme for Cloud Services (EUCS) High+ framework assumes that EU headquarters and EU-based data processing sufficiently shield data from the reach of foreign legal systems. Canada’s King v. OVHcloud case is the live counterexample.
In September 2024, the Ontario Court of Justice issued a production order requiring OVHcloud to disclose subscriber data stored on servers in France, the United Kingdom, and Australia. The appeal remains pending.
That the most prominent extraterritorial production order of the past 18 months targeted Europe’s flagship sovereign-cloud provider, involving EU-hosted data, should weigh more heavily in this debate than it has so far.
Digital Sovereignty Is Not Autarky
At the EU level, CAIDA should take a risk-based rather than categorical approach, while preserving member-state subsidiarity for genuinely stricter public-administration requirements, instead of turning them into a single-market default. The genuinely narrow category of residual extraterritorial-risk concerns can already be addressed through Article 9 of the General Data Protection Regulation (GDPR), tailored national-security exceptions, and the proportionality principles that govern public-sector procurement more broadly.
The “build” side of the agenda—where European policymakers actually have leverage—looks very different. It runs through corporate-law reform, financial-single-market integration, and faster, harmonized permitting for data centers and electric-grid expansion.
The European Commission’s proposed “EU Inc.” framework belongs in that conversation, although its current drafting risks dilution through excessive deference to member-state legal autonomy—the same pattern I have criticized in earlier work.
The Commission’s own Joint Research Centre captured the core point with unusual bluntness for a JRC paper: “digital sovereignty cannot be equated with autarky.”
I will return to the package, the Council negotiations, and the EUCS High+ debate as the implementing acts come into view. For now, the key point is simpler than much of the rhetoric surrounding “AI sovereignty” suggests.
Europe’s binding constraints are silicon, capital, power generation, and its own hesitation to enact the corporate-law reforms its technology sector has requested for years—not jurisdiction.
A categorical CAIDA would not change those constraints. It would mostly change who pays for them.
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