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 20 August 2026 and assigned it the closest of 31 fixed categories, at 100% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Growth
63 measurements spanning 43 days, net +60. 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 15,232–15,388 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 63
Measured (UTC)
Subscribers
Change
18 Sept 2026, 13:57
15,318
+5
17 Sept 2026, 10:22
15,313
-2
16 Sept 2026, 06:40
15,315
-1
15 Sept 2026, 08:57
15,316
-4
14 Sept 2026, 12:41
15,320
-1
13 Sept 2026, 17:36
15,321
no change
12 Sept 2026, 23:57
15,321
-7
11 Sept 2026, 02:18
15,328
+1
9 Sept 2026, 16:15
15,327
-3
8 Sept 2026, 01:56
15,330
-4
6 Sept 2026, 09:19
15,334
no change
4 Sept 2026, 22:58
15,334
-8
4 Sept 2026, 00:15
15,342
+9
3 Sept 2026, 08:49
15,333
no change
2 Sept 2026, 13:14
15,333
+6
2 Sept 2026, 02:34
15,327
+5
1 Sept 2026, 15:38
15,322
+16
31 Aug 2026, 23:16
15,306
+51
31 Aug 2026, 13:06
15,255
-1
31 Aug 2026, 00:14
15,256
first reading
Engagement
81 posts held, back to 3 August 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 57 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
9.20%
avg views ÷ 15,318 subscribers
Avg views / post
1,410
28 posts measured
Reaction rate
1.25%
reactions ÷ views · ER floor
Posts in window
28
of 81 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 3 September 2026
Posts held
81 (3 August 2026 – 3 September 2026)
Views total
39,467
Reactions total
495
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
3 Sept 2026, 10:50 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
58m 09s
Average length
1m 05s
Measured directly from 54 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
1,360 reactions across 78 posts, in 5 distinct kinds. The most used accounts for 37.7% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
513
37.7%
🔥
301
22.1%
custom 5334917580035468337
250
18.4%
custom 5244673458083734407
158
11.6%
❤
138
10.1%
Custom emoji. 2 of the rows above are 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 counts beside them are Telegram’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 81 of the 81 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 1,386 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 81 most recent posts we hold, published 3 August 2026 to 3 September 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Telegram Stars
Stars received
7
across the posts below
Posts paid on
6
of 81 we hold a reading for · 7%
Most on one post
2
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @neurohub. 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 81 most recent posts we hold for this entry, published 3 August 2026 to 3 September 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
🧐 ИИ добрался аниме.
LINGER — короткометражка про девушку, меха и пилота. Две с половиной минуты старой фантастики с полями, огромными роботами и вайбом аниме из девяностых.
Визуал собрали в Seedream 5 Pro, анимацию сделали через Seedance 2.5, музыку — в Suno.
Когда уже хочется досмотреть, а не только разглядывать артефакты.
🎥 NEUROHUB
✴️ Google выпустила Gemini 3.8 Flash — третью Flash-модель за шесть недель.
Главный апгрейд достался кодингу и ИИ-агентам. Нейронка лучше справляется с длинными задачами, сама планирует работу, проверяет результат и может управлять компьютером.
В тестах Google модель почти сравнялась с Claude Opus 5 в разработке, а в задачах по финансам, юриспруденции и работе с видео местами обошла его. При этом скорость и цена ос…
😧 Больше 30 тысяч промптов собрали в одном месте.
В бесплатной библиотеке YouMind лежат готовые запросы для генерации картинок, видео и сайтов. У каждого есть пример результата.
Есть сортировка по модели, категории и популярности. Поддерживаются GPT Image 2, Nano Banana Pro, Seedance, Grok Imagine, Gemini и другие нейронки.
Ещё сервис умеет разбирать загруженные изображения и превращать их в подробные запросы.
➡…
✴️ Claude предложил разгадку шифра, который не могли прочитать 373 года.
Vals AI поручили новой Fable 5.1 расшифровать старую нерешённую криптограмму, и модель за 44 минуты нашла способ её взломать.
Шифр Томаса Уркхарта из 1653 года состоял из двух строк по 32 числа. Рядом в книге были 32 пронумерованных пожелания автора.
Каждое число указывало на нужное слово в соответствующем пожелании, а первые буквы найденных…
🚘 В Пакистане показали беспилотное авто и сразу въехали в полицейскую машину.
Во время демонстрации автомобиль потерял управление, а пассажир не успел остановить его ручником.
За секунду до столкновения журналист заявил, что «в Пакистане нет недостатка в талантах».
🎥 NEUROHUB
🙄 На рабочем столе теперь можно завести собственную ИИ-вайфу.
Animates превращает обычный чат с нейронкой в разговор с анимированным персонажем. Он отвечает голосом, замечает ваше настроение и запоминает детали из прошлых бесед.
Даже после закрытия приложения он обдумывает прошлые разговоры и возвращается с новыми мыслями. Заодно умеет искать информацию, писать тексты и помогать с планами.
Доступно на iOS, Android…
✴️ Ловите огромный каталог дополнений для Claude.
В Build with Claude собрано больше 27 тысяч плагинов, 4100 навыков и 6200 MCP-серверов.
Ищем нужную задачу и получаем агентов-специалистов, команды для Git и тестов, хуки и подключения к сервисам. У каждого дополнения есть описание, исходники и команда установки.
Плагинов много, много не бывает.
🎥 NEUROHUB
Откуда нейросеть берет инфу на русском?
Когда я готовлю посты, я часто использую нейросети для фактчекинга и ресерча.
И здесь есть интересная деталь: когда просишь модель найти что-то актуальное именно в русскоязычном сегменте, она практически весь веб-поиск выстраивает вокруг Telegram. Со временем я заметил, что нейронка раз за разом ссылается на одни и те же каналы.
Ради интереса закинул ей промпт:
Собери список…
💬 Нашли бесплатный CapCut для субтитров.
AISubs — локальное приложение для Windows, которое само расшифровывает речь и вшивает субтитры сразу в пачку роликов. Аккаунт, подписка и API-ключ не нужны.
Что умеет:
🟡 Расставлять таймкоды для каждого слова;
🟡 Подсвечивать произносимое слово в стиле караоке;
🟡 Редактирует текст и тайминги перед рендером;
🟡 Сохранять свои стили субтитров.
Видеокарта NVIDIA желательна для с…
🏥 Вышел навык, который прокачает скиллы ваших агентов.
Skill Doctor изучает чаты в Claude Code, Codex и Warp, а затем оценивает, насколько хорошо агент справляется с задачами и пишет код.
В отчёте будут оценка работы, примеры неудачных решений и конкретные рекомендации. А проверку можно поставить на автомат, чтобы агент сам становился полезнее после каждого проекта.
Можно включить автоматическую проверку, чтобы ск…
👍12❤3
Showing the 12 most recent of 81 posts we hold for @neurohub. 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.
Posts edited after publishing
@neurohub edited 2 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
26 August 2026
Most recent edit
28 August 2026
Mentions
Named by 17 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
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.
НейроProfit | Соня Pro Ai @NeuralProfit · 23,400 Telegram ranks this channel #6 of 96 here — alongside 95 others — read 18 September 2026
NeuroADEPT @neuroadepts · 41,375 Telegram ranks this channel #6 of 85 here — alongside 84 others — read 29 August 2026
MIDJOURNEY (Нейросеть) @mdjrny · 23,604 Telegram ranks this channel #10 of 68 here — alongside 67 others — read 18 September 2026
Tips AI | IT & AI @tips_ai · 25,376 Telegram ranks this channel #14 of 95 here — alongside 94 others — read 14 September 2026
ИИ Представляет @iirepresent · 120,362 Telegram ranks this channel #17 of 86 here — alongside 85 others — read 23 August 2026
Lama AI @lama_channel_gpt · 24,736 Telegram ranks this channel #21 of 90 here — alongside 89 others — read 15 September 2026
Bard AI | Нейросети & IT @NeuralToday · 30,447 Telegram ranks this channel #25 of 85 here — alongside 84 others — read 7 September 2026
Ринат Шакиров | Промпты для Midjourney | ChatGPT | @dailyprompts · 42,650 Telegram ranks this channel #27 of 91 here — alongside 90 others — read 29 August 2026
Технологии | Нейросети | Боты @aiaiai · 176,423 Telegram ranks this channel #32 of 93 here — alongside 92 others — read 12 August 2026
КиберХаб - IT и Нейросети @kyberhub · 60,729 Telegram ranks this channel #35 of 88 here — alongside 87 others — read 22 August 2026
Нейроскептик @neuroskep · 29,484 Telegram ranks this channel #36 of 90 here — alongside 89 others — read 8 September 2026
Neurogen @neurogen_news · 22,930 Telegram ranks this channel #38 of 88 here — alongside 87 others — read 19 September 2026
PROAI @pro_ai_news · 90,512 Telegram ranks this channel #39 of 92 here — alongside 91 others — read 16 August 2026
PRO | Нейросети @pro_neiroset · 31,879 Telegram ranks this channel #40 of 86 here — alongside 85 others — read 5 September 2026
Нейролента @neirosety · 30,294 Telegram ranks this channel #42 of 87 here — alongside 86 others — read 7 September 2026
GeekNeural @geekneural · 63,099 Telegram ranks this channel #44 of 92 here — alongside 91 others — read 21 August 2026
CyberYozh AI Security @CyberYozh_AI_security · 26,576 Telegram ranks this channel #46 of 91 here — alongside 90 others — read 12 September 2026
Мир нейросетей - новости, обучение и заработок @pro_ai_novosti · 50,517 Telegram ranks this channel #48 of 90 here — alongside 89 others — read 25 August 2026
Serge_AI 1.0 @serge_ai · 57,484 Telegram ranks this channel #50 of 99 here — alongside 98 others — read 23 August 2026
Промпты для нейросетей @prompty · 30,029 Telegram ranks this channel #56 of 89 here — alongside 88 others — read 7 September 2026
SYNTX FAMILY @syntxfamily · 323,728 Telegram ranks this channel #60 of 93 here — alongside 92 others — read 22 August 2026
AI Университет @neural_university_webinar · 37,547 Telegram ranks this channel #61 of 96 here — alongside 95 others — read 31 August 2026
Нейросетевые покои: нейросети, ChatGPT, Midjourney @neural_houses · 44,640 Telegram ranks this channel #64 of 92 here — alongside 91 others — read 28 August 2026
SMM с Дамиром Халиловым @damirkhalilov · 23,321 Telegram ranks this channel #86 of 91 here — alongside 90 others — read 18 September 2026
This channel appears in 24 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 18 September 2026 — this
entry's latest reading, not the date you are reading this.
“NEUROHUB” (@neurohub), 15,318 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/neurohub.
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.