series dict | issues list | indicators list |
|---|---|---|
{
"title": "AI Cost Watch",
"subtitle": "A recurring, dated note on the unit economics of the AI buildout: whether its cost and demand assumptions are holding. Each issue states a falsifiable forward call.",
"concept_doi": "10.5281/zenodo.20541643",
"orcid": "0009-0003-4213-7769",
"author": "NM AI Research",
... | [
{
"n": 1,
"week": "Week of 2 June 2026",
"pub": "4 June 2026",
"doi": "10.5281/zenodo.20541644",
"status": "EXPANSION",
"trigger": false,
"thread": "The week stayed bifurcated: spend did not roll over, while the demand and price side kept accumulating deflation evidence and the physical ... | [
{
"name": "Core signal: capex-guidance down-revision",
"unit": "trigger state",
"note": "The one thing this series watches. A down-revision in the Big Four's forward capex guide is the trigger.",
"readings": [
{
"issue": 1,
"value": "no trigger",
"note": "guidance not t... |
AI Cost Watch
Reproducible, primary-source analysis of the AI industry: whether the buildout's unit economics are holding. A recurring, dated note, where each issue states a falsifiable test for its forward call. Every figure is published with its data and a script that regenerates it, so any number can be checked at source.
AI disclosure: the research is the author's; this text was drafted with AI assistance and reviewed by the author. The model, and the conflict it creates, are named in the Conflict of interest section of the linked paper.
- Author: NM AI Research (independent analyst)
- ORCID: 0009-0003-4213-7769
- Concept DOI: https://doi.org/10.5281/zenodo.20541643
- Interactive tool: https://nmairesearch.github.io/cost-watch/
- Source and code: https://github.com/NMAIResearch/cost-watch
What this is
The dataset behind the AI Cost Watch series. costwatch.json holds the frozen data: the series metadata, each issue with its status and developments, and the tracked indicators with their per-issue readings. build.py regenerates the interactive front-end from that JSON using only the Python standard library, so the published output cannot carry an unchecked number.
The tracked signal
The series watches one indicator: a down-revision in the Big Four hyperscalers' forward capital-expenditure guidance. That is the trigger it is built to catch. It has not fired in any issue to date.
Files
costwatch.json: the frozen dataset (series metadata, issues, indicators, readings).build.py: standard-library reproducer that reads the JSON and writes the front-end.LICENSE: Creative Commons Attribution 4.0 International.
Method
Each issue states one signal for the period and carries a set of indicators across issues, each with the condition that would change its reading. Every figure is stated at the tier of its source, with vendor claims labelled by the seller's business model.
Citation
NM AI Research. AI Cost Watch. Zenodo. https://doi.org/10.5281/zenodo.20541643 . Licensed CC BY 4.0.
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