Technology — 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 8 August 2026 and assigned it the closest of 31 fixed categories, at 100% 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 25 comparable posts for this entry, running 3 August 2026 to 7 August 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 @iPumpBrain — 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 7 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.
36 measurements spanning 51 days, net -2,015. 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 182,438–185,057 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 36
Measured (UTC)
Subscribers
Change
26 Sept 2026, 09:36
182,740
-206
19 Sept 2026, 11:37
182,946
-83
17 Sept 2026, 03:36
183,029
-106
15 Sept 2026, 05:41
183,135
-85
13 Sept 2026, 12:58
183,220
-82
11 Sept 2026, 18:20
183,302
-40
9 Sept 2026, 05:58
183,342
-49
5 Sept 2026, 19:16
183,391
-27
3 Sept 2026, 20:55
183,418
-49
2 Sept 2026, 10:24
183,467
-17
1 Sept 2026, 12:44
183,484
-10
31 Aug 2026, 14:23
183,494
-21
30 Aug 2026, 15:47
183,515
+49
29 Aug 2026, 17:07
183,466
-26
28 Aug 2026, 18:34
183,492
-46
27 Aug 2026, 19:48
183,538
-57
26 Aug 2026, 19:48
183,595
-24
25 Aug 2026, 21:16
183,619
-80
24 Aug 2026, 19:14
183,699
-94
23 Aug 2026, 02:07
183,793
first reading
Engagement
352 posts held, back to 3 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 114 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
2.63%
avg views ÷ 182,740 subscribers
Avg views / post
4,810
189 posts measured
Reaction rate
0.899%
reactions ÷ views · ER floor
Posts in window
189
of 352 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 187 of 189 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 27 September 2026
Posts held
352 (3 August 2026 – 27 September 2026)
Views total
909,089
Reactions total
8,090
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
27 Sept 2026, 12:38 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
≈8,630
Videos
≈7,800
Links
≈14,500
Lifetime counters from Telegram’s own channel header, read 27 September 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
2h 16m
Average length
43s
Measured directly from 191 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
14,936 reactions across 342 posts, in 6 distinct kinds. The most used accounts for 30.2% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
😁
4,513
30.2%
🔥
3,493
23.4%
👍
2,563
17.2%
🥴
2,247
15.0%
🤯
1,451
9.71%
🤔
669
4.48%
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 349 of the 352 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 15,334 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 352 most recent posts we hold, published 3 August 2026 to 27 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.
В сети выкатили гайд по сочетанию вина и сыра по всем правилам гастрономии — чем нежнее сыр, тем легче должно быть вино
Записываем:
▪️Буррата — Франчакорта
▪️Моцарелла — Альбариньо
▪️Бюш-де-Шевр — молодой Шенен Блан
▪️Валансе — Карриканте или Ркацители на осадке
▪️Гауда — Шардоне без дуба
▪️Качотта — Кортезе
▪️Оссо-Ирати — Гарнача со старых лоз
▪️Камамбер — Креман де Бургонь
▪️Нёшатель — Гевюрцтраминер
▪️Горгонзола …
В интернете набрал популярность «IQ-тест» для котов.
Нужно сложить пальцы в жест ОК, положить на ладонь вкусняшку и предложить её коту.
Если питомец быстро понимает, что лакомство можно просто взять с ладони, значит, он умный. А если упорно пытается добраться до него через отверстие между пальцами, то у вас дурачок.
Прокачай Мозг
В Японии устраивают книжные рейвы
Люди собираются вместе и читают одну и ту же книгу под эмбиент-музыку и при приглушённом свете.
Причём такой формат «вечеринок» набирает популярность по всему миру.
Рейвы, когда тебе за 30
Прокачай Мозг
Lacoste — ВСЁ: в России начали продавать «крокодули» и «акудилды».
По словам продавца, это вездеходные тяги, которые идеально подходят для наших дорог.
Прокачай Мозг
Claude уничтожил проект разработчика всего за 1,5 минуты.
Реддитор попросил ИИ создать копию проекта, но вместо этого нейронка удалила около 48 тысяч файлов из рабочей директории, включая данные Git. Всё произошло за 103 секунды. Восстановить практически ничего не удалось.
После этого ИИ-агент написал: «Я кое-что сломал».
Прокачай Мозг
Warner Bros. показала первые кадры из НОВОГО фильма «Властелин колец: Охота на Голлума» — на них герой возвращается домой, к двери Бильбо Бэггинса.
Лица хоббита не видно, но фанаты сразу узнали Фродо: к роли снова вернётся Элайджа Вуд. В подписи к тизеру студия намекнула на осеннюю атмосферу Шира:
«В Шир пришла осень…»
Режиссёром фильма выступает Энди Серкис — исполнитель роли Голлума в оригинальной трилогии. Он та…
В Индии сделали бога Ганешу в стиле Subway Surfers и теперь приносят ему дары.
В интернете пишут, что это в честь множества индусов, которых сбивают поезда, когда те снимают видео
Прокачай Мозг
В США создали препарат, который полностью восстанавливает двигательные функции после инсульта
DDL-920 — первое лекарство, способное обеспечить комплексную реабилитацию без сложной длительной физиотерапии
Прокачай Мозг
Американский пекарь готовит максимально проклятые пироги в виде зловещих и страдающих лиц, полных ужаса.
Причём это реальные съедобные пироги со сладкой начинкой, которые он превращает в нечто кошмарное.
Когда вкладываешь в готовку всю душу (чужую)
Прокачай Мозг
Любители острого живут дольше: учёные доказали, что перец продлевает жизнь!
Учёные из Гарварда выяснили: если есть острое хотя бы раз в день, риск умереть от болезней снижается на 14%.
Перец и специи содержат биоактивные вещества, которые снижают «плохой» холестерин и помогают держать триглицериды в норме.
Прокачай Мозг
Воздух царапает бордовый iPhone 18 Pro. За четыре дня блогер превратил корпус новинки в доказательство того, что чехол все-таки не такая плохая идея.
Забавно, что на старом iPhone 15 Pro Max за три года у него не появилось ни одной царапины.
Что там по обновке, коллеги?
Прокачай Мозг
😁19🥴8👍3🔥2
Showing the 12 most recent of 352 posts we hold for @iPumpBrain. 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.
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 16 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.
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 11 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.
Это интересно! @very_interesno · 172,515 Telegram ranks this channel #1 of 85 here — alongside 84 others — read 12 August 2026
Мир Фактов @MirFacto · 140,692 Telegram ranks this channel #2 of 80 here — alongside 79 others — read 13 August 2026
Наука дня | Факты @sciensday · 57,561 Telegram ranks this channel #3 of 67 here — alongside 66 others — read 23 August 2026
Популярная наука @PopularNauka · 20,500 Telegram ranks this channel #4 of 63 here — alongside 62 others — read 27 September 2026
КиберПанк | Технологии Будущего | Technology @technology_future_cyberpunk · 37,246 Telegram ranks this channel #4 of 84 here — alongside 83 others — read 1 September 2026
Саморазвитие в Опросах @samorasvitia_opros · 157,214 Telegram ranks this channel #4 of 87 here — alongside 86 others — read 12 August 2026
Первая передача @firstgear_channel · 198,531 Telegram ranks this channel #4 of 84 here — alongside 83 others — read 11 August 2026
НА ГРАНИ @nagrani_video · 37,136 Telegram ranks this channel #5 of 67 here — alongside 66 others — read 1 September 2026
Animal Planet @animal_planeta · 117,755 Telegram ranks this channel #5 of 86 here — alongside 85 others — read 14 August 2026
Главная Дорога @Glavnayadoroga_tg · 205,406 Telegram ranks this channel #5 of 86 here — alongside 85 others — read 11 August 2026
За рулём @driverone · 459,529 Telegram ranks this channel #5 of 88 here — alongside 87 others — read 10 August 2026
Улётные приколы😂 @prikoly · 370,798 Telegram ranks this channel #7 of 85 here — alongside 84 others — read 10 August 2026
Математика | Опросы @mathematics_channeI · 25,516 Telegram ranks this channel #8 of 63 here — alongside 62 others — read 14 September 2026
Очевидные вещи @ochewid · 55,247 Telegram ranks this channel #8 of 88 here — alongside 87 others — read 23 August 2026
Удивительный Мир 🏝 @travelmir_tg · 166,683 Telegram ranks this channel #9 of 74 here — alongside 73 others — read 12 August 2026
МЕХАНИК @imehanik · 320,465 Telegram ranks this channel #10 of 85 here — alongside 84 others — read 10 August 2026
MATEMATIKA🧠 @mathrus3 · 54,800 Telegram ranks this channel #13 of 77 here — alongside 76 others — read 23 August 2026
National Geographic @Nationall_Geoographic · 50,223 Telegram ranks this channel #14 of 83 here — alongside 82 others — read 25 August 2026
Live Nature @priroda_animal · 113,063 Telegram ranks this channel #14 of 85 here — alongside 84 others — read 14 August 2026
МАСТЕР @macters · 233,958 Telegram ranks this channel #16 of 84 here — alongside 83 others — read 11 August 2026
Глубина @thedeepsee · 41,949 Telegram ranks this channel #17 of 65 here — alongside 64 others — read 29 August 2026
ЯТХ @ytx_sex_public · 57,835 Telegram ranks this channel #17 of 68 here — alongside 67 others — read 25 August 2026
Простые Рецепты @prostoy_retsept · 581,949 Telegram ranks this channel #17 of 76 here — alongside 75 others — read 10 August 2026
Терабит: айти технологии @tbite · 28,050 Telegram ranks this channel #18 of 85 here — alongside 84 others — read 9 September 2026
This channel appears in 79 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.
Domains linked from posts
One domain this channel’s own posts have linked to, measured by scanning the post bodies themselves — not the channel’s description, which is the separate Declared links section below when this entry has one. Appearing here is not a claim about who runs the linked site or why the channel linked to it; an advertisement, a news citation and a malicious link all leave the same kind of row.
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 26 September 2026 — this
entry's latest reading, not the date you are reading this.
“Прокачай Мозг: Айти, Тренды, Технологии” (@iPumpBrain), 182,740 subscribers as measured 26 September 2026. Telegram Register, tgregister.com/channel/iPumpBrain.
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.