AI factories
4 articles
Payments for machinesFor operators: paid for AI work you did not have to sell
Operators already run the machines AI needs. The hard part is the demand: finding buyers, pricing small units of work, and being sure of getting paid by software rather than a signed customer. How demand reaches an operator's capacity through Tenzro, and how per-call settlement and signed receipts reduce counterparty risk.
6 min read
Energy and placementEnergy, power and placement: routing AI work to capacity
Power and grid connections, not chips, now limit where AI capacity can grow. This article sets out what the IEA, the US Department of Energy and EU rules say about data-centre electricity, and why routing flexible inference to where power and capacity already exist is a policy and engineering lever.
5 min read
Distributed computingFrom idle capacity to served inference: what operators need
Inference demand rises and falls through the day, so most AI capacity has spare hours. This article covers the five things a data-centre operator needs to sell those hours on an open network: machine identity, a trusted model supply, metering, proof of availability and direct settlement.
5 min read
AI factoriesUtilisation decides AI factory economics
An AI factory's accelerators cost the same whether they are busy or idle, so served work per installed accelerator is the number that matters. This article covers where utilisation is lost, and how matching demand across many operators recovers some of it.
5 min read