A precursor to international coordination on AI is that all compute is covered. However, due to the ease of smuggling and the build-out of China's domestic chip manufacturing capabilities, this may be difficult. China may want to hide the data centers, and we will want to find them. What are the different ways they could? And how could we catch them?
In approximate order of difficulty:
Rent and run data centers from overseas. Some firms have used front or shell entities to rent compute from overseas providers. Why does that Canadian businessman need so many H100 hours? H100s are Nvidia’s flagship AI accelerators used for training and serving large models. In Southeast Asia, Malaysia’s Johor region and, to a lesser extent, Singapore have become hubs because of cost, fiber access, and a large Chinese-speaking workforce. Both are tightening oversight: Malaysia is reining in data-center growth and adding stricter permits that complicate access to U.S.-origin AI chips, while Singapore now allocates capacity through a “Green DC” roadmap.
Repurpose existing big-tech servers. Meta amassed large GPU fleets for recommendation systems across Facebook and Instagram, then leveraged them for LLM training (e.g., the Llama series). ByteDance (which owns TikTok) operates large-scale recommender stacks and is developing in-house chips to reduce reliance on Nvidia.
Co-locate in mega-factories. Park GPU racks inside sprawling electronics or battery-gigafactory campuses. Shared switchgear, HVAC, and fiber make the extra load look like industrial process variation. The surrounding industrial profile raises the detection bar.
Repurpose the Bitcoin mining facilities. Bitcoin mining today relies on ASICs, not GPUs, so it isn’t a plug-and-play swap. But many mining sites already have high-capacity power, buildings, and cooling that can be converted to host GPU clusters with networking and interconnect upgrades. Large miners are pivoting capacity toward AI/HPC hosting.
Pretend it is an aluminum factory, or similar heavy industry. Both guzzle enormous power, which can look similar in satellite imagery. Smelters, however, have characteristic air-emission profiles (e.g., SO₂ and fluorides) and extremely high continuous loads, often hundreds of megawatts, which create different signatures than most data centers.
Build it underground. A huge capital and logistical investment—but commercially proven. Underground and bunker data centers exist today, demonstrating feasibility for concealed builds.
What can we do to catch this?
Location tracking. Shipment-level tracking and attestation for export-controlled accelerators has been used in targeted cases. Proposals for stronger on-chip telemetry or universal location mandates exist, but they don’t bind purely domestic Chinese chips. Recent reporting indicates U.S. authorities embedded trackers in high-risk shipments to catch diversions, a tactic that drew public criticism in China.
Intelligence synthesis. If NSA/CIA prioritized covert data-center tracking, they could fuse diverse signals—commercial satellite imagery, thermal-IR heat maps, mobility data, PPAs, hiring and procurement trails, grid logs, and social media—and apply automated analysis. Well-resourced private teams already use OSINT toolkits for satellite-imagery-driven investigations.
Grid-load fingerprinting. Data centers exhibit high load factors and relatively static demand compared to many other large loads; utilities and ISOs can spot flat shapes and frequency-response behavior in telemetry. NILM-style methods and utility studies indicate improving ability to characterize these loads and to flag crypto mining.
Spy on the companies. Large, capital-intensive projects are hard to keep secret. Open-source signals leak: interconnection queues, PPAs, vendor wins, job postings, and permit filings often telegraph locations and timelines. (For methods, see OSINT guides above.)
Overall, I don’t find the argument of “we won’t know whether China has built many secret data centers that may not be subject to our treaty’s rules” very convincing—particularly if we try. Finding data centers is hard, but building them in secret is harder.