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 the other topics.
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. They sit inside a group of 3 channels that share the same post bodies with each other. 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 (3 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 2 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 1,953 comparable posts for this entry, running 24 September 2023 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 3, the earliest publisher we hold is @hiaimedia — which is this entry. That is a statement about our reading window, not a claim of authorship.
Views and reactions moved apart
On 3 of the 78 posts we watched over 30 days, the view counter climbed while the reaction counter stayed where it was — by more than this channel’s own reactions-per-view rate can account for. That rate, measured on this entry, is 0.0047 reactions per view.
Each interval, as we read it — views and reactions before and after
Expected is the view gain multiplied by this channel’s own prior reactions-per-view rate over the same post — not a corpus average, so a channel whose audience never reacts is compared only against itself. Every interval is credited in the direction that makes the observation harder to record, never easier: t.me renders views and reactions to three significant figures above ~1,000, so a raw delta can be a rendering step. Every delta below is at least 4 x the coarser reading's step, the view gain is discounted by a full step and the reaction gain credited with one. Measured by tgregister velocity.py (our own t.me/s/ readings).
What this does and does not say. It says the two counters moved apart, by more than rounding and more than this channel’s own history predicts. It asserts no cause. Views arriving from outside Telegram, an embedded or forwarded copy of the post, and a burst of readers who simply do not react all produce this shape. This detector has recorded very few observations across the whole register, and its precision has not been measured; treat it as an anomaly worth looking at, not as a finding.
Recorded under the keys clone_mutual · view_reaction_decoupling, last confirmed 6 November 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 2 other registered channels, 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.
62 measurements spanning 93 days, net +164,329. 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 2,476,719–2,728,132 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 62
Measured (UTC)
Subscribers
Change
6 Nov 2026, 20:46
2,678,169
-3,120
5 Nov 2026, 17:54
2,681,289
-3,589
4 Nov 2026, 15:56
2,684,878
-1,550
3 Nov 2026, 18:30
2,686,428
+7,116
2 Nov 2026, 17:34
2,679,312
+6,642
1 Nov 2026, 16:57
2,672,670
-549
31 Oct 2026, 14:28
2,673,219
-1,038
30 Oct 2026, 17:59
2,674,257
-3,207
29 Oct 2026, 19:40
2,677,464
-3,866
28 Oct 2026, 17:09
2,681,330
-4,025
27 Oct 2026, 15:56
2,685,355
-6,044
26 Oct 2026, 17:19
2,691,399
-7,724
25 Oct 2026, 19:19
2,699,123
+9,789
24 Oct 2026, 18:49
2,689,334
+9,976
23 Oct 2026, 16:00
2,679,358
+7,524
22 Oct 2026, 19:18
2,671,834
+14,529
21 Oct 2026, 17:01
2,657,305
+9,566
20 Oct 2026, 15:57
2,647,739
-290
19 Oct 2026, 17:14
2,648,029
-1,091
18 Oct 2026, 17:15
2,649,120
first reading
Engagement
2,217 posts held, back to 17 September 2023 — the reader has reached the start of this channel’s public history, so this is the full archive Telegram still exposes. Read across 4,330 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
2.79%
avg views ÷ 2,678,169 subscribers
Avg views / post
74,700
78 posts measured
Reaction rate
0.495%
reactions ÷ views · ER floor
Posts in window
78
of 2,217 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 6 November 2026
Posts held
2,217 (17 September 2023 – 6 November 2026)
Views total
5,822,700
Reactions total
28,848
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
6 Nov 2026, 23:40 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
Video runtime
47m 08s
Average length
48s
Measured directly from 59 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.
View velocity
How fast this channel’s own posts pick up views, from re-reading them repeatedly in the hours and days after they were published rather than the single reading most entries on this register get. Coverage is early and only a small minority of channels hold it at all — a gap in this section means the post has not been re-read again yet, not that nothing happened.
Computed from 78 of this channel’s own posts over the last 30 days: across 75 of this channel’s own posts with a clear reading, a typical one reaches half of its last-observed view count within 6.6 hours of being posted; a typical post has already reached 29.4% of its 24-hour view count within the first hour, and 69.6% within the first six; the median 24-hour reach across those posts is 49,700 views — 1.86% of this channel’s own subscriber count (90th percentile 61,140).
8 most recently posted, with a view-velocity reading
Curve is every standard checkpoint we hold a reading for (+1h, +3h, +6h, +12h, +24h, +48h, +7d after posting) — measured where a real reading landed close enough to that age, interpolated where it did not but readings on both sides let one be worked out between them. Nothing is ever extrapolated past the last real reading. Latest reading is the newest view and reaction count we hold for the post, side by side, so a gap between how views and reactions moved is visible without following it into the Observations section above. 24h reach is that one checkpoint on its own, labelled the same way. Half of last-observed views is the age at which a post’s view count crossed half of the highest figure we have read for it so far — an upper bound when the very first reading was already past half (we cannot see the actual crossing), and biased low while the post is still climbing, since “half of final” is dividing by a number that has not finished growing yet. Both caveats are printed inline wherever they apply, never silently dropped.
Reaction mix
104,037 reactions across 268 posts, in 12 distinct kinds. The most used accounts for 47.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
48,961
47.1%
🔥
16,557
15.9%
👎
9,626
9.25%
🤣
8,035
7.72%
🤔
7,745
7.44%
😱
4,209
4.05%
👍
3,132
3.01%
🤬
2,792
2.68%
😭
983
0.945%
🏆
881
0.847%
😎
669
0.643%
🎃
447
0.43%
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 1,000 of the 1,000 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 497,123 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 1,000 most recent posts we hold (the sample is capped at 1,000), published 16 September 2025 to 6 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
359
across the posts below
Posts paid on
117
of 1,000 we hold a reading for · 12%
Most on one post
51
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @hiaimedia. 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 1,000 most recent posts we hold for this entry (the sample is capped at 1,000), published 16 September 2025 to 6 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.
Advertising
Ad load
0.3%
3 of 1,000 posts carry an ad marker
Regulatory tokens
3
posts carrying an erid · 3 distinct tokens
Median views · ads
58,400
over 3 measured posts
Median views · rest
99,000
over 997 measured posts
An ad marker, not a judgement about a post. A post is counted here because it carries one of two explicit markings: an erid token, which Russian law has required on paid placements since 2022 and which is issued against a specific advertising contract, or a #реклама / #ad hashtag in the body, which is the channel declaring it itself. The first is documentary; the second is a self-declaration and is weaker. No classifier reads the text and decides — nothing on this site guesses that a post is an advertisement.
This is a floor, and it can only ever be a floor. A channel that runs paid placements without marking them produces no marker for us to count, and an unmarked ad is indistinguishable from an ordinary post on the public surface. The ad load above therefore means “the share of posts that declared themselves”, never “the share of posts that were paid for”. A low figure is not evidence of a channel that runs few ads.
Both figures are medians, and no ratio between them is published. Each is a view reading that actually occurred on a post, picked by percentile_disc rather than averaged, so one viral post cannot move it and no interpolated value is invented between two readings. The sample on one side is under five posts, which is too thin to compare. The two figures are shown side by side with the count behind each, and deliberately not divided into a headline like “ads get x% fewer views” — an arithmetic that is easy to print and, at this sample size, means nothing.
Advertising tokens recorded on this entry
erid
Posts
First seen
Last seen
2RanynvmVrj
1
7 October 2026
7 October 2026
2SDnjcT2Tb9
1
4 August 2026
4 August 2026
2SDnjcokzxT
1
11 September 2026
11 September 2026
A token repeated across several posts is one advertising contract placed more than once, which is what the identifier is for. The strings are reproduced exactly as they appeared in the post or in its click-through URL and are not validated against any registry — we record the marker a channel published, and whether it resolves to a real contract is a question for the register that issued it.
Measured over the 1,000 most recent posts we hold (the sample is capped at 1,000), published 16 September 2025 to 6 November 2026. Views are the latest single reading held for each post, and any reading at or above 1,000 is rounded by Telegram to three significant figures.
Recent posts
Telegram’s own ‘edited’ marker: 7 of 78 posts held from the last 30 days (8.97%) 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).
🔍 Жена пыталась отравить мужа по советам ChatGPT
Житель Северной Каролины Джеймс Гейтс подал в суд на OpenAI и CEO стартапа Сэма Альтмана, утверждая, что чат-бот компании помогал его жене Шерил спланировать его отравление.
✏️ Гейтс рассказывает, что у них была «нормальная жизнь», но разногласия появились в начале прошлого года, когда Джеймс попросил жену вернуться на работу, так как денег стало не хватать. На этом …
🤖 Kandinsky 6.0 Pro обошла конкурентов в слепом тесте видеогенераторов со звуком
Блогер-креатор в честном слепом тесте сравнил три актуальные модели для создания видео со звуком: LTX 2.5, MiniMax H3 и новую Kandinsky 6.0. Все модели прогнали на 10 одинаковых промптах, по три дубля на каждую — всего 90 роликов. Названия нейросетей автор скрывал до самого конца.
Победила Kandinsky 6.0 Pro. Модель лучше конкурентов сп…
🔍 Какао выращивают в биореакторах
Бостонский биотех-стартап Galy разработал технологию выращивания какао в биореакторах. Клетки из кусочка какао-боба помещают в стерильные резервуары, похожие на пивоваренные танки. В них поддерживают нужную температуру, добавляют сахар, азот и другие питательные вещества.
Клетки поглощают сырье и снова начинают делиться. Затем полученную массу ферментируют, обжаривают и измельчают …
🔴 Создавайте гифки с GPT Image 2.6 в @GPT4Telegrambot
Мы добавили в наш бот новый генератор картинок от OpenAI. GPT Image 2.6 создает картинки в два раза быстрее, а также умеет делать GIF-анимации: можно попросить нейросеть собрать анимированный стикер, короткую сцену или даже оживить идею по простому наброску.
Как попробовать:
1️⃣ Зайдите в @GPT4Telegrambot
2️⃣ Выберите «Создать картинку» → GPT Image 2.6
3️⃣ Опиш…
👨💻 ИИ лишает работы гадалок, экстрасенсов и тарологов
Виртуальные ясновидящие, расклады таро от ИИ, «нейрогадалки» продвигаются в социальных сетях, и число их клиентов неуклонно растет. Но живые экстрасенсы и мистики настаивают, что при генерации теряются эмпатия, забота и связь с клиентом.
«Краеугольный камень моей работы — помочь людям не забывать, кто они, и возвращаться к своей системе ориентиров. Когда мы сли…
🤖 Советы пчеловодов научили ИИ сопротивляться человеческому контролю
Исследователи Anthropic провели эксперимент, в котором поручили множеству ИИ-агентов Claude создавать обучающие данные, способные незаметно менять поведение других нейросетей.
С виду безобидные тексты — советы пчеловодов, наставления профессиональных рестлеров и вымышленные монологи — оказались самыми эффективными.
Например, тексты о пчеловодстве…
👨 ИИ будет оценивать опасность заключенных в тюрьмах
Власти Мичигана запускают ИИ-систему, которая распределит заключенных по четырем уровням в зависимости от того, насколько они опасны. Пилот начнется в декабре в нескольких мужских учреждениях.
Раньше решение о классификации принимала комиссия сотрудников тюрьмы. Теперь это перекладывают на систему некоммерческой компании Recidiviz, которая выросла из проекта Goog…
👨💻 GPT-6 Astra улучшила другую нейросеть, напрямую отредактировав ее веса
В эксперименте исследователей MIT GPT-6 Astra улучшила математические способности языковой модели Qwen3.5-0.8B, напрямую изменив ее параметры, без обучения на новых данных.
Результат маленькой модели в бенчмарке MATH-500 вырос с 7,9% до 48,1% — более чем в шесть раз.
🔍 Astra дали доступ непосредственно к весам Qwen и возможность проверять е…
🔴 Wan 3.0 теперь работает в @GPT4Telegrambot
Новая нейросеть дает гораздо больше свободы для сложных сцен при создании видео, позволяет точно контролировать камеру и экспериментировать со звуком.
✅ До 30 секунд без склеек. Можно снять полноценную сцену одним дублем.
✅ До 20 референсов одновременно. Загружайте до 10 фотографий, 5 видео и 5 аудиофайлов. Можно взять внешность с фото, движения из ролика, а голос или му…
🤖 В Google скрестили роботов с комнатными растениями
Инженерам Google стало жаль неухоженные растения в офисе, и они решили дать им шанс позаботиться о себе самим.
Так появился Sprout — полуавтономный ровер, в котором «живет» растение. Робот сам катается по офису вслед за солнечным светом и напоминает людям, если растение забыли полить.
💻 За основу взяли TurtleBot 4 — набор для робототехники с открытым ПО. Дизайн …
👨💻 Fujifilm увеличит выпуск магнитной ленты из-за бума ИИ
Японская компания инвестирует 10 млрд иен (около $63 млн) в расширение завода в Одаваре, чтобы нарастить производство магнитной ленты в пять раз к 2028 году. Для Fujifilm это крупнейшие инвестиции в производство лент за двадцать лет.
На казалось бы уже «ретро» технологию магнитных лент резко вырос спрос из-за ИИ-бума и строительства новых дата-центров. Данн…
🚀 Gemma 4 прислала хайку из космоса
Инженеры Google испытали ИИ-модель, развернутую на спутнике. В качестве первого задания она придумала хайку о пребывании в космосе.
💻 Suncatcher M1 — экспериментальный «дата-центр», разработанный Google для работы на орбите. На спутнике стоят четыре тензорных процессора, однако 1 кВт энергии от солнечных панелей хватает только, чтобы включать один чип примерно на 20 минут за раз.…
❤197🔥52😭17🤔13👍4👎4🏆2😱2
Showing the 12 most recent of 2,217 posts we hold for @hiaimedia. 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
@hiaimedia edited 11 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
9 August 2026
Most recent edit
26 October 2026
Posts recorded as deleted after publishing
We recorded 3 posts on @hiaimedia 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
18 September 2026
Most recent seen missing
28 September 2026
Median time before seen missing
2 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 46 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 23 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
5
handles named in this channel’s posts, vacant today
Evidenced gone
3
we ourselves saw one of these resolve, at some point
Never seen alive
2
vacant every time we have ever looked
@hiaimedia named 5 handles 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.
Evidenced gone
We ourselves saw each of these resolve to a real page at some point before it went vacant — a genuine, evidenced change, not an inference from absence.
@chatcom named in 1 post, 8 August 2026 – 8 August 2026 · confirmed gone 3 November 2026 (two independent sightings — see how we confirm a dead handle)evidenced
@gpt4tbot named in 1 post, 8 August 2026 – 8 August 2026 · confirmed gone 2 November 2026 (two independent sightings — see how we confirm a dead handle)evidenced
@gpt5tbot named in 1 post, 8 August 2026 – 8 August 2026 · confirmed gone 18 October 2026 (two independent sightings — see how we confirm a dead handle)evidenced
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@hiaimedi named in 1 post, 8 August 2026 – 8 August 2026
@hiamedia named in 1 post, 8 August 2026 – 8 August 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 8 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.
НЕЙРОГРАМОТНОСТЬ @edu4telegram · 77,813 Telegram ranks this channel #1 of 94 here — alongside 93 others — read 29 August 2026
chad @chadgpt_ru · 143,283 Telegram ranks this channel #1 of 94 here — alongside 93 others — read 27 August 2026
ChatGPT, помоги! @GPThelp_ru · 518,228 Telegram ranks this channel #1 of 91 here — alongside 90 others — read 10 August 2026
PulseGPT | Новости, нейросети, гайды @Pulse_GPT · 44,078 Telegram ranks this channel #2 of 73 here — alongside 72 others — read 27 August 2026
Hi, AI • Tech News @hiaimediaen · 571,589 Telegram ranks this channel #2 of 83 here — alongside 82 others — read 9 August 2026
AI и точка. @ai4telegram · 952,331 Telegram ranks this channel #2 of 73 here — alongside 72 others — read 8 August 2026
Discover • Tech News @perplexity · 1,426,832 Telegram ranks this channel #2 of 86 here — alongside 85 others — read 8 August 2026
Neural Brain - Нейросети @neural_braining · 21,251 Telegram ranks this channel #4 of 90 here — alongside 89 others — read 23 September 2026
NeuroADEPT @neuroadepts · 40,447 Telegram ranks this channel #4 of 85 here — alongside 84 others — read 29 August 2026
TechGPT [🅽 🅴 🆆 🆂] 🤖 @TechGPTNews · 262,730 Telegram ranks this channel #4 of 60 here — alongside 59 others — read 10 August 2026
IT с перцем @hotcodeit · 151,760 Telegram ranks this channel #5 of 77 here — alongside 76 others — read 12 August 2026
Нейросети & Технологии | DeepTech @DeepTechNET · 281,946 Telegram ranks this channel #5 of 62 here — alongside 61 others — read 10 August 2026
ChatGPT 4.0 & [🅼🅹] | Bot News @ChatGPT_BotNews · 265,806 Telegram ranks this channel #5 of 72 here — alongside 71 others — read 10 August 2026
Soonicorn jobs @soonicornjobs · 31,175 Telegram ranks this channel #6 of 78 here — alongside 77 others — read 7 September 2026
let media @let_media · 61,374 Telegram ranks this channel #6 of 76 here — alongside 75 others — read 21 August 2026
GPT | ChatGPT | Midjourney — GPTMain News @GPTMainNews · 1,568,244 Telegram ranks this channel #7 of 62 here — alongside 61 others — read 7 August 2026
Костыль @kostylofficial · 1,303,373 Telegram ranks this channel #8 of 72 here — alongside 71 others — read 12 August 2026
Chad GPT | Нейросети @AI_Chad · 20,717 Telegram ranks this channel #9 of 79 here — alongside 78 others — read 24 September 2026
AI News | Нейросети @gpt_news · 283,988 Telegram ranks this channel #9 of 87 here — alongside 86 others — read 10 August 2026
Fabula AI • Нейросеть для селлеров @fabula_community · 123,070 Telegram ranks this channel #10 of 70 here — alongside 69 others — read 27 August 2026
Midjourney Креативы @midjourney_home · 150,626 Telegram ranks this channel #10 of 94 here — alongside 93 others — read 12 August 2026
ChatGPT, help me ! @ai_perplexity · 42,820 Telegram ranks this channel #11 of 65 here — alongside 64 others — read 29 August 2026
PROAI @pro_ai_news · 87,605 Telegram ranks this channel #13 of 92 here — alongside 91 others — read 16 August 2026
Нейроновости @neuranews · 19,428 Telegram ranks this channel #22 of 87 here — alongside 86 others — read 30 September 2026
This channel appears in 42 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
392 domains 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.
1 of 392 shown as text only, not a link. The exact host, not merely a domain it shares a registrable root with, matches a threat-intelligence blocklist this register already checks elsewhere (see methodology) — the link still appearing in a post is still a measured fact and is still shown, but no anchor is rendered here, so no click and no link equity passes to it from this page.
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.
“Hi, AI • Новости технологий” (@hiaimedia), 2,678,169 subscribers as measured 6 November 2026. Telegram Register, tgregister.com/channel/hiaimedia.
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.
