Analysis on the infrastructure, engineering, and economics behind modern technology and AI.
Nvidia says one gigawatt of AI data center now costs about $60 billion. Here is the bill line by line: chips, networking, power gear, cooling, the building, and the running costs after it opens.
Amazon, Alphabet and Meta have all gone cash-flow negative on AI spending. Here is who fills the gap: bond investors, private lenders, shareholders, chip suppliers and, in the end, customers.
On November 3, 2026, local voters restricted AI data centers in 33 of the 34 measures counted by the next morning. What was on the ballot, from 25 MW caps to bans, why residents said no, and what it means for the AI buildout.
Why AI data centers are moving to 800-volt DC power: a 1 MW rack at 54 volts needs up to 200 kg of copper and about 18,500 amps. How Nvidia's 800 VDC design works, what it saves, who builds it, and what the grid still has to solve.
Why AI data centers are switching to liquid cooling: how rack power rose from 8 kW to 120 kW, why water moves heat so much better than air, and how direct-to-chip and immersion cooling compare on density and cost.
HBM explained: how stacked high-bandwidth memory works, where figures like 819 GB/s and 1.2 TB/s come from, what the 18.75× HBM-vs-DDR5 comparison really measures, and why memory limits AI hardware.
Understand HBM memory, TSMC CoWoS advanced packaging, and why making compute dies is only one step in delivering Nvidia AI accelerators.
AI cloud specialists sell access to clusters of Nvidia GPUs. CoreWeave shows how long-term capacity contracts can support rapid growth while creating financing, customer, and hardware risks.
ASML's extreme ultraviolet lithography systems turn chip designs into silicon. How the $400 million High NA generation works, why chipmakers consider it, and where the bottleneck lies.
AI data centers depend on transformers, switchgear, liquid cooling, optical links, power electronics, and microgrids. These industrial suppliers may determine how quickly new computing capacity becomes usable.
How do data centers earn money? Operators sell power, space and connections on contracts — Equinix earns over 90% of revenue as recurring fees. See how colocation, hyperscale leases, utilization and financing decide profit.
Microsoft, Google, Amazon, and Meta are moving beyond buying electricity. Their nuclear, geothermal, grid, and power-development deals reveal how energy is becoming a strategic part of the AI business.
Why do AI data centers need so much power? Explore GPU electricity demand, cooling overhead, grid bottlenecks, and a worked electricity-cost example.
AI looks like software, but the machine behind it is physical: chips, servers, networks, cooling, power, land, and capital. A look at who actually profits from the AI infrastructure buildout.