HUMANOIDLEDGER
Metodología: léala antes de citar cualquier cifra. La metodología en sí es un activo de confianza: lo que sigue son las reglas, no un resumen.

Methodology

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

1. Qué es este sitio

Un libro público de datos sobre robots humanoides: especificaciones verificadas, una cronología de anuncios, vídeos oficiales y la cobertura analizada de toda la web, más tres libros construidos a partir de esa cobertura (afirmaciones vs. medidas, puntuaciones, problemas). Es un libro independiente, sin vínculo con ningún fabricante citado. La regla de contabilidad es sencilla: solo se anota lo que tiene fuente; lo no verificado se escribe «No publicado», nunca se adivina una cifra.

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 Where a figure is unpublished or unverified, the cell says Not stated rather than a guess.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. Los tres libros

Afirmaciones vs. medidas toma los key_claims de cada análisis; una afirmación solo se lista con un valor medido cuando el modelo enunció efectivamente uno (55 de 289 afirmaciones, a 2026-11-08). El resto son afirmaciones del fabricante o de la fuente, consignadas tal cual: se listan, no se verifican. Puntuaciones agrega sentiment_index y recommendation_index (distribuciones, recuentos, medias solo sobre valores no nulos) y los recuentos de conclusiones de los autores. Problemas agrupa los issues[] por texto idéntico y luego por modelo. Un modelo sin filas en un libro se muestra como «sin datos registrados», nunca como 0. Endpoints en vivo: /api/ledger/claims-vs-measured, /api/ledger/scores, /api/ledger/issues (cada uno acepta ?model=<key>).

8. Limitations — read before quoting a number

9. Corrections

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

10. Archivo: añadido el 7 de noviembre de 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. Datos abiertos: añadidos el 7 de noviembre de 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. Tablas de segunda fase: persistentes, rellenadas el 7 de noviembre de 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. Historia: pasado, presente y futuro en tres tramos completos, y lo que sigue en 0

El libro registra el pasado, el presente y el futuro en tres tramos completos; nunca parte del 0 del presente esperando solo a que cambie el futuro. La historia es la línea base: sin línea base, el cambio futuro no tiene sentido. Cada dimensión se rellena, por tanto, hasta donde alcanzan las fuentes públicas y los artículos recogidos. Relleno del 7 de noviembre de 2026 (330 artículos analizados, instantánea del 2026-11-07 20:10 EST) y registros públicos verificados:

14. Fuentes