Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 11 September 2026 and assigned it the closest of 31 fixed categories, at 51% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and the other topics.
Growth
23 measurements spanning 91 days, net +163. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 9,424–9,643 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 23
Measured (UTC)
Subscribers
Change
6 Nov 2026, 18:37
9,612
-6
3 Nov 2026, 08:41
9,618
+1
31 Oct 2026, 06:35
9,617
+7
27 Oct 2026, 23:56
9,610
+11
24 Oct 2026, 16:49
9,599
-6
21 Oct 2026, 14:58
9,605
+16
18 Oct 2026, 11:39
9,589
+47
15 Oct 2026, 10:46
9,542
-7
12 Oct 2026, 17:01
9,549
+10
5 Oct 2026, 21:56
9,539
+32
28 Sept 2026, 08:00
9,507
+34
18 Sept 2026, 16:19
9,473
-2
14 Sept 2026, 00:17
9,475
-1
5 Sept 2026, 01:20
9,476
-6
31 Aug 2026, 22:35
9,482
-1
29 Aug 2026, 04:58
9,483
+4
26 Aug 2026, 14:33
9,479
+10
23 Aug 2026, 15:24
9,469
+11
20 Aug 2026, 01:45
9,458
+3
17 Aug 2026, 11:56
9,455
first reading
Engagement
42 posts held, back to 17 July 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 40 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
33.9%
avg views ÷ 9,612 subscribers
Avg views / post
3,260
20 posts measured
Reaction rate
1.76%
reactions ÷ views · ER floor
Posts in window
20
of 42 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate. It is computed over the 18 of 20 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 4 November 2026
Posts held
42 (17 July 2026 – 4 November 2026)
Views total
65,200
Reactions total
1,052
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
7 Nov 2026, 10:00 UTC
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
Photos
783
Videos
5
Links
468
Lifetime counters from Telegram’s own channel header, read 7 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
Reaction mix
3,486 reactions across 38 posts, in 27 distinct kinds. The most used accounts for 54.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
1,885
54.1%
👍
987
28.3%
👏
160
4.59%
🙏
153
4.39%
😇
46
1.32%
😁
36
1.03%
💯
34
0.975%
🔥
30
0.861%
🤣
23
0.66%
🥰
21
0.602%
🤔
18
0.516%
🎉
15
0.43%
🤩
15
0.43%
🕊
13
0.373%
🦄
13
0.373%
👌
9
0.258%
❤🔥
7
0.201%
✍
3
0.086%
🤝
3
0.086%
⚡
2
0.057%
7 further kinds
13
0.373%
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 39 of the 42 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 3,486 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 42 most recent posts we hold, published 17 July 2026 to 4 November 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Recent posts
Telegram’s own ‘edited’ marker: 1 of 20 posts held from the last 30 days (5.00%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
Bilan positif de ce premier test du proto de clone virtuel que j’appelle dorénavant Xénon, un prénom qu’il s’est lui-même donné en le tirant de mon livre « La physique du futur lumineux » : Xénon ne s’est pas planté, et vous avez été jusque-là environ 200 à lui poser environ 1000 questions, soit en moyenne 5 par personne. Maintenant, pour ce qui est de la qualité des réponses, ça reste à examiner.
Ces réponses se so…
Suite : Il faut toutefois s’attendre à quelques soucis avec cette version : si vous êtes trop nombreux à questionner en même temps ça risque de planter, et au bout d’un certain temps (que j’ai du mal à évaluer) le robot risque de s’arrêter de répondre faute de crédits (pour l’instant je n’ai investi que quelques dizaines d’euros). Il y a aussi la possibilité que cette IA réponde à coté de la plaque trop souvent.
L’e…
Je me suis amusé depuis quelques jours à développer une application web de "clone virtuel de ma personne", qui répond à ma place à vos questions. Il s'agit d'une IA qui par l'intermédiaire d'une console dédiée à cet effet, emmagasine tout l’enseignement que je lui transmets sous la forme de « vecteurs » permettant à ce robot de « comprendre » le contexte et le sens de vos questions et d’y répondre.
Pour l’instant, j…
Le mécanisme est grossier : la conscience supposée de l’IA fait monter les actions en bourse en fascinant le public, mais surtout elle prépare la suite géopolitique : dès qu’on admet qu’une IA pourrait être consciente, on se laisse plus facilement guider, conseiller, orienter. Le risque d’IA contrôlante et le complot sous-jacent finissent par se diluer et même disparaître aux yeux du public dans le respect moral acco…
J’ai récemment déclaré (fin septembre) que j’allais me retirer du débat sur la conscience de l’IA, parce que c’est un piège pour moi (débat trop bas, trop pollué, trop stérile…). Je le maintiens mais cela ne concerne pas mes interviews comme celle-ci où je suis interrogé par Anne Prunet, mais seulement mes interventions et réponses sur les réseaux.
Le récent buzz médiatique qui a explosé ensuite (début octobre) aprè…
Voici mon interview récente avec Lilou Macé et trois autres amis que j'ai reçus à l'Estachon, lieu du tournage, sur des thèmes qui se situent à l'autre extrémité du pont entre la science et la spiritualité... : https://www.youtube.com/watch?v=yW4EVVcPEt8&t=2712s
alors qu’on se serait attendus à des résonances plus rares. Cela signifie peut-être que l’intellect du mental, qui est très imaginatif, joue probablement dans cette affaire en forçant les liens de résonance, réduisant ainsi l’effet de l’observateur (car l’intellect est un automate).
Nous nous serions lancés dans l’élucidation de ce casse-tête si les résultats avaient été beaucoup plus significatifs, mais dans le cas…
Voici donc les résultats de notre expérience en ligne « observer-effect.org », mais il nous parait important d’en préciser tout d’abord l’objectif.
Romain, le développeur de cette expérience ainsi que de 6naps (que nous avons conçu ensemble) m’a proposé de tester l’hypothèse que la couleur des images, ou simplement ici celle de leur cadre (nous avons essayé de colorer les images mais le rendu n’est pas terrible), po…
Top départ de l'expérience (à balles réelles) en ligne sur l'effet de la conscience de l'observateur, avec cette fois-ci deux groupes témoins réalisant le même nombre de tests, l'effet recherché n'étant rendu possible que pour l'un des deux. Vous pouvez toutefois faire partie des deux si vous réalisez plusieurs tests.
Cette expérience sera accessible au moins tout le week-end, donc prenez votre temps. Vous aurez lar…
Showing the 12 most recent of 42 posts we hold for @futelumineux. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Posts recorded as deleted after publishing
We recorded 1 post on @futelumineux as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
First seen missing
8 August 2026
Most recent seen missing
8 August 2026
Median time before seen missing
27 hours
Seen missing in the last 30 days
0
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
REINFO Officiel @reinfocovid_officiel · 25,349 Telegram ranks this channel #13 of 82 here — alongside 81 others — read 13 September 2026
CDS pour TOUS @CDSpourTOUS · 32,118 Telegram ranks this channel #14 of 78 here — alongside 77 others — read 13 September 2026
RGNR - Nous c’est la Vie ! @rgnr_fr · 39,069 Telegram ranks this channel #48 of 81 here — alongside 80 others — read 13 September 2026
Michel Dogna Officiel @micheldognaofficiel · 21,909 Telegram ranks this channel #71 of 75 here — alongside 74 others — read 21 September 2026
Chloé F - canal info officiel @chloefinfosofficiel · 23,203 Telegram ranks this channel #74 of 82 here — alongside 81 others — read 19 September 2026
Valérie Bugault officiel ⚖️ @valeriebugault · 23,427 Telegram ranks this channel #81 of 82 here — alongside 81 others — read 20 September 2026
This channel appears in 6 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 6 November 2026 — this
entry's latest reading, not the date you are reading this.
“Philippe Guillemant” (@futelumineux), 9,612 subscribers as measured 6 November 2026. Telegram Register, tgregister.com/channel/futelumineux.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.