On-Device AI in 2026: NPUs, Local Models, and What Still Needs the Cloud
Hero: phones and PCs now carry dedicated neural silicon for private, low-latency inference. For most of the generative AI boom,...
How Distributed AI Superfactories Stretch the Network Between Campuses
Figure 1. A multi-campus AI network turns separate power-constrained halls into one logical superfactory—if the interconnect can keep collectives predictable....
The Texas AI Factory Race: Why Hyperscalers Are Betting Tens of Billions on One State
Drive west out of Abilene and the scrubland gives way to something that did not exist three years ago: a...
Power, Water, and Local Pushback: The Hidden Constraints on AI Campuses
Chip supply, model rankings, and capital expenditure dominate AI headlines. On the ground, a quieter set of constraints is deciding...
Can Nuclear Power AI in Time? SMRs, Large Reactors, and the 2030 Gap
Hyperscale AI campuses are being planned in months. Large nuclear plants are built over decades. Between those two clocks sits...
Vertical Integration or Cosplay? Why AI Labs Want Dirt-to-Model Stacks
A few years ago, an AI lab's supply chain fit on one invoice: rent GPUs from a cloud provider, train...
Capex Arms Race: Mapping Hyperscaler AI Spend and What It Buys
Every quarter, the earnings season now doubles as an infrastructure census. Between 21 and 29 October 2026, Meta, Microsoft, Alphabet...
Browser, IDE, and OS: The Three Battlegrounds for AI Interfaces
Every computing era has been decided less by who had the best technology than by who controlled distribution. The PC...
From Chatbots to Work OS: How AI Assistants Are Swallowing Enterprise SaaS
Three years ago, the enterprise chatbot was a novelty tab. Employees opened it to draft an email or summarise a...
Multi-Trillion-Parameter Training: What the Next Silicon Generation Must Deliver
The compute ceiling for frontier models is no longer set by any one chip. It is set by the whole...