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Channel

Все о блокчейн/мозге/space/WEB 3.0 в России и мире

@blockchainRF

On this record: Topic · Observations · Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Citations · Telegram's recommendations · Cite this entry

20,457subscribers

+364 since we began measuring on 5 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001036051144
TypeChannel
Username@blockchainRF
DescriptionКанал создан 5.08.2016г. о: блокчейн, мозг(BCI), биотех, space tech, цифровая экономика, WEB 3.0 Больше на Patreon https://www.patreon.com/Blockchainrf?utm_campaign=creatorshare_creator Основатель @AniAslanyan Eng channel https://t.me/alwebbci
Created4 August 2016 — measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live9 November 2026
Measurements held61
Confirmed unchanged1 time, most recently 9 November 2026
On Telegramt.me/blockchainRF

Topic

Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 10 September 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 in near-verbatim form 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
@blockchainRF/13327 · this entry24 Aug 2026, 14:21 UTC@F_S_C_P/12279824 Aug 2026, 20:34 UTC0.996.2 hours
@blockchainRF/13581 · this entry5 Nov 2026, 16:10 UTC@F_S_C_P/1245446 Nov 2026, 03:46 UTC0.9812 hours
@blockchainRF/13296 · this entry12 Aug 2026, 17:18 UTC@F_S_C_P/12254913 Aug 2026, 10:42 UTC0.9817 hours
@blockchainRF/13584 · this entry6 Nov 2026, 10:51 UTC@F_S_C_P/1245726 Nov 2026, 22:25 UTC0.9712 hours
@blockchainRF/13588 · this entry9 Nov 2026, 12:02 UTC@F_S_C_P/1246449 Nov 2026, 22:55 UTC0.9611 hours
@blockchainRF/13271 · this entry5 Aug 2026, 08:16 UTC@F_S_C_P/1223765 Aug 2026, 20:19 UTC0.9612 hours
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
ChannelMatching postsText overlapTypical gapPublished first
@F_S_C_P11 (8/8 hand-verifiable sample passed)0.9611 hoursthis entry (11–0)

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 148 comparable posts for this entry, running 30 July 2026 to 10 November 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).

Recorded under the key clone_source, last confirmed 11 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.

Growth

20,08220,58220,33220,4575 August 20269 November 2026
61 measurements spanning 96 days, net +364. 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 20,007–20,657 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 61
Measured (UTC)SubscribersChange
9 Nov 2026, 18:0820,457-5
8 Nov 2026, 13:1120,462+1
7 Nov 2026, 09:1620,461+1
6 Nov 2026, 10:4620,460+1
5 Nov 2026, 07:0520,459+2
4 Nov 2026, 03:0720,457+3
3 Nov 2026, 01:2620,454-2
2 Nov 2026, 03:0620,456-10
1 Nov 2026, 02:1120,466-12
31 Oct 2026, 03:5820,478-22
30 Oct 2026, 05:4920,500-31
29 Oct 2026, 06:2020,531-18
28 Oct 2026, 00:4820,549-16
26 Oct 2026, 22:2620,565-2
25 Oct 2026, 20:0520,567-2
23 Oct 2026, 16:5620,569-2
22 Oct 2026, 19:3820,571-11
21 Oct 2026, 15:2120,582+1
20 Oct 2026, 09:5620,581+11
19 Oct 2026, 13:1620,570first reading

Engagement

152 posts held, back to 30 July 2026 — the reader has reached the start of this channel’s public history, so this is the full archive Telegram still exposes. Read across 74 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
10.4%
avg views ÷ 20,457 subscribers
Avg views / post
2,130
49 posts measured
Reaction rate
0.795%
reactions ÷ views · ER floor
Posts in window
49
of 152 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 November 2026
Posts held152 (30 July 2026 – 10 November 2026)
Views total104,170
Reactions total828
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken11 Nov 2026, 03:28 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

What this channel posts

Photos
≈2,180
Videos
≈412
Links
≈9,010

Lifetime counters from Telegram’s own channel header, read 11 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.

Video runtime
1m 48s
Average length
27s

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

2,492 reactions across 147 posts, in 33 distinct kinds. The most used accounts for 30.5% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤76130.5%
🔥62124.9%
👍50420.2%
❤‍🔥1395.58%
💯803.21%
😁391.57%
👀371.48%
😱311.24%
🤔311.24%
😍291.16%
🏆281.12%
👏251.00%
👎220.883%
🙏190.762%
🥰190.762%
🤣150.602%
🤯130.522%
🎉110.441%
🌚100.401%
🦄90.361%
13 further kinds491.97%

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 152 of the 152 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 2,588 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 152 most recent posts we hold, published 30 July 2026 to 10 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
150
across the posts below
Posts paid on
16
of 152 we hold a reading for · 11%
Most on one post
70
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @blockchainRF. 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 152 most recent posts we hold for this entry, published 30 July 2026 to 10 November 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.

Recent posts

Telegram’s own ‘edited’ marker: 17 of 49 posts held from the last 30 days (34.7%) 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).

10 Nov 2026, 19:39 UTC960 views12 reactionsread 11 November 2026

Гонка за бессмертием стала серьёзным бизнесом и перспективным направлением для стартапов В конце октября мы проводили для наших подписчиков уровня Star на Patreon встречу с сооснователем биотех компании Bioptic Романом Дорониным, чьим партнером является Андрей Дороничев, экс-продуктовый директор Google. Отчет тут. В рамках этой встречи мы обсудили вопросы о бизнесе в биотехе, и почему туда все рвутся, есть ли там р…

❤10🔥1🥰1

10 Nov 2026, 16:07 UTC≈1,310 views7 reactionsread 11 November 2026

Вау!Google говорят, что их модель Argon помогла в создании новой модели для роботов Gemini Robotics 2.5 Сейчас компания выпустила Gemini Robotics 2.5 - свою новую ИИ-модель для управления роботами. Команда отмечает, что это 1-я модель, которую сильно ускорила другая модель - Gemini 4 Argon, которая используется как симулятор: генерирует тысячи вариаций тренировочных прогонов на основе реальной съёмки и строит цифро…

❤5💯1🔥1

10 Nov 2026, 14:10 UTC≈1,400 views13 reactionsread 11 November 2026

7 крупнейших IT-компаний покупают акции Anthropic на $26млрд Согласно обновлённой информации, поданной в SEC, компания договорилась с 7 компаниями, что они покупают акции по цене IPO в частном размещении на $26 млрд. Вот эти 7 компаний: - Google покупают акции на $10млрд - Nvidia на $10млрд - AMD $2.5млрд - Broadcom $1млрд - Micron $1млрд - Microsoft $1млрд - TSMC $500млн Все они представляют собой почти всю цеп…

🔥8💯3❤2

10 Nov 2026, 13:06 UTC≈1,380 views10 reactionsread 11 November 2026

Команда Robbyant (Alibaba) выложила модель, которая учит роботов чувствовать объекты Компания Robbyant выпустила в open-source модель LingBot-Touch, которая обучена почти на 5000 часах реальных касаний. У нее 2 версии: Tiny и Small. Модель использует подход JEPA и может сделать из разных сигналов от сенсоров единое тактильное представление, которое можно подключить к разным политикам робота. LingBot-Touch работае…

👍5❤3💯2

10 Nov 2026, 11:37 UTC≈1,440 views7 reactionsread 11 November 2026

А вот Skyfall представили ИИ в виде CEO компании, который управляет агентами и бизнесом Steve - система ИИ-агентов, которую компания называет CEO, описываемый как автономный бизнес-харнесс, способный управлять SaaS-продуктами и приложениями Shopify. Причём Steve - харнесс вокруг Enterprise World Model. Steve создана компанией Skyfall - команда создателей Maluuba, которую купили Microsoft в 2017. Интересно, что St…

👍3💯2🔥2

10 Nov 2026, 08:41 UTC≈1,800 views19 reactionsread 11 November 2026

Впервые в истории робот построил конструкцию в космосе Робот ASTRA, разработанный в Caltech и профинансированный DARPA за 6 месяцев на орбите собрал часть фермы из композитных трубок и алюминиевых узлов. Полную 1,4 метровую антенну из 11 сегментов достроить не успели, но пруф оф концепт уже есть. Этот проект был нужен для того, чтобы научиться строить в космосе вещи, которые физически не влезают в ракету: гигантск…

❤11👍4🔥4

9 Nov 2026, 19:06 UTC≈2,280 views24 reactions3 Starsread 11 November 2026

Это бомба! Anthropic выпустили прямо сейчас модель Fable 5.2 и Mythos 5.2 Как говорит сама компания, эти модели созданы для решения самых сложных задач в разных областях и показывают улучшенную работу в программировании, рассуждениях и обработке изображений. Вот, на что способны эти модели: • Fable 5.2 формализовала доказательство теоремы Ферма за 30 часов • Решила 2 открытых вопроса в теоретической физике чёрных…

❤‍🔥11❤5🔥5👍3

9 Nov 2026, 17:23 UTC≈1,980 views14 reactionsread 11 November 2026

Google научили ИИ-агентов находить новые квантовые алгоритмы и сразу доказывать их корректность и стоимость в Lean. Над этим работала как команда DeepMind, так и Quantum. Эта работа отличается от прошлых подходов, где ИИ-агенты проверяли квантовые схемы численным моделированием на классическом компьютере. Здесь же агенты работают с алгоритмами на тысячах кубитов, которые невозможно просимулировать классически, но …

❤5❤‍🔥4👍3💯2

9 Nov 2026, 15:31 UTC≈1,780 views15 reactionsread 11 November 2026

Google выпустил под ИИ-агентов сразу 2 новые TPU-системы 8tx и 8i Max Впервые компания выпускает 4 конфигурации TPU за 1 год,(в апреле был ещё запуск) что говорит о двух вещах: 1. цикл разработки и адаптации железа стал намного короче. 2. универсального чипа больше нет, а есть специализация под каждую стадию жизни агента. Параллельно Google дожимает уровень софта: открытый TorchTPU, автонастройка через Claude Cod…

❤6🔥4👍3💯2

9 Nov 2026, 14:01 UTC≈1,730 views16 reactionsread 11 November 2026

Внезапно хедж-фонд Jane Street выложил инструкцию, как сделать из ИИ персонального репетитора Компания, которая зарабатывает миллиарды $ на количественном трейдинге, выложила на GitHub простую инструкцию для ИИ-агентов. Хэдж-фонд делает больше для образования, чем кто-либо вообще.

👍11🔥3❤2

9 Nov 2026, 12:02 UTC≈2,470 views25 reactionsread 11 November 2026

Anthropic поделились, как они создают память для агентов Claude В частности, они пишут, что Anthropic называет памятью агента - знания, которые Claude получает из опыта (взаимодействие с пользователем и задачи) и сохраняет между сессиями как контекст, который можно прочитать позже. А основная идея памяти ИИ-агента - не только все сохранять, а это предсказание того, что пригодится в будущем, плюс умение потом это п…

👍11❤7🔥7

9 Nov 2026, 08:51 UTC≈1,950 views20 reactionsread 11 November 2026

У Nvidia китайская проблема: выяснилось, что Alibaba закупала чипы Nvidia через сингапурскую компанию, чей топ-менеджер была в романтических отношениях с Дженсеном Хуангом, СЕО Nvidia А сейчас против Хуанга началось расследование внутри компании и на уровне национальной безопасности США. Последние несколько дней идет обсуждение этого скандала, которое вскрыло, что по данным аналитиков Culper Research, Alibaba фина…

🌚9👍3🔥3🍓2💯2🤣1

Showing the 12 most recent of 152 posts we hold for @blockchainRF. 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.

Republished by 54 registered channels. The 48 listed are the ones that have forwarded the most posts; the rest are counted here but not each listed.

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артём
@motel_next_to_cemetery · 30
1 post
НейроХаб. Public
@neurohub_public · 48
1 post
Экономика цифровой эры
@newdigitalera · 2,834
1 post
Nexi's channel
@nexiware · 111
1 post
NIKTA NEWS
@niktanewsforweb · 3
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 41 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.

Names

Channels on the register whose handles appear in this channel's posts.

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.

All about AI, Web 3.0, BCI
@alwebbci · 3,947
#1
Нецифровая экономика
@antidigital · 24,491
#2
База знаний AI
@ict_moscow_ai · 9,061
#3
Denis Sexy IT 🤖
@denissexy · 140,753
#4
Минцифры России
@mintsifry · 232,434
#5
Innovation & Research
@abulaphia · 5,195
#6
Сиолошная
@seeallochnaya · 81,254
#7
vc.ru
@vcnews · 112,144
#8
Клуб CDO
@cdo_club · 4,132
#9
e/acc
@cryptoEssay · 63,613
#10
addmeto
@addmeto · 72,001
#11
Малоизвестное интересное
@theworldisnoteasy · 74,298
#12
42 секунды
@ftsec · 19,385
#13
The Bell
@thebell_io · 105,097
#14
Код.ру
@d_code · 405,444
#15
ICT.Moscow
@ICT_Moscow · 5,076
#16
РБК Крипто
@RBCCrypto · 131,891
#17
TechSparks
@techsparks · 46,736
#18
Институт AIRI
@airi_research_institute · 13,977
#19
GPT/ChatGPT/AI Central Александра Горного
@aioftheday · 44,602
#20
Дизраптор
@disruptors_official · 72,494
#21
Russian Business
@rb_ru · 366,227
#22
HCAI // Регулирование ИИ
@AI_regulation · 1,532
#23
MMI
@russianmacro · 101,987
#24
GigaChat
@official_gigachat · 303,004
#25
News & Trends by Sber
@sbmarketing · 6,684
#26
Complete AI
@complete_ai · 7,887
#27
Венчур в картинках
@ventureinpics · 11,272
#28
Data Secrets
@data_secrets · 96,035
#29
Мониторинг аналитики об IT
@ict_moscow_analytics · 2,221
#30
TAdviser
@tadviser · 13,470
#31
Раньше всех. Ну почти.
@bbbreaking · 1,975,436
#32
Банкста
@banksta · 439,838
#33
Лебедев про мозг
@augmented_brain · 6,377
#34
ЕЖ
@ejdailyru · 664,380
#35
MarketTwits
@markettwits · 341,015
#36
Цифровая экономика
@DataEconomyRU · 7,455
#37
DigitalRussia
@drussia · 13,891
#38
РБК. Новости. Главное
@rbc_news · 913,555
#39
Нейроинтерфейсы
@bci_ru · 6,505
#40
эйай ньюз
@ai_newz · 98,339
#41
DeCenter — блокчейн, биткоин, инвестиции
@DeCenter · 1,640,924
#42
Банки, деньги, два офшора
@bankrollo · 462,080
#43
Skolkovo Leaks
@skolkovoleaks · 15,754
#44
Грустный Киберпанк
@korolevsnotes · 6,409
#45
Ассоциация ФинТех
@fintechassociation · 16,121
#46
The Edinorog 🦄
@Theedinorogblog · 44,082
#47
Русский венчур
@rusven · 24,986
#48
НЕЗЫГАРЬ
@russicaru · 417,710
#49
ForkLog
@forklog · 101,391
#50
Коммерсантъ
@kommersant · 295,286
#51
Эксплойт
@exploitex · 2,022,997
#52
Бэкдор
@whackdoor · 1,538,229
#53
Forbes Russia
@forbesrussia · 235,497
#54
Метаверсище и ИИще
@cgevent · 53,591
#55
Стартап дня. Александр Горный.
@startupoftheday · 62,560
#56
Сергей Марков: машинное обучение, искусство и шитпостинг
@oulenspiegel_channel · 12,397
#57
Лучшие вакансии
@vacanciesbest · 162,821
#58
headlines
@headlines_for_traders · 114,637
#59
bitkogan
@bitkogan · 257,290
#60
ВЕДОМОСТИ
@vedomosti · 86,957
#61
Финтехно
@fintexno · 29,738
#62
Proeconomics
@proeconomics · 68,730
#63
FSCP
@F_S_C_P · 13,560
#64
Токсичная цифра
@toxic_digital · 5,529
#65
aavst2022
@aavst2022 · 175,172
#66
TrendWatching
@trendwatching24 · 1,375,035
#67
kyrillic
@kyrillic · 61,233
#68
Телекоммуналка
@telecommunal · 43,858
#69
Gram RUS
@toncoin_rus · 508,907
#70
Пул N3
@dimsmirnov175 · 331,028
#71
PlugoNews
@plugonews · 1,191
#72
Web 3.0 :: Web3
@web3news · 7,334
#73
Грокс
@groks · 42,476
#74
Толкователь
@tolk_tolk · 126,403
#75
Сигналы РЦБ
@cbrstocks · 117,222
#76
Майский указ
@maydecree · 19,471
#77
Ivan Begtin
@begtin · 9,104
#78
DEFI Scam Check
@Defiscamcheck · 48,110
#79
Kedr to Earth | Земля, я Кедр
@kedr2earth · 10,140
#80
Труба под Неглинной
@trubapodneglinnoy · 137,211
#81
лидер мнений среди удобрений
@lider · 175,531
#82
ЦФА в РФ
@CFA_RF · 5,805
#83
Банк России
@centralbank_russia · 243,972
#84
CNews.ru
@CNewsDaily · 15,763
#85
Дерипаска
@olegderipaska · 115,845
#86
Образ будущего
@obrazbuduschego2 · 163,839
#87
Evening Prophet
@eveningprophet · 19,092
#88
Frank Media
@frank_media · 32,153
#89
Baza
@bazabazon · 1,557,057
#90
Милитарист
@infantmilitario · 275,861
#91
Беспощадный пиарщик
@prbezposhady · 151,213
#92
Политджойстик / Politjoystic ™
@politjoystic · 250,548
#93
Китайская угроза
@daokedao · 98,737
#94
Правительство России
@government_rus · 167,239
#95
Московские новости
@mnews_ru · 194,474
#96
BRIEFLY RU
@brieflyru · 100,290
#97

Read from Telegram’s recommendation API, most recently 27 September 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.

Нецифровая экономика
@antidigital · 24,491
Telegram ranks this channel #15 of 96 here — alongside 95 others — read 16 September 2026
Tech Crunch
@techcrunchru · 16,299
Telegram ranks this channel #17 of 95 here — alongside 94 others — read 5 October 2026
Витрина стартапов
@showstartup · 26,848
Telegram ranks this channel #24 of 90 here — alongside 89 others — read 11 September 2026
Малоизвестное интересное
@theworldisnoteasy · 74,298
Telegram ranks this channel #26 of 94 here — alongside 93 others — read 19 August 2026
Кот Эльвиры
@KotElviry · 47,884
Telegram ranks this channel #33 of 97 here — alongside 96 others — read 26 August 2026
Russian Business
@rb_ru · 366,227
Telegram ranks this channel #37 of 98 here — alongside 97 others — read 14 August 2026
КиберПанк | Технологии Будущего | Technology
@technology_future_cyberpunk · 37,160
Telegram ranks this channel #53 of 84 here — alongside 83 others — read 1 September 2026
Evening Prophet
@eveningprophet · 19,092
Telegram ranks this channel #57 of 94 here — alongside 93 others — read 5 October 2026
Sber AI
@SberAIScience · 26,483
Telegram ranks this channel #66 of 95 here — alongside 94 others — read 10 September 2026
Waves 🌊
@wavesnews · 943,891
Telegram ranks this channel #82 of 88 here — alongside 87 others — read 15 August 2026
Сколково
@skolkovolive · 40,883
Telegram ranks this channel #83 of 98 here — alongside 97 others — read 29 August 2026
Финтехно
@fintexno · 29,738
Telegram ranks this channel #85 of 96 here — alongside 95 others — read 8 September 2026
РБК Деньги
@rbc_pro · 27,506
Telegram ranks this channel #89 of 97 here — alongside 96 others — read 10 September 2026

This channel appears in 13 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 9 November 2026 — this entry's latest reading, not the date you are reading this.

“Все о блокчейн/мозге/space/WEB 3.0 в России и мире” (@blockchainRF), 20,457 subscribers as measured 9 November 2026. Telegram Register, tgregister.com/channel/blockchainRF.

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.