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 10 August 2026 and assigned it the closest of 31 fixed categories, at 48% 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.
Observations
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Content that also appears on other registered channels
Posts published here appear word for word on 1 other registered channel. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
Matching posts — open both and compare (6 of the pairs behind the counts below)
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. None of the 0 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.
“Published first” means first in this corpus. We hold 14 comparable posts for this entry, running 15 May 2026 to 29 July 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).
Across the whole group of 2, the earliest publisher we hold is @strangedalle — which is this entry. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_source, last confirmed 8 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
Also posting the same content
This channel’s posts match, word for word or near enough, posts on 1 other registered channel, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
35 measurements spanning 44 days, net +1,317. 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 45,221–47,450 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 35
Measured (UTC)
Subscribers
Change
19 Sept 2026, 03:38
46,847
-11
16 Sept 2026, 14:59
46,858
-13
14 Sept 2026, 18:41
46,871
+8
13 Sept 2026, 06:38
46,863
-18
11 Sept 2026, 11:40
46,881
-42
8 Sept 2026, 18:20
46,923
-47
5 Sept 2026, 12:01
46,970
-46
3 Sept 2026, 13:37
47,016
-34
2 Sept 2026, 10:24
47,050
-12
1 Sept 2026, 13:43
47,062
-36
31 Aug 2026, 15:06
47,098
-50
30 Aug 2026, 16:26
47,148
-45
29 Aug 2026, 18:04
47,193
+227
28 Aug 2026, 17:43
46,966
+248
27 Aug 2026, 21:14
46,718
+530
26 Aug 2026, 21:34
46,188
+476
25 Aug 2026, 19:32
45,712
+234
24 Aug 2026, 16:47
45,478
-2
22 Aug 2026, 22:33
45,480
-13
21 Aug 2026, 14:06
45,493
first reading
Engagement
26 posts held, back to 15 May 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 94 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
40.0%
avg views ÷ 46,847 subscribers
Avg views / post
18,700
7 posts measured
Reaction rate
0.868%
reactions ÷ views · ER floor
Posts in window
7
of 26 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 9 September 2026
Posts held
26 (15 May 2026 – 9 September 2026)
Views total
131,200
Reactions total
1,139
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
22 Sept 2026, 16:35 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
893
Videos
255
Links
283
Lifetime counters from Telegram’s own channel header, read 22 September 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
4m 10s
Average length
1m 03s
Measured directly from 4 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
6,773 reactions across 26 posts, in 7 distinct kinds. The most used accounts for 40.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
2,735
40.4%
❤
2,060
30.4%
👍
1,016
15.0%
👻
334
4.93%
🤔
296
4.37%
🤯
257
3.79%
😱
75
1.11%
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 26 of the 26 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 6,773 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 26 most recent posts we hold, published 15 May 2026 to 9 September 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
157
across the posts below
Posts paid on
19
of 26 we hold a reading for · 73%
Most on one post
55
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @strangedalle. 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 26 most recent posts we hold for this entry, published 15 May 2026 to 9 September 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.
Вышел Suno 6 💃
Так что качество нейротреков соссмыслом про пацанских волков и любовную любовь в такси чуть подрастет.
Можно править отдельные слова и припевы, не пересобирая песню целиком, скрещивать несколько треков и делать музыку по картинкам и видео. Версий теперь три: обычная, wild для экспериментов и бесплатная mini.
Ну и сюда же. Я.Музыка (наконец-то) ввела маркировку AI-треков, собственную детекцию и настр…
✊ Ура, вышел ChatGPT Images 2.5, лучший друг нейрослопных постеров для малого бизнеса, ну и ладно, лучшая картиношная модель по пониманию промта. По анонсу — лучше держит внешность с референсов, точнее правит отдельные детали и (самое важное) сохраняет качество после нескольких итераций.
Что ещё завезли:
1. Время генерации сократили до 50%. Плюс обещают более естественный свет и текстуры.
2. Sketch — можно прямо в…
Все никак не могу сесть написать пост про GPT Astra. Во первых, кажется уже все всё написали. Во вторых, не могу из нее вылезти. 😑
Можно сделать так — расскажите про ваш реальный (не шоукейсный) опыт в комментариях. Каких приколдесов успели поделать? Свой и ваш опыт скомбинирую в следующий жирный обзорный пост.
Скиллы, как мы уже знаем, — новое золото. 💸 Где его копать?
Best Skills — хит-парад скиллов, который каждый день пылесосит тысячи штук из разных экосистем и строит рейтинг по установкам, росту и активности.
Наверху сейчас agent-browser, frontend-design, find-skills, grill-me. Последний, кстати, советую жёстко — через уточняющие вопросы выжимает из вас нужный контекст.
Короче, хороший радар для регулярного обновле…
29 августа выступаю на онлайн-конференции «Основателей».
Расскажу, чем занимаюсь в последнее время. Моя тема — вАйБвОрКиНг. Короче, следующий уровень после обычного общения с нейронками: вместо отдельных поручений длинные задачи с агентами, скиллами и прочими финтифлюшками.
Покажу, как применя этот подход в рекламе и производстве бренд-контента. Ну и как это меняет креативную индустрию.
А другие господа с картинки…
Чистим ГПТ картинки от шакалов.
Вы просили — выкладываю. На самом деле всё просто. Берём картинку и отправляем его в Grok 1.5, просим почистить от шакалов и артефактов. Всё. Способ у кого-то у канале подсмотрел, но не помню точно у кого (если это вы — напишите, отмечу).
Скилл не прикладываю, так как он заточен под мой MCP, советую сделать под себя, чтобы в чате просто попросить — убери шакалов, он пишем промт точн…
Заставляем ГПТ точечно править картинку без шакалов 🗡
Большая часть моего взаимодействия с ЛЛМками сейчас — это крафт полезных продакшенов скиллов для студии (ну и лично для себя). Делюсь одним из.
В чем соль. Бывает, что нужно поправить деталь в картинке, но ГПТ генерит ее целиком, деталь поправлена, но изображение деградировало и покрылась фирменной шакальной паутинкой. Конечно, можно исправить (тоже для этого ес…
Если вы запутались в изобилии новых видеонейронок — попробую коротко распутать.
Seedance стал 2.5. По-прежнему финальный босс: 30 секунд вместо 15, до 50 рефов, ещё лучше слушает длинные промты. В целом стал чуть живее. Минусы: супертревожный на тему авторских прав — на всякий случай блокирует почти всё. Русский снова не завезли. По тестам после 15 секунд начинает сыпаться. Пока только 720p. Ну и ДОРОГО ЖЕСТЬ ВЫ ЧТ…
Я (возможно) победил тайм-менеджмент.
Продолжаю нахваливать ГПТ Ворк. Перетащил туда кучу проектов из Клода — теперь и тайм-менеджмент.
С ним всё ужасно (было). Всегда устаю обслуживать систему раньше, чем она начинает работать, поэтому сделал свою. И здесь важная деталь — запланированные задания в Work.
🔄Система, как палка (простая):
1. Сливаю все задачи в Todoist голосом (у них есть такая фича). Без меток, прио…
Рассказываю, как это собиралось.
1. Адаптация сценария и все промпты — Claude Fable с кастомным скиллом-промтером под Seedance 2. Разбили сюжет на 15-секундные сегменты (ориентир — 4 сцены и ~35 слов диалога), дальше он выдавал промпт под каждый кусок (а я редактировал и приносил обратно скриншоты фейлов).
2. На каждый такой кусок — от четырёх до восьми вариаций (всего вышло под сто). Первые уродцы — проверить пром…
🔥426❤103👍48🤯7👻4😱3🤔1
Signed Dobrokotov
Showing the 12 most recent of 26 posts we hold for @strangedalle. 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
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 39 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.
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.
Handles this channel named that no longer answer
Dead references
1
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
1
vacant every time we have ever looked
@strangedalle named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@sketch named in 7 posts, 9 September 2026 – 17 September 2026
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 27 August 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
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.
Технологии | Нейросети | Боты @aiaiai · 176,423 Telegram ranks this channel #4 of 93 here — alongside 92 others — read 12 August 2026
Neural Shit @NeuralShit · 53,680 Telegram ranks this channel #6 of 92 here — alongside 91 others — read 24 August 2026
Метаверсище и ИИще @cgevent · 52,361 Telegram ranks this channel #7 of 92 here — alongside 91 others — read 25 August 2026
Neurogen @neurogen_news · 22,930 Telegram ranks this channel #11 of 88 here — alongside 87 others — read 19 September 2026
Tips AI | IT & AI @tips_ai · 25,376 Telegram ranks this channel #13 of 95 here — alongside 94 others — read 14 September 2026
Denis Sexy IT 🤖 @denissexy · 137,325 Telegram ranks this channel #14 of 95 here — alongside 94 others — read 13 August 2026
Lama AI @lama_channel_gpt · 24,736 Telegram ranks this channel #18 of 90 here — alongside 89 others — read 15 September 2026
Силиконовый Мешок @prompt_design · 85,657 Telegram ranks this channel #21 of 96 here — alongside 95 others — read 18 August 2026
Смотри, Морозов и ИИ @mmmorozov · 61,416 Telegram ranks this channel #24 of 96 here — alongside 95 others — read 23 August 2026
эйай ньюз @ai_newz · 96,889 Telegram ranks this channel #24 of 94 here — alongside 93 others — read 16 August 2026
Малоизвестное интересное @theworldisnoteasy · 74,000 Telegram ranks this channel #25 of 94 here — alongside 93 others — read 19 August 2026
НейроProfit | Соня Pro Ai @NeuralProfit · 23,400 Telegram ranks this channel #27 of 96 here — alongside 95 others — read 18 September 2026
🟡NeuroGraph @neyr0graph · 34,435 Telegram ranks this channel #30 of 90 here — alongside 89 others — read 3 September 2026
Neural Pony @neuralpony · 195,187 Telegram ranks this channel #30 of 61 here — alongside 60 others — read 13 August 2026
involta - технологии, наука, будущее, IT, интернет! @involta · 34,123 Telegram ranks this channel #33 of 89 here — alongside 88 others — read 3 September 2026
Двоичный кот @binarcat · 30,854 Telegram ranks this channel #35 of 93 here — alongside 92 others — read 9 September 2026
CyberYozh AI Security @CyberYozh_AI_security · 26,576 Telegram ranks this channel #37 of 91 here — alongside 90 others — read 12 September 2026
Сиолошная @seeallochnaya · 79,594 Telegram ranks this channel #37 of 97 here — alongside 96 others — read 19 August 2026
Serge_AI 1.0 @serge_ai · 57,484 Telegram ranks this channel #46 of 99 here — alongside 98 others — read 23 August 2026
UX Live 🔥 @uxlive · 35,985 Telegram ranks this channel #75 of 86 here — alongside 85 others — read 2 September 2026
e/acc @cryptoEssay · 62,598 Telegram ranks this channel #79 of 96 here — alongside 95 others — read 21 August 2026
Ряды Фурье @Fourier_series · 42,189 Telegram ranks this channel #81 of 93 here — alongside 92 others — read 29 August 2026
Связь Вишневского @pokamojno · 24,171 Telegram ranks this channel #84 of 98 here — alongside 97 others — read 16 September 2026
LLM под капотом @llm_under_hood · 29,146 Telegram ranks this channel #92 of 96 here — alongside 95 others — read 9 September 2026
This channel appears in 25 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. 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 19 September 2026 — this
entry's latest reading, not the date you are reading this.
“Ai molodca” (@strangedalle), 46,847 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/strangedalle.
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.