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 12 September 2026 and assigned it the closest of 31 fixed categories, at 96% 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
27 measurements spanning 97 days, net -164. 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 8,038–8,252 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 27
Measured (UTC)
Subscribers
Change
11 Nov 2026, 02:12
8,063
-1
7 Nov 2026, 19:30
8,064
-5
4 Nov 2026, 19:57
8,069
-18
1 Nov 2026, 13:58
8,087
-3
29 Oct 2026, 21:28
8,090
+1
26 Oct 2026, 20:50
8,089
-3
24 Oct 2026, 02:46
8,092
-6
20 Oct 2026, 20:09
8,098
-2
17 Oct 2026, 08:54
8,100
-1
14 Oct 2026, 10:28
8,101
-7
11 Oct 2026, 03:16
8,108
-14
5 Oct 2026, 06:59
8,122
-18
26 Sept 2026, 17:40
8,140
-3
17 Sept 2026, 17:18
8,143
-10
13 Sept 2026, 21:17
8,153
-33
10 Sept 2026, 03:17
8,186
-4
5 Sept 2026, 01:20
8,190
-3
31 Aug 2026, 22:38
8,193
-2
26 Aug 2026, 12:17
8,195
-2
23 Aug 2026, 16:24
8,197
first reading
Engagement
22 posts held, back to 16 February 2024 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 38 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
10.6%
avg views ÷ 8,063 subscribers
Avg views / post
856
1 post measured
Reaction rate
2.22%
reactions ÷ views · ER floor
Posts in window
1
of 22 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.
What these figures were computed from
Window
Rolling 30 days · latest post in window 3 November 2026
Posts held
22 (16 February 2024 – 3 November 2026)
Views total
856
Reactions total
19
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
11 Nov 2026, 13:44 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
222
Videos
254
Links
413
Lifetime counters from Telegram’s own channel header, read 11 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.
Video runtime
19m 21s
Average length
58s
Measured directly from 20 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
1,483 reactions across 22 posts, in 3 distinct kinds. The most used accounts for 63.2% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
937
63.2%
❤
374
25.2%
⚡
172
11.6%
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 22 of the 22 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 1,483 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 22 most recent posts we hold, published 16 February 2024 to 3 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.
Telegram Stars
Stars received
3
across the posts below
Posts paid on
1
of 22 we hold a reading for · 5%
Most on one post
3
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @too_motion. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 22 most recent posts we hold for this entry, published 16 February 2024 to 3 November 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Recent posts
Telegram’s own ‘edited’ marker: 0 of 1 post held from the last 30 days (0%) 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).
Mago Studio - opensource local-first end-to-end AI production studio
Не прошло и месяца как Maga Mago Studio опенсорснули (в отличие от некоторых гарфилдов).
Есть полноценные пайплайны для работы с картинками, видео, и генерации короткого метра из сценария.
С историей настроек, возможностью итерации, редактирования, вот это вот все.
С нормальным управлением проектами, а не все рендеры в кучу в общей истории и 'з…
берегите ваши глаза и уши. я навайбкодил видео!
Don't Slop Me Babe - мой новый экспериментальный проект. это сатирическое высказывание на происходящее вокруг с отсылками на криповые тренды и реально существующие профили. исходный пайплайн взял из музыкального видео BLISS (советую посмотреть, это очень стильно и красиво)
фишка проекта в том что тут нет как такового монтажа. клод написал движок несуществующего сайта …
айда играться со временем и пространством в видео
навайбкодил веб-инструмент который превращает видео в объем и дает посмотреть на видео-поток "со стороны". и сбоку и сверху и под любым углом.
сама идея не новая. принцип работы подробно объяснил и показал ТехноШаман. а для своей реализации как референс я использовал визуалы Bradley Tangonan
https://vsewall.github.io/time-volume/
@тоже_моушн
They Replaced Us
интерактивная инсталляция на основе 3DGS в Touchdesigner для мероприятия BYOB в Берлине
люблю бросать себе вызовы. впервые замахнулся на создание в одиночку такой сложной задумки. в итоге из пруф оф концепт получился вполне рабочий прототип. попутно испробовал разные инструменты и выбрал наиболее эффективную технологию:
1. генерировал изображение в Nano Banana Pro
2. анимировал в Seedance 2.5
3. по…
вы не ждали а я вернулся. и не с пустыми руками а со старыми добрыми сплатами, с пылу с жару, только из печи.
сплаты кстати полностью синтетические: вот оно ничего не было и вот он объект в 3д - крути и двигай, ломай и пересобирай как душе угодно. пусть и прозвучит пафосно но ощущаю как жизнь опять поделилась на до и после.
полтора года назад аналогичный эксперимент потерпел неудачу потому что видео модельки плохо …
колыбельная. опять мрачняк - ну такое настроение
мой новый личный фаворит среди опенсорсных видео моделей - LTXVideo+STG. по качеству конечно не Hunyuan, зато работает в 8 раз быстрее и к тому же умеет в img2vid
до сих пор до конца не верю что оживлятор картинок подобного уровня теперь доступен локально. все еще не сора и не клинг но уже заметно лучше чем SVD
за трек спасибо прекрасному Demien Stoker
кастомные но…
новогодний триллер в духе позднего СССР как напоминание о том что новый год подкрался незаметно
автор мрачного гиперреалистичного видео Aleksej Lotkov, ему также помогали Aleksei Olenchenko и Leo Erdman
В этой супер-короткометражке я хотел обыграть западный имидж СССР и нестандартный нарратив. Стиль под пленку 80-ых помог скрыть пару косяков и разгуляться воображению.
Использовали самые новые/передовые тулзы по тип…
Ну что, друзья? Встречайте FaceTracker for Blender (Beta)
Наше фирменное решение для трекинга лиц теперь доступно каждому прямо в Blender. Сгенерировать 3D модель лица по кадрам из видео, потрекать мимику, омолодить или состарить, добавить тату, 3D эффект или симуляцию — все это теперь легко сделать, не закрывая Blender!
Что вас ждёт:
– Быстрый и точный трекинг головы и мимики
– Встроенный FaceBuilder для создания …
если вам тоже было интересно как затанцевать макароны, держите воркфлоу для комфи а также свежий пошаговый видео туториал
магия происходит конечно же благодаря ip-adapter и qrcode-monster controlnet. а за хорошую скорость генерации отвечает lcm моделька. все необходимые ссылки есть в туториале
workflow на civitai
туториал
ig автора воркфлоу
@тоже_моушн
признаюсь, я не большой любитель аудио генераций. немного баловался с suno но вау эффекта не получил
однако с этим треком ситуация ровно наоборот - полное попадание в мои персональные музыкальные мурашки и желание слушать его на репите. автор - мой хороший друг, исполнитель - udio. не представляю как у Саши получилось так лихо укротить сетку и так сочно передать вайбы и звучание электронной музыки 2010х. некоторые "…
В Казани стартовал международный фестиваль медиаискусства NUR. На нем представлена инсталляция EYE, созданная в коллаборации четырех независимых хужодников из SILA SVETA: Ilia Balakin, EGO, Vsevolod Taran и Alexander Karelin.
Искать инсталляцию нужно во дворе «Национального музея», ее центральный элемент — сцена-ракушка — превращена в око искусственного интеллекта. Зрачок перед сценой олицетворяет ИИ, который с помо…
очень милый и визуально приятный кейс - ручная анимация цветных шейпов в бесплатной рисовалке Tagtool на айпаде с дальнейшей реалтайм обработкой в TouchDesigner с помощью StreamDiffusion
это дело рук VJ Suave - дуэта медиахудожников из Бразилии. подробней про проект можно почитать у Demien Stoker
StreamDiffusion - это ну очень быстрый txt2img: запросто выдает 15 fps на 4090 в разрешении 512. и это реально выглядит …
🔥53⚡10❤8
Showing the 12 most recent of 22 posts we hold for @too_motion. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Forward network
Republishes
Channels on the register whose posts this channel has forwarded.
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.
Mentions
Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
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 11 November 2026 — this
entry's latest reading, not the date you are reading this.
“тоже моушн” (@too_motion), 8,063 subscribers as measured 11 November 2026. Telegram Register, tgregister.com/channel/too_motion.
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.