4 measurements spanning 4 days, net -6. 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 4,997–5,005 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
11 Aug 2026, 10:26
4,998
-4
8 Aug 2026, 05:12
5,002
-2
7 Aug 2026, 12:01
5,004
no change
7 Aug 2026, 11:55
5,004
first reading
Engagement
14 posts held, back to 22 April 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 8 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
20.8%
avg views ÷ 4,998 subscribers
Avg views / post
1,040
1 post measured
Reaction rate
2.31%
reactions ÷ views · ER floor
Posts in window
1
of 14 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 26 July 2026
Posts held
14 (22 April 2026 – 26 July 2026)
Views total
1,040
Reactions total
24
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
12 Aug 2026, 04:59 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
176
Videos
69
Links
167
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. Below Telegram’s rounding threshold, so these counts are exact.
Video runtime
3m 46s
Average length
45s
Measured directly from 5 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
193 reactions across 13 posts, in 11 distinct kinds. The most used accounts for 29.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
56
29.0%
👍
51
26.4%
❤
50
25.9%
🗿
13
6.74%
👾
10
5.18%
😁
4
2.07%
🤯
4
2.07%
🤩
2
1.04%
⚡
1
0.518%
🌚
1
0.518%
🫡
1
0.518%
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 13 of the 14 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 193reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 14 most recent posts we hold, published 22 April 2026 to 26 July 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
1
of 14 we hold a reading for · 7%
Most on one post
7
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @InNeuralNetwork. 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 14 most recent posts we hold for this entry, published 22 April 2026 to 26 July 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.
Два месяца против полутора часов
7 лет назад приятель показал мобильную игру, которую собрал сам. Блочный город, объекты, механики. Своего рода упрощённая GTA. До этого он два месяца с нуля разбирался с Unity
Тогда это выглядело как магия, которую хотелось повторить. Но новый навык скорее оплачивался вычетом из того, чем уже занят. Прикинул размер вычета и понял, что мой пыл умерен для отказа
В пятницу после выход…
Как отупеть от нейросетей
Недавно помогал по работе редактировать чужой документ. Открываю, а там знакомый почерк
«Это начинается не с эмоций, а с понимания человека». Будто у автора рука (или что помягче) отвалится, если убрать часть с «не». Жирные заголовки в каждом перечислении. И слово «важно» в конце каждого абзаца, чтобы не расслаблять внимание
Пока правил, поймал себя на мысли: а зачем в этой цепочке вообще…
США запретили Anthropic пускать иностранцев к Fable и Mythos. Под раздачу попали даже сотрудники самой компании
Первый в истории случай, когда доступ к ИИ-модели режут по паспорту. И, судя по всему, не последний.
12 июня в 17:21 по нью-йоркскому времени Anthropic получила от правительства США директиву экспортного контроля: со ссылкой на нацбезопасность приостановить доступ к Fable 5 и Mythos 5 для любых иностранце…
Claude Fable 5 жесть круто
Попросил сделать русскую GTA, и тот сделал прикольно
Заметил, что лучше работает взаимодействие с объектами, с чем была проблема у 4 серии Claude (особенно, когда делаете что-то прототипное). Теперь же пространство учитывается в сборке. Есть косяки минорные по габаритам, но не бросаются в глаза
Так что для сложных задач новая базовая модель установлена. Сжирает в 2 раза больше токенов, ч…
Обзавелся Яндекс Дропс, но с теми пока непросто
Позиционируют их как наушники с ИИ: вызываешь ассистента по чиху, просишь что надо. Работает сносно, лучше текущей Siri — команды срабатывают, хотя иногда активируется ошибочно. Зато когда срабатывает, подручный в ухе радует
Главная фича — память. Надиктовываешь дела, долгосрочные и на сейчас, а ассистент напоминает или достает нужное. Например, я завел несколько запи…
Посмотрел WWDC 26, а такое представление, что 2024 во второй раз, но уже нормально. Прикольные штуки, которые были на презе:
• Siri AI работает на базе эпловском и гугловском контуре, отчего можно быстро и с контекстом утсройство чатиться с Siri как с нормальным человеком, а не полумной. Но хоть и Gemini поддерживает русский, в сентябре на выходе его не будет :с
• Любимая фичи фотошопа добрались и до фото — можно ст…
Как выглядит типичный день вайбкодера, лучше всего показали в сериале «Fired on Mars» (Уволен на Марсе). Правда, там Джефф дизайнер, но это уже и не важно. А вообще сериал крутой - рекомендую.
Opus 4.8 настолько хорош, что в контексте свыше 200к токенов начал делать также хорошо, как в самом начале. А то, что в начале не выходило, теперь работает без придумок. Но варит ответ очень долго
Скачатьгенерить презентацию быстро, классно, давай-давай 👉
Одна презентация под две задачи почти никогда не работает. Выступление перед своими и отправка важному дядьке для чтения с экрана все же разные жанры, даже если мысль одна
Да, никуда не делись нейросети для подрезки формулировок и подбора визуала. Но их расплодилась куча, при том не все для всего подходят. А чего уж говорить, если просить целиком сделать пр…
0$ → 20$ → 200$
И ведь эти три типа месячной подписки на чатбота делают одно и то же. Что-то спрашиваешь, затем с n-ной попытки получаешь. Разница в доступах, лимитах, скорости и немного в качестве
Полтора года я смотрел на планы дороже 20$ как на что-то для сверхбогатых. Ежедневно фигачу десятки запросов по тексту, дизайну, коду, но 200$ в месяц за чатбота это десять моих текущих подписок на того же чатбота. Даже …
👾8👍4🗿3❤1
Showing the 12 most recent of 14 posts we hold for @InNeuralNetwork. 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.
Citation-graph rank
Citation-graph rank — 929,060 of 1,176,251entries 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.
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 2 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.
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 11 August 2026 — this
entry's latest reading, not the date you are reading this.
“InNeuralNetwork” (@InNeuralNetwork), 4,998 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/InNeuralNetwork.
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.