Реклама и сотрудничество: @coldmay
Тренды в культуре и технологиях; AI, фильмы, сериалы, книги, музыка. Наблюдения за реальностью.
Автор: @dtrbn
#AII9O
Номер заявления: 7726253803
Created
26 February 2022 — measured — cross-checked against a third-party dataset (ext.tg_channel)
Education — 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 20 August 2026 and assigned it the closest of 31 fixed categories, at 82% 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
58 measurements spanning 93 days, net +616. 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 12,948–13,865 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 58
Measured (UTC)
Subscribers
Change
6 Nov 2026, 23:37
13,759
+17
5 Nov 2026, 23:59
13,742
-7
4 Nov 2026, 21:30
13,749
+31
3 Nov 2026, 17:35
13,718
+9
2 Nov 2026, 20:10
13,709
-5
1 Nov 2026, 20:55
13,714
+5
31 Oct 2026, 20:47
13,709
+22
30 Oct 2026, 18:21
13,687
+12
29 Oct 2026, 20:40
13,675
+28
28 Oct 2026, 21:57
13,647
+21
27 Oct 2026, 22:49
13,626
+11
26 Oct 2026, 23:19
13,615
+30
26 Oct 2026, 00:18
13,585
+62
24 Oct 2026, 23:48
13,523
+13
24 Oct 2026, 02:50
13,510
+2
23 Oct 2026, 02:19
13,508
-1
22 Oct 2026, 01:38
13,509
+6
20 Oct 2026, 17:27
13,503
+3
18 Oct 2026, 15:39
13,500
-2
17 Oct 2026, 14:42
13,502
first reading
Engagement
43 posts held, back to 7 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 60 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
12.1%
avg views ÷ 13,759 subscribers
Avg views / post
1,670
20 posts measured
Reaction rate
2.01%
reactions ÷ views · ER floor
Posts in window
20
of 43 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 7 November 2026
Posts held
43 (7 July 2026 – 7 November 2026)
Views total
33,416
Reactions total
671
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
7 Nov 2026, 18:28 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
≈1,970
Videos
≈788
Links
≈861
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. 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
22m 09s
Average length
1m 42s
Measured directly from 13 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
1,742 reactions across 43 posts, in 8 distinct kinds. The most used accounts for 41.6% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
724
41.6%
😁
432
24.8%
🔥
240
13.8%
😱
126
7.23%
👏
90
5.17%
😢
81
4.65%
🤔
34
1.95%
custom 5366112503031962495
15
0.861%
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 is Telegram’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 43 of the 43 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 1,742 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 43 most recent posts we hold, published 7 July 2026 to 7 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
13
across the posts below
Posts paid on
3
of 43 we hold a reading for · 7%
Most on one post
11
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @danieltrbn. 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 43 most recent posts we hold for this entry, published 7 July 2026 to 7 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: 7 of 20 posts held from the last 30 days (35.0%) 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).
Появился словарь слов, которых ещё нет, но они скоро понадобятся.
10 ноября выходит книга «Future Words: A Non-Obvious Glossary of Terms That Don't Exist (But Soon Will)». Её написали Рохит Бхаргава, автор ежегодных трендбуков «Non-Obvious», и Генри Коутиньо-Мейсон. Внутри 100 придуманных слов для того, что с нами уже происходит, но пока не имеет имени.
Выписал любимые:
— fauxstalgia, «фейкосталгия» — тоска по вос…
Anthropic научила Claude видеть сны. И забывать лишнее.
В инженерном блоге Anthropic вышел пост про память агентов, то есть ИИ, которые сами выполняют длинные задачи. Начинается он со сравнений с человеческим мозгом. Пока мы спим или просто отдыхаем, гиппокамп заново проигрывает то, что с нами случилось за день, и часть этого переезжает в долговременную память.
С Claude теперь делают то же самое и называют это «dre…
Хоакин Феникс в рекламе умных очков Gentle Monster, которую срежиссировал Джонатан Глейзер. Это вообще как?
Gentle Monster — корейский бренд очков, известный магазинами, похожими на арт-инсталляции, — выпускает первую коллекцию очков с ИИ. Делает её вместе с Google и Samsung, внутри будет Gemini — ИИ-помощник Google, с которым говорят голосом. Google так верит в эту затею, что в прошлом году купил 4% бренда примерно…
У Нэйтана Филдера появился младший брат, который тоже ломает реальность.
Вы наверняка знаете Филдера (документалку ждем очень), а еще может быть слышали про The Yes Men — дуэт активистов, которые с 90-х выдают себя за представителей корпораций. В 2004-м один из них в эфире BBC от имени химического гиганта Dow Chemical пообещал компенсации жертвам Бхопала, катастрофы на химзаводе в Индии, и акции Dow за 23 минуты упа…
Клава Кока запустила шоу про ИИ-музыку.
Вчера у певицы Клавы Коки в VK вышел первый выпуск «ХИИТ ШОУ». Механика такая: на сцену по очереди выходят три исполнительницы и поют под фонограмму. За каждой песней может стоять человек, нейросеть или они вместе, и голос на фонограмме тоже может быть сгенерирован, а девушка на сцене просто открывает рот. Жюри гадает и пропускает дальше одну.
Двое выбывших рассказывают, как …
23 ноября мы запускаем новый поток курса по ИИ, который назвали «AI-Пересборка».
Последние полгода я ощущаю ИИ не как ассистента и чат-бота, а как собственную автономную операционную систему и конструктор, из которого можно собрать все, что угодно.
И вот эту систему мы будем создавать. Что делегировать, а что оставить себе? Как все настроить? Как найти себя в мире, где все хотят всех заменить ИИ? Курс у нас делится…
Пять вопросов, чтобы не сдать своё мышление нейросети.
Адди Османи делает в Anthropic Claude Code. В X он написал, как не разучиться думать, когда работу делает ИИ.
Османи описывает три ступени:
1. Делегирование. Работу делает ИИ, но вы проверяете результат и отвечаете за него.
2. Вера на слово. Ответ нейросети вы ещё читаете, но уже не сомневаетесь в нём.
3. Капитуляция. Ответ ИИ становится вашим мнением, вы ег…
ИИ вытащил из ста фантастических романов 6 222 идеи стартапов с оценками.
Вышла Startup Archaeology, «археология стартапов» — сайт с архивом идей. Нейросеть прочитала сто фантастических книг 1818–1965 годов и выписала из них все выдуманные изобретения, 6 222 штуки. Каждое перевели в современную идею для бизнеса: кто первый клиент, каким будет первый продукт, в чём риски. И оценили по десятибалльной шкале, насколько …
На скучный созвон можно отправить вместо себя исландскую вязальщицу, а не этот ваш ИИ.
Бюро туризма Исландии запустило рекламную кампанию AI Knittakers. Название — игра слов: knit — «вязать», note-taker — тот, кто ведёт протокол встречи. А AI тут расшифровывается как Authentic Icelandic, «настоящие исландцы». Вместо ИИ-ассистента, который слушает созвон и присылает саммари, к онлайн-встрече подключается живой челове…
❤34🔥9👏6🤔1
Showing the 12 most recent of 43 posts we hold for @danieltrbn. 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 @danieltrbn 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
23 August 2026
Most recent seen missing
23 August 2026
Median time before seen missing
3 days
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.
Mentions
Named by 17 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.
DECODERS @d3c0d3rzzz · 20,863 Telegram ranks this channel #4 of 85 here — alongside 84 others — read 25 September 2026
ХОРОШИЕ НОВОСТИ @goodnews_goodtimes · 45,857 Telegram ranks this channel #27 of 86 here — alongside 85 others — read 27 August 2026
ШишКИНО @shishkino · 41,898 Telegram ranks this channel #40 of 97 here — alongside 96 others — read 29 August 2026
Осовцов говорит @osovtsovgovorit · 80,480 Telegram ranks this channel #42 of 72 here — alongside 71 others — read 21 September 2026
psycho daily @psychodaily · 18,946 Telegram ranks this channel #53 of 88 here — alongside 87 others — read 5 October 2026
НА ШУМЕ @nashume · 20,105 Telegram ranks this channel #55 of 82 here — alongside 81 others — read 27 September 2026
Vika Chuma @chumavecherinka · 19,405 Telegram ranks this channel #59 of 84 here — alongside 83 others — read 4 October 2026
Павел Недостоев / дилер впечатлений @pavelnedostoev · 30,283 Telegram ranks this channel #70 of 96 here — alongside 95 others — read 7 September 2026
kuji @kujikuji · 49,827 Telegram ranks this channel #78 of 83 here — alongside 82 others — read 8 September 2026
This channel appears in 9 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.
“AI меняет культуру | Trabun” (@danieltrbn), 13,759 subscribers as measured 6 November 2026. Telegram Register, tgregister.com/channel/danieltrbn.
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.