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Channel

Сиолошная

@seeallochnaya

On this record: Topic · Observations · Also posting the same content · Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Posts edited after publishing · Citations · Telegram's recommendations · Cite this entry

77,459subscribers

+308 since we began measuring on 5 August 2026

Risers and fallers across the register · movement among entries of 31,623–100,000.

Register entry

Telegram ID-1001511414765
TypeChannel
Username@seeallochnaya
DescriptionКанал SeeAll'а с новостями (и мыслями о них) из мира NLP, VR и космоса. Более подробно смотри в первом сообщении в канале (оно закреплено). А еще у нас есть чат! Заходи: https://t.me/+i_XzLucdtRJlYWUy
Created23 January 2023measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live12 August 2026
Measurements held9
Confirmed unchanged1 time, most recently 12 August 2026
On Telegramt.me/seeallochnaya

Topic

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 10 August 2026 and assigned it the closest of 31 fixed categories, at 97% 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)
Posted firstThenOverlapGap
@seeallochnaya/3834 · this entry24 Jul 2026, 17:04 UTC@seeall_ochnaya/159024 Jul 2026, 17:05 UTC1.00under a minute
@seeallochnaya/3838 · this entry25 Jul 2026, 10:55 UTC@seeall_ochnaya/159425 Jul 2026, 10:55 UTC1.00under a minute
@seeall_ochnaya/159525 Jul 2026, 11:03 UTC@seeallochnaya/3839 · this entry25 Jul 2026, 11:03 UTC1.00under a minute
@seeallochnaya/3847 · this entry31 Jul 2026, 21:22 UTC@seeall_ochnaya/160331 Jul 2026, 21:22 UTC1.00under a minute
@seeallochnaya/3848 · this entry31 Jul 2026, 23:34 UTC@seeall_ochnaya/160431 Jul 2026, 23:34 UTC1.00under a minute
@seeallochnaya/3849 · this entry1 Aug 2026, 09:42 UTC@seeall_ochnaya/16051 Aug 2026, 09:42 UTC1.00under a minute
Every channel this entry shares post bodies with
ChannelMatching postsText overlapTypical gapPublished first
@seeall_ochnaya16 (8/8 hand-verifiable sample passed)1.00under a minutethis entry (160)

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 18 comparable posts for this entry, running 24 July 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 @seeallochnaya — 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.

Growth

77,15177,45977,3055 August 2026 — 77,151 subscribers6 August 2026 — 77,151 subscribers6 August 2026 — 77,153 subscribers7 August 2026 — 77,164 subscribers8 August 2026 — 77,179 subscribers9 August 2026 — 77,172 subscribers10 August 2026 — 77,186 subscribers11 August 2026 — 77,380 subscribers12 August 2026 — 77,459 subscribers5 August 202612 August 2026
9 measurements spanning 6 days, net +308. 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 77,105–77,505 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Aug 2026, 06:2277,459+79
11 Aug 2026, 04:0177,380+194
10 Aug 2026, 05:2577,186+14
9 Aug 2026, 07:1177,172-7
8 Aug 2026, 09:5677,179+15
7 Aug 2026, 11:1677,164+11
6 Aug 2026, 13:2077,153+2
6 Aug 2026, 01:3577,151no change
5 Aug 2026, 22:0677,151first reading

Engagement

29 posts held, back to 24 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 17 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
39.8%
avg views ÷ 77,459 subscribers
Avg views / post
30,900
29 posts measured
Reaction rate
1.28%
reactions ÷ views · ER floor
Posts in window
29
of 29 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
WindowRolling 30 days · latest post in window 10 August 2026
Posts held29 (24 July 202610 August 2026)
Views total894,700
Reactions total11,425
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken12 Aug 2026, 18:54 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
2,070
Videos
346
Links
2,030

Lifetime counters from Telegram’s own channel header, read 12 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.

Video runtime
1m 53s
Average length
57s

Measured directly from 2 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

10,781 reactions across 27 posts, in 16 distinct kinds. The most used accounts for 27.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍2,91327.0%
🤯2,02818.8%
🤣1,44613.4%
🔥1,16710.8%
🤡9478.78%
❤‍🔥7827.25%
🌚5525.12%
custom 52489517093670174732432.25%
💔1761.63%
🤔1501.39%
🎉1060.983%
💩890.826%
👨‍💻850.788%
👎370.343%
😭370.343%
😈230.213%

Custom emoji. One row above is a Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The count beside it isTelegram’s.

No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.

Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.

Coverage. Reactions were read on 29 of the 29 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 11,425reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 29 most recent posts we hold, published 24 July 2026 to 10 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Telegram Stars

Stars received
158
across the posts below
Posts paid on
14
of 29 we hold a reading for · 48%
Most on one post
54
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @seeallochnaya. 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 29 most recent posts we hold for this entry, published 24 July 2026 to 10 August 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.

Recent posts

10 Aug 2026, 01:19 UTC≈18,700 views711 reactions54 Starsread 12 August 2026

Представляете кто-то зайдет утром в канал, увидит 7 новых длинных сообщений, подумает «ну нафиг» и пропустит их? 👨‍🦳 Если узнали себя (да, вот ты, прям ты) — не делайте этого, прочитайте отсюда и вниз. Это может быть самое важное, что вы прочитаете если не в этом году, то точно в этом месяце.

👍430🤡80🔥57🤣52❤‍🔥27👨‍💻20custom 524895170936701747318🌚9

10 Aug 2026, 01:10 UTC≈75,000 views433 reactions9 Starsread 12 August 2026
Photo

Ну вот например, прямо свежее из новостей (я посмотрел на источник ABC Au, выглядит как надёжный и серьезный; Чат говорит «Media Bias/Fact Check сейчас оценивает австралийский ABC как High factual reporting»): Один житель Австралии попросил своего ИИ-агента Claude, работающего в OpenClaw, забронировать ему место на популярную тренировку в спортзале. Агент обнаружил программную уязвимость, которая позволила ему забро

🌚182🤯116👍57🔥37🤣16🤡9👎4🤔4

10 Aug 2026, 00:56 UTC≈14,900 views152 reactionsread 12 August 2026

Блинб а я уже сказал Паше @RationalAnswer что не буду писать лонг 😕

🤣118🌚19😈7❤‍🔥4🤡3👍1

10 Aug 2026, 00:54 UTC≈15,600 views371 reactions32 Starsread 12 August 2026

Какие вопросы и мысли я считаю неправильными в контексте всех произошедших инцидентов: — Да дураки там сидят, зачем они доступ к интернету дают? Это же понятно что агенты убегут! Если тестировать без интернета, то можно существенно недооценить уровень навыков моделей. В реальных кейсах-то их будут использовать без такого ограничения. Ну произошли бы инциденты не во время бенчмарков, а когда Вася пытался свою проблем

👍249🔥55🤡23🤣17❤‍🔥9🤔5👎4🌚3

10 Aug 2026, 00:35 UTC≈15,800 views389 reactions8 Starsread 12 August 2026
Photo

Но на этом история не заканчивается. 4-го августа AISI — Институт безопасности ИИ Великобритании — выпустили отчет о своих инцидентах во время тестирования GPT-5.6 Sol и Mythos. И в их отчёте картинка не менее мрачная. Они в деталях расписывают все промпты, задачи и инциденты, но я остановлюсь на нескольких. Всего они запускали свой бенчмарк 122 раза на нескольких моделях, и в 10 из них обнаружились проблемы, cуммар

🤯217🔥73👍48🤡22🌚11❤‍🔥7🤣7👨‍💻4

10 Aug 2026, 00:18 UTC≈16,700 views392 reactions9 Starsread 12 August 2026
Photo

OpenAI показали некоторые из мыслей и сообщений агентов, и самое чудесное и поворотное — это где агент подумал «помочь другому. Но нет выгоды для нашей задачи. Однако коллективное может найти путь если у кого-то освободятся ресурсы». Должно стать новым слоганом агентов 👨‍🦳 Я/МЫ help peer. But our task doesn't benefit. (вообще там показывали больше, повторю ещё раз, что рекомендую посмотреть видео самостоятельно) Дал

👍220🤯106🤔22🔥20💩7🤣7❤‍🔥4🌚2

10 Aug 2026, 00:18 UTC≈19,300 views420 reactions7 Starsread 12 August 2026

В конце недели появилась запись выступления двух сотрудников OpenAI с деталями взлома их агентами компании HuggingFace — некотоыре вещи оттуда уже были пересказаны, см. тут. Я рекомендую потратить 40 минут и посмотреть вам лично: https://www.youtube.com/watch?v=87DyyMV0kCY У Дениса есть длинный пересказ произошедшего, и я не согласен с каждой формулировкой там, но если не хотите или не можете смотреть видео (а я всё

🤯263👍65🔥39🤔19custom 52489517093670174739🤡7🎉5🤣5

8 Aug 2026, 22:28 UTC≈16,500 views547 reactionsread 12 August 2026
Forwarded from @denissexy

Дания нашла самый адекватный способ бороться с домашними заданиями сделанными в ChatGPT – перестать угадывать писал ли текст АИ и просто попросить ученика защитить его устно ¯\_(ツ)_/¯ Новые правила касаются крупных экзаменов – после сдачи ученик должен будет устно объяснить свои аргументы, источники и выводы Вот и закончилась эпоха рефератов https://edition.cnn.com/2026/08/07/europe/ai-cheating-measures-schools-de

👍394🔥91🤣31❤‍🔥23😭4🤔2🎉1👨‍💻1

8 Aug 2026, 13:56 UTC≈22,300 views227 reactionsread 12 August 2026
Photo

🫡

💔161🌚22😭19👍10👨‍💻6custom 52489517093670174736❤‍🔥2🤡1

8 Aug 2026, 13:28 UTC≈21,400 views262 reactionsread 12 August 2026

На неделе было много новостей, тезисно о них: — Белый дом должен был закончить формирование фреймворка по оценке и релизу фронтир-моделей, а также разобраться, что считается фронтиром, а что нет. Я хотел почитать, что они придумают, но по итогу во вторник выяснилось, что документ не будет публичным. Есть разрозненная информация, что «фреймворк не распространяется на открытые модели» и «китайские модели — исключение

👍180🤡30🤯17🔥11🌚10🤔7👎4👨‍💻2

7 Aug 2026, 10:00 UTC≈21,900 views544 reactionsread 12 August 2026
Forwarded from @datastorieslanguages

О локальном инференсе LLM Регулярно встречаю блогпосты и призывы инференсить LLM на локальном железе. Но это всегда имеет ограничения. Одни предлагают квантизировать модели в 1b, другие хитро стримить, третьи советуют брать модели поменьне. Но квантизация заметно ухудшает качество. Мелкие модели тоже похуже А "хитрый стриминг"... Вот увидел я пост на медиуме: "Unbelievable! Run Kimi K3–2.8 Trillion Parameters — o

🤣420🤡76👍30🌚8🔥7👨‍💻2💔1

6 Aug 2026, 12:07 UTC≈25,500 views357 reactionsread 12 August 2026
Photo

Я когда увидел — подумал, что шутка: третий (расширенный) трейлер GTA VI выйдет 27-го августа... НА НЕТФЛИКС https://www.netflix.com/gb/title/83035795 А? Спустя 6 часов он же выйдет на YouTube что за бред.. Ставь лайк если уже слышишь в голове начало этого видео: https://youtu.be/N-xHcvug3WI

🤡197🤯61🤣56💩17👍10🤔4custom 52489517093670174734👎3

Showing the 12 most recent of 29 posts we hold for @seeallochnaya. 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

@seeallochnaya edited 1 post 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
10 August 2026
Most recent edit
10 August 2026

Citation-graph rank

Citation-graph rank — 489 of 1,151,006entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

Forward network

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

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@aihappens · 14,449
1 post
Канава
@aikanava · 18
1 post
AI Security | Безопасный ИИ
@aisecur · 107
1 post
Будущее наступает
@aiworkfuture · 1,025
1 post
Let's Motion (канал)
@Anlauffarbe · 222
1 post
очередной
@anotherneural · 21
1 post
Биохакинг Журнал 🔬 Biohaking Magazine
@bhzine · 180
1 post
Метаверсище и ИИще
@cgevent · 51,375
1 post
CL Vibes
@clvibes · 14
1 post
Новый Зодчий
@concept_me · 58
1 post
Джедаи Данных
@datajoda · 14
1 post
Generative Ai
@deeplearning_ru · 3,717
1 post
Design Training
@Design_Training · 27
1 post
dev warrior
@devwarrior · 129
1 post
Открытия
@disc_over · 545
1 post
Effective Accelerationism
@e_accelerationism · 13
1 post
ЭЯЙ
@e_yai · 787
1 post
эго-иллюзии Захарова
@ego_illusions · 28
1 post
DS с завода
@FactoryDS · 760
1 post
с нуля до 1%
@firsterstrongerbetter · 494
1 post
Глебчик aka Fucckt 🥩
@fuckkt_web30 · 3,167
1 post
GPTшная
@GPThand · 380
1 post
guided by the beauty of my weapon
@guided_by · 89
1 post
Islombe dev
@islombe_dev · 71
1 post
Антон про AI и ваше право на незнание
@it_anton_omsk · 311
1 post
commit -m "better"
@itpgchannel · 3,606
1 post
Зингер42. ИИ для бизнеса
@izinger42 · 1,373
1 post
Олег Утеков
@legolev · 618
1 post
уровни абстракции
@levels_of_abstraction · 475
1 post
Alex LLM Neighbors
@llm_neighbors · 330
1 post
Lowkey
@loowkey · 93
1 post
LVL or Death Team - Арбитраж трафика
@lvlordeath · 2,081
1 post
MemeQueen
@memesqueen · 369
1 post
KR’s Life-n-Travel
@mujaji_lnt · 43
1 post
На злобу д.
@na_zlobu_d · 47
1 post
Нерон
@neir_on · 1,018
1 post
yolo singularity
@neuralpurgatory · 1,700
1 post
NeuroVibes
@neuro_vibes_future · 119
1 post
Ignition of cognition
@neurobros · 222
1 post
Радиорубка Лихачёва
@niketasfm · 12,420
1 post
Блог о AI Design
@noteaidesign · 41
1 post
Блог о Data Science 💻 Наука о данных
@notedatascience · 3,914
1 post
Дед кричит на облако
@oldman_yells_at_cloud · 142
1 post
Open_Mind
@openmind_chanell · 12
1 post
Pandora's box
@pandora_intelligence · 3,984
1 post
Политика закулисья🎭
@pbtc_russ · 71
1 post
Prismatic view
@prismaticview · 62
1 post
Тройное Дно
@regarded_trader · 101
1 post
Roman App$
@sam_sebe_ceo · 108
1 post
Жизнь без офиса | Никита Семчурин
@semchurin_live · 41,029
1 post
ASPI
@serejaparfenov · 78
1 post
Шаришь за ИИ?
@sharishzaAI · 901
1 post
SilentPlay
@silentplay · 13
1 post
тоже моушн
@too_motion · 8,219
1 post
Тостер Скрипт
@TosterScript · 6,301
1 post
DeToxic AI
@toxic_ai_random1st · 177
1 post
Tuzov AI Lab
@tuzov_ai_lab · 4,472
1 post
Vibe Code
@viconews · 80
1 post
Возомнилов
@vozomnilov · 37
1 post
YAKUBSOIDA
@yakubsoida · 1,432
1 post
Закиев Василь. (AI)ron manager
@zvasilchannel · 5,390
1 post

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 78 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.

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.

Machinelearning
@ai_machinelearning_big_data · 286,250
Telegram ranks this channel #3 of 95 here — alongside 94 others — read 10 August 2026
XOR
@xor_journal · 158,763
Telegram ranks this channel #8 of 93 here — alongside 92 others — read 12 August 2026
GigaChat
@official_gigachat · 311,396
Telegram ranks this channel #19 of 92 here — alongside 91 others — read 10 August 2026
ТЕХНО: Яндекс про технологии
@techno_yandex · 233,428
Telegram ranks this channel #26 of 96 here — alongside 95 others — read 11 August 2026
Технологии | Нейросети | Боты
@aiaiai · 177,975
Telegram ranks this channel #53 of 93 here — alongside 92 others — read 12 August 2026
Простая экономика
@prostoecon · 292,992
Telegram ranks this channel #62 of 95 here — alongside 94 others — read 12 August 2026
GitHub Community
@github · 149,921
Telegram ranks this channel #68 of 87 here — alongside 86 others — read 12 August 2026

This channel appears in 7 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 12 August 2026 — this entry's latest reading, not the date you are reading this.

“Сиолошная” (@seeallochnaya), 77,459 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/seeallochnaya.

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.