HUMANOIDLEDGER
Méthodologie — à lire avant de citer un chiffre. La méthodologie elle-même est un actif de confiance : ce qui suit, ce sont les règles, pas un résumé.

Methodology

How the Humanoid Ledger is built, what each number measures, and what it cannot tell you. Last updated 2026-11-08.

1. Ce qu’est ce site

Un registre public de données sur les robots humanoïdes : des spécifications vérifiées, une chronologie des annonces, des vidéos officielles, et la couverture analysée de tout le web — plus trois registres construits à partir de cette couverture (affirmations vs mesures, scores, problèmes). C’est un registre indépendant, sans lien avec aucun fabricant cité. La règle de tenue des comptes est simple : on ne note que ce qui a une source ; ce qui n’est pas vérifié s’écrit « Non publié », on ne devine jamais un chiffre.

2. Seed data — verified before entry

The 12 models, 31 release events and 8 official videos were each checked against a vendor page or a trade-press report before entry (seeded 2026-11-06). Every row carries its source link. Prices are vendor-published only: target prices, estimates and unconfirmed reports live in the notes field, never in the price column. Where a figure is unpublished or unverified, the cell says Not stated rather than a guess.

3. Live coverage — sources and the relevance gate

Hacker News (Algolia API), Google News RSS (with Bing News RSS as fallback when Google rate-limits the Worker egress), tech-blog RSS (The Verge, Engadget, Wired, TechCrunch, IEEE Spectrum, The Robot Report, PCMag, Tom’s Guide, 9to5Google, Road to VR, UploadVR), YouTube search pages, and Reddit via Google News. Ingest runs hourly. An item counts for a model only when its headline names the product — vendor + model where the name alone is ambiguous (e.g. “Apollo” only counts with “Apptronik”, “Digit” only with “Agility”, “Atlas” only with “Boston Dynamics”). Items that fail the gate are counted as skipped, not silently dropped.

4. Per-article analysis

Each article is analyzed once by Workers AI (Llama 3.1 8B, max 2048 tokens, JSON only): a 1–3 paragraph summary plus structured extraction — sentiment index, comparison, usage time, recommendation index, per-aspect scores, verifiable claims, issues, and the author’s verdict. The model is instructed never to invent numbers, quotes, durations or facts not present in the evidence; undeterminable fields are null, never invented.

5. Evidence checking (what survives, what is dropped)

Two hard guards run on every analysis before it is stored. First, a compared product is kept only if its name appears in the evidence text (title + snippet + body excerpt); anything else is dropped as model invention, and the compares-with flag is recomputed from the surviving list. Second, a verdict quote is kept only if the exact quote appears in the evidence text; otherwise it is stored as null. Aspect scores are restricted to eight aspects — locomotion, dexterity, battery, payload, autonomy, safety, software, price — each scored −100 to +100 only when the article actually discusses that aspect.

6. The scoring decision — what the three retained fields are, and are not

Decision (2026-11-07): the sentiment index (0–100), the recommendation index (0–100) and the author verdict (buy / wait / skip / mixed, with the author’s own words) are retained in full, in the article cards, in the metrics pages and in the three ledgers. They are kept because they measure the source content and its author — the stance of an article, and the conclusion its author reached — not this site’s judgement of any product. This site issues no rating, no ranking, no recommendation and no prediction of its own: there is no site score anywhere on the ledger, no “best model” list, and no verdict written by us. That is the whole of the exception, and it is the only exception: the general rule for this ledger is the same as the no-scores rule — record what happened, cite the source, add no judgement of our own. The three retained fields are presented with their provenance (which article, analyzed from snippet or full text, with what confidence), with nulls counted and never filled in, so a reader can always see how thin the underlying signal is — for example, the recommendation index is not determined in 308 of 329 analyzed articles, because most coverage is news, not a buying recommendation.

7. Les trois registres

Affirmations vs mesures reprend les key_claims de chaque analyse ; une affirmation n’est listée avec une valeur mesurée que lorsque le modèle en a effectivement énoncé une (55 affirmations sur 289 au 2026-11-08). Les autres sont des affirmations du fabricant ou de la source, consignées telles quelles — listées, pas vérifiées. Scores agrège sentiment_index et recommendation_index (distributions, effectifs, moyennes sur les valeurs non nulles uniquement) ainsi que les effectifs des conclusions des auteurs. Problèmes regroupe les issues[] par formulation identique, puis par modèle. Un modèle sans ligne dans un registre est affiché « aucune donnée enregistrée », jamais 0. Endpoints en direct : /api/ledger/claims-vs-measured, /api/ledger/scores, /api/ledger/issues (chacun accepte ?model=<key>).

8. Limitations — read before quoting a number

9. Corrections

Errors are corrected in the open and logged here, not silently fixed.

10. Archives — ajoutées le 7 novembre 2026

Five vendor documents are archived as a baseline (Figure 03 announcement, Unitree G1 product page, Boston Dynamics Atlas product page, Agility Digit solutions page, 1X NEO order page), each with a SHA-256 fingerprint of the raw fetch and of the cleaned text, a 6-character seal and a 64-bit SimHash. The baseline is the first archived version; every later check compares the live document against it and records any change in doc_changes (currently 0 rows — 0 changes means nothing has changed since the baseline, not that nothing is watched). Live endpoint: /api/archive; page: /archive/. The Tesla Optimus official page could not be baselined: tesla.com returns 403 to this fetcher. It will be retried with a rendered fetch; until then it is listed on /archive/ as not baselined, not silently omitted.

11. Données ouvertes — ajoutées le 7 novembre 2026

Every dataset behind this site is open JSON with no key. /data/ lists the catalogue with denominators and coverage; /api/open-data returns the same catalogue live, including a row count for every D1 table. Live endpoint: /api/open-data.

12. Tables de deuxième phase — persistantes, remplies le 7 novembre 2026

Four persistent tables were backfilled from the 330 analyzed articles (snapshot 7 Nov 2026, 20:10 EST) and are served live with a ?model= filter. experience_records (55 rows): every key_claim that carries a measured value, classified by metric (locomotion, dexterity, battery, payload, autonomy, safety, software, price, other) — the value is the number as stated in the article, not an independent lab measurement. review_scores (224 rows): one row per analyzed article that carries a sentiment index, a recommendation index or a verdict — metadata only (reviewer = article source, score / 100, date, URL, aspects tested), no quoted opinion text. failure_modes (93 rows): issues clustered per model by identical wording, with mention counts, first/last seen dates and up to 3 source URLs. resale_snapshots (1 row): the G1, with used_price_median NULL — no used-sold market exists for humanoid robots in any reachable public source (see §13). Live endpoints: /api/experience, /api/review-scores, /api/failure-modes, /api/resale.

13. Histoire — passé, présent et futur en trois segments complets, et ce qui reste à 0

Le registre consigne le passé, le présent et le futur en trois segments complets ; il ne part jamais du 0 du présent en attendant que le futur change. L’histoire est la référence : sans référence, le changement futur n’a pas de sens. Chaque dimension est donc remplie a posteriori aussi loin que le permettent les sources publiques et les articles collectés. Remplissage du 7 novembre 2026 (330 articles analysés, instantané du 2026-11-07 20:10 EST) et enregistrements publics vérifiés :

14. Sources