AI Chips: why they cost as much as a car, and why companies can't get enough

AI chips sit at the center of modern AI progress: specialized accelerators (Nvidia Blackwell/Hopper, Google TPU, Amazon Trainium, Huawei Ascend) are designed by a few firms but mostly fabricated by TSMC, with critical upstream suppliers such as ASML (EUV) and HBM vendors Samsung, SK Hynix, and Micron. By Q4 2025 roughly 20 million AI chips had been shipped by the five largest designers, with Nvidia supplying ~50% of units and >66% of deployed compute capacity. Metrics matter more than sticker price: although flagship chips rose from $5,700 (2016) to $34,000 (2022), computation per dollar improved dramatically (H100 ≈17× P100), and compute-per-dollar has doubled ~every 2.5 years. Chips consume ~1,000 W each and total datacenter power reached tens of gigawatts by late 2025; energy efficiency has improved ~40% annually, but aggregate electricity use still grows because deployment outpaces per-chip gains.