Other / unclassifiable — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 9 August 2026 and assigned it the closest of 31 fixed categories, at 40% 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 why it has no browse page of its own yet.
Growth
9 measurements spanning 7 days, net +53. 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 118,925–119,107 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
13 Aug 2026, 11:29
118,999
-87
12 Aug 2026, 11:43
119,086
+83
11 Aug 2026, 11:34
119,003
+40
10 Aug 2026, 10:32
118,963
-108
9 Aug 2026, 11:52
119,071
+121
8 Aug 2026, 12:31
118,950
-114
6 Aug 2026, 15:31
119,064
+118
6 Aug 2026, 01:32
118,946
no change
6 Aug 2026, 00:12
118,946
first reading
Engagement
36 posts held, back to 1 August 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 19 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
11.7%
avg views ÷ 118,999 subscribers
Avg views / post
13,900
36 posts measured
Reaction rate
6.31%
reactions ÷ views · ER floor
Posts in window
36
of 36 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 13 August 2026
Posts held
36 (1 August 2026 – 13 August 2026)
Views total
500,020
Reactions total
31,557
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
13 Aug 2026, 19:06 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
≈4,730
Videos
≈1,260
Links
≈1,400
Lifetime counters from Telegram’s own channel header, read 13 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Video runtime
4m 53s
Average length
49s
Measured directly from 6 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
23,456 reactions across 28 posts, in 13 distinct kinds. The most used accounts for 37.8% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
8,870
37.8%
🔥
6,711
28.6%
👍
3,446
14.7%
😁
1,393
5.94%
👏
918
3.91%
🤬
774
3.30%
😢
713
3.04%
😱
326
1.39%
🤔
171
0.729%
🥰
53
0.226%
👎
47
0.2%
custom 5337306071478321357
26
0.111%
🤩
8
0.034%
Custom emoji. One row above is a Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The count beside it isTelegram’s.
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 36 of the 36 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 31,557reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 36 most recent posts we hold, published 1 August 2026 to 13 August 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
31
across the posts below
Posts paid on
16
of 36 we hold a reading for · 44%
Most on one post
5
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @cognitive_life. 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 36 most recent posts we hold for this entry, published 1 August 2026 to 13 August 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.
"ПЕРВАЯ ПРОПОВЕДЬ ГОВАРДА БИЛА - 2026"
Я болею и смотрю старые фильмы. Вот, например, "Телесеть" 1976 год. Культовая вещь. Сегодня - зацепил! Магия и предвидение. Там съехавший телеведущий становится теле проповедником и вот его первая проповедь (см.в комменте). Я написала вариант, чтобы он сказал сегодня в 2026. На ваш суд:
ПРОПОВЕДЬ ГБ - 2026
Мне не нужно говорить вам, что дела плохи. Вы и без меня это знаете.…
ХОЧУ И НАДО
ЭВОЛЮЦИЯ ИИ В ПРОЕКТЕ C- PILOT
В рамках последних работ наша команда вскрывает все новые и новые покровы с целью формирования действительно умного и безопасного автобота. Как я уже писала мы движемся по антропоморфному пути и вплотную приблизились к следующему...
Стандартная человеческая развилка между ХОЧУ И НАДО:
- хочу эту девушку/ должен жениться;
- хочу поваляться в постели/ надо вставать на работ…
НЕ ЛЕБЕДИНОЕ ОЗЕРО, НО...
Народ, сильно заболела. Температура и т.п. пару дней текстов не будет. Лажу постить неохота, а голова не работает.
В Москве сейчас вспышка ковида (по мнению моих врачей). Ничего смертельного, просто противно. Поэтому Матвей здесь исполняет не Лебединое Озеро. Билеты на встречу с ним и со мной 23 сентября. (Мировая Премьера, между прочим))) https://olgauskova.timepad.ru/event/4064180/.
Всех …
ДЕТАЛИ
"У него на плотине блестит горлышко разбитой бутылки и чернеет тень от мельничного колеса - вот и лунная ночь готова..."
А.П.Чехов "Чайка"
В них не Дьявол, в них Бог. При работе над Искусственными Мозгами C-Pilot мы пришли к довольно интересным наблюдениям. Оказывается, чтобы запустить логический процесс, РАССУЖДЕНИЕ, человеку нужен "серьезный" повод. То есть факт, событие воспоминание, носящее комплек…
УРАЛ
Сегодня на переговорах всплыла аллегория про то, как сейчас работается в отечественной электронной промышленности - как будто ты маленький. Угнал папин велосипед Урал. И крутишь педали из-под рамы посреди пыльного проселка.
Для молодежи в ленте справка:
"Пермский машиностроительный завод в 1965 году выдал на-гора велосипед "повышенной прочности и проходимости" — "Урал". Среди пацанов ходили байки, что первую мо…
УПРАВЛЕНИЕ ЛИЧНОЙ ВНУТРЕННЕЙ ПОЛИТИКИ
(практически coming out)
В одиннадцать вечера Николай Петрович совершил роковую ошибку решил перед сном пять минут почитать новости.
Обычный человек в такой ситуации смотрит прогноз погоды, выясняет, что завтра дождь, думает - "опять врут" и спокойно засыпает.
Но Николай Петрович открыл политическую ленту.Сначала прочитал про снятие с выборов партии "Яблоко".
- Ну вот, - сказа…
Три года назад в этот день нас с Антоном обвенчали в маленькой деревянной церквушке в деревянном скиту в тайге на Байкале.
Я описала это в конце моей главной книги "Аминь". "Аминь" - это вообще автобиография моей души. Я верю в то, что у души есть еще и свой отдельный путь, отличный от совместного с телом. Отсюда и воображение, и умение мечтать, и умение творить...
"...На краю берега уже выстроились в неровную лини…
ЕЛЕНА, СПАСИБО)))
Захожу в блог, а там Лена Астафьева (девушка на фото) собирает народ, чтобы "Си-Пи" дали премию Президента.
"Открыт приём документов на соискание премии Президента в области культуры за произведения и проекты для детей и юношества
Совет при Президенте по культуре объявляет о начале приёма документов на соискание премии Президента в области культуры за произведения и проекты для детей и юношества за…
СЕРГИЕВ ПОСАД. АВГУСТ.
У нас вчера был семейный праздник. ДР у свекрови. И мы провели день по ее плану. В Сергиевом Посаде.
Я решила написать, т.к. замечательный день получился и рекомендую.
Дорога на машине: от Москвы близко. Ярославка шоссе загруженное. Лучше выбираться в будни или пораньше в выходной. Можно попасть в пробки,( но не смертельные). Но подъезд идеальный к городу. Развязки, парковки - все на высшем …
В ГОСТЯХ У СКАЗКИ
Сказка ложь, да в ней намёк: чему Си-Пи может научить Человека-паука?
У каждого народа свой путь к супергерою. В Америке мальчика кусает радиоактивный паук и он получает сверхсилу, сверхреакцию и пожизненную обязанность бегать по небоскрёбам в обтягивающем трико. В России мальчик Ваня вместе с папой собирает робота из подручных приборов и инопланетной детали, и получает друга, приключения и угрозу …
ИГРЫ, В КОТОРЫЕ МЫ ИГРАЕМ
(Я не знаю, когда выпущу роман "Преемник". Пока не время точно. Но вот рабочая глава романа - для субботы, на ваш суд.)
У Сергея Аркадьевича была проблема. Для человека его уровня слово "проблема" вообще-то считалось неприличным. Проблемы бывают у населения, а у руководства бывают вызовы, отдельные вопросы, временные сложности и необходимость дополнительной проработки.
Но сейчас у Сергея …
❤177🔥110👍53🤔8😁5👎2
Showing the 12 most recent of 36 posts we hold for @cognitive_life. 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.
Posts edited after publishing
@cognitive_life edited 2 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
8 August 2026
Most recent edit
8 August 2026
Citation-graph rank
Citation-graph rank — 11,019 of 1,176,251entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
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.
Mentions
Named by 23 registered channels — 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.
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.
ЮЛИЯ МЕНЬШОВА @JuliaMenshovaJulia · 361,530 Telegram ranks this channel #3 of 91 here — alongside 90 others — read 10 August 2026
Алеся Петровна @alesiapetrovna · 140,827 Telegram ranks this channel #14 of 89 here — alongside 88 others — read 13 August 2026
Татьяна Мужицкая и все-все-все @muzhitskaya · 165,210 Telegram ranks this channel #42 of 91 here — alongside 90 others — read 12 August 2026
Кухня наизнанку @min2ru · 534,992 Telegram ranks this channel #47 of 83 here — alongside 82 others — read 11 August 2026
Хазин @khazinml · 246,004 Telegram ranks this channel #73 of 91 here — alongside 90 others — read 11 August 2026
Константин Дараган 🔶 Комментарий астролога️ @daragan_konstantin · 209,220 Telegram ranks this channel #80 of 92 here — alongside 91 others — read 11 August 2026
Мария Шукшина @mariashukshina · 153,947 Telegram ranks this channel #88 of 92 here — alongside 91 others — read 12 August 2026
This channel appears in 7 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 13 August 2026 — this
entry's latest reading, not the date you are reading this.
“Ольга Ускова | Cognitive Life” (@cognitive_life), 118,999 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/cognitive_life.
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.