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Channel

Нейроскуф | Про Нейросети&AI

@neyroskuf

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

8,749subscribers

+1,184 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1002674365272
TypeChannel
Username@neyroskuf
CreatedBetween 1 March 2025 and 31 July 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live8 November 2026
Measurements held25
Confirmed unchanged1 time, most recently 8 November 2026
On Telegramt.me/neyroskuf

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 12 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.

Growth

7,5658,7618,1637 August 2026 — 7,565 subscribers7 August 2026 — 7,565 subscribers10 August 2026 — 7,568 subscribers13 August 2026 — 7,567 subscribers19 August 2026 — 7,573 subscribers23 August 2026 — 7,577 subscribers26 August 2026 — 7,702 subscribers29 August 2026 — 7,705 subscribers1 September 2026 — 7,785 subscribers5 September 2026 — 7,793 subscribers10 September 2026 — 7,947 subscribers14 September 2026 — 7,942 subscribers18 September 2026 — 8,024 subscribers27 September 2026 — 8,161 subscribers5 October 2026 — 8,351 subscribers11 October 2026 — 8,309 subscribers15 October 2026 — 8,428 subscribers18 October 2026 — 8,448 subscribers21 October 2026 — 8,586 subscribers24 October 2026 — 8,599 subscribers27 October 2026 — 8,647 subscribers29 October 2026 — 8,702 subscribers2 November 2026 — 8,685 subscribers5 November 2026 — 8,761 subscribers8 November 2026 — 8,749 subscribers8,7497 August 20268 November 2026
25 measurements spanning 94 days, net +1,184. 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 7,386–8,940 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 25
Measured (UTC)SubscribersChange
8 Nov 2026, 13:178,749-12
5 Nov 2026, 00:398,761+76
2 Nov 2026, 07:078,685-17
29 Oct 2026, 22:558,702+55
27 Oct 2026, 07:568,647+48
24 Oct 2026, 18:408,599+13
21 Oct 2026, 12:368,586+138
18 Oct 2026, 13:488,448+20
15 Oct 2026, 04:218,428+119
11 Oct 2026, 15:408,309-42
5 Oct 2026, 10:208,351+190
27 Sept 2026, 19:008,161+137
18 Sept 2026, 19:008,024+82
14 Sept 2026, 01:017,942-5
10 Sept 2026, 17:377,947+154
5 Sept 2026, 06:577,793+8
1 Sept 2026, 12:447,785+80
29 Aug 2026, 13:457,705+3
26 Aug 2026, 14:137,702+125
23 Aug 2026, 07:037,577first reading

Engagement

64 posts held, back to 21 July 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 28 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
12.8%
avg views ÷ 8,749 subscribers
Avg views / post
1,120
31 posts measured
Reaction rate
0.593%
reactions ÷ views · ER floor
Posts in window
31
of 64 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 8 November 2026
Posts held64 (21 July 2026 – 8 November 2026)
Views total34,587
Reactions total205
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken8 Nov 2026, 11:57 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
3m 14s
Average length
32s

Measured directly from 6 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

678 reactions across 64 posts, in 22 distinct kinds. The most used accounts for 31.6% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤21431.6%
🔥15723.2%
👍12117.8%
😁8312.2%
🤣192.80%
🥴131.92%
👏101.47%
💯101.47%
🤯81.18%
✍60.885%
🥱60.885%
👀50.737%
😢50.737%
🏆40.59%
🥰40.59%
🐳30.442%
💊30.442%
🤔20.295%
🤷‍♂20.295%
💅10.147%
2 further kinds20.295%

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 64 of the 64 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 678 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 64 most recent posts we hold, published 21 July 2026 to 8 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.

Recent posts

Telegram’s own ‘edited’ marker: 0 of 31 posts held from the last 30 days (0%) 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).

8 Nov 2026, 06:32 UTC338 views3 reactionsread 8 November 2026
Photo

Проектирование лендингов без шаблонной верстки через ai-design-skills Если просто попросить нейросеть сверстать посадочную страницу под новый продукт, она в девяти случаях из десяти выдаст стерильный фиолетовый градиент с тремя унылыми карточками преимуществ и кривыми отступами. Проблема не в том, что модель плохо пишет CSS, а в том, что без жесткого дизайн-фреймворка агент пропускает этап смысловой упаковки и сразу…

👍3

7 Nov 2026, 14:33 UTC568 views22 reactionsread 8 November 2026
Video

Ребята из проекта Ц.И.К.А.Д.А сделали вот такой вот ролик для нашего канала 💗 Для любителей фантастики - прям супер формат.

👍5🔥5🥴5🥱4❤3

7 Nov 2026, 06:33 UTC648 views2 reactionsread 8 November 2026
Video

Генерация пиксельных спецэффектов и спрайт-шитов в библиотеке PixelFX Открытый проект PixelFX снимает с инди-разработчиков и вайбкодеров самую нудную часть двумерного геймдева - покадровую отрисовку вспышек, взрывов, заклинаний и ударов, на которой обычные диффузионные нейросети стабильно выдают кривую кашу с плывущей сеткой пикселей. Вместо слепой генерации растра авторы собрали бесплатную библиотеку из 244 выверен…

❤2

6 Nov 2026, 14:32 UTC744 views1 reactionsread 8 November 2026
Photo

Подмена лица на вебке в реальном времени по одному фото в Deep-Live-Cam Классические дипфейк-пайплайны обычно требуют часами собирать датасет из сотен ракурсов и гонять видеокарту всю ночь ради минутного ролика, где губы все равно живут своей отдельной жизнью. Открытая утилита Deep-Live-Cam ужимает этот процесс до одной-единственной фотографии донора и переносит чужую внешность на поток с веб-камеры, живой стрим в O…

😁1

6 Nov 2026, 06:31 UTC767 views8 reactionsread 8 November 2026
Photo

Сверхвысокое разрешение до 6K без мутантов и дообучения в AReA Попытка заставить популярные диффузионные модели вроде FLUX сходу нарисовать холст в 4K или 6K почти всегда заканчивается анатомическим хоррором. Поскольку нейросеть учили мыслить квадратами около тысячи пикселей, на огромном полотне она теряет общую связность сцены и начинает клонировать головы, лепить третьи руки или дробить фон на несвязанные куски. …

❤5🔥2🏆1

5 Nov 2026, 14:33 UTC780 views1 reactionsread 8 November 2026
Photo

Точечная прокачка интерфейса и памяти агента через сборку Claude Mods Работа в длинных сессиях Claude часто напоминает полет по приборам с заклеенной приборной панелью - остаток лимитов подписки не видно до самой блокировки, контекстное окно незаметно забивается мусором, а один случайный вызов терминала может молча снести нужные файлы без лишних вопросов. Открытый набор из пяти независимых плагинов Claude Mods закр…

❤1

5 Nov 2026, 09:03 UTC790 views8 reactionsread 8 November 2026
Photo

Меня тут периодически зовут на всякие конференции: где-то в зале с умным видом посидеть, а где-то даже со сцены про успешный успех поговорить. Очень часто выбраться не получается (сами понимаете: диван сам себя не продавит, да и пельмени стынут). Но каждый раз прям чертовски приятно! И с вами поделиться всегда тянет, потому что все эти события в мире высоких технологий, безусловно, очень важные и невероятно интересны…

🔥3🏆2💯2❤1

5 Nov 2026, 06:30 UTC800 views4 reactionsread 8 November 2026
Photo

Часовая расшифровка на сорока языках в открытой модели Nemotron 3.5 Transcribe Инженеры Nvidia выкатили на Hugging Face открытые веса Nemotron 3.5 Transcribe, которые превращают обычное распознавание голоса в полноценную аналитику длинных созвонов. Модель на тридцать миллиардов параметров с четырьмя миллиардами активных за один присест переваривает аудиозаписи длительностью до целого часа на сорока языках, включая в…

❤4

4 Nov 2026, 14:32 UTC876 views1 reactionsread 8 November 2026
Photo

Интерактивные взрыв-схемы любых механизмов через Teardown Когда для технической статьи, документации или презентации нужно показать внутреннее устройство гаджета в разобранном виде, обычные диффузионные генераторы рисуют красивую фантастику с лишними шестеренками, висящими в воздухе без всякой инженерной логики. Свежий модуль Teardown для Claude Code и Codex решает задачу не слепым рисованием пикселей, а программно…

❤1

4 Nov 2026, 06:33 UTC936 views8 reactionsread 8 November 2026
Photo

Локальная база выживания и ремонта без интернета в Survival LLM Обычная локальная нейросеть без доступа к сети при отключении электричества или связи быстро превращается в уверенного сказочника, который может на полном серьезе перепутать дозировку антибиотика или схему пайки инвертора. Чтобы избавиться от галлюцинаций в полном офлайне, приложение ставит на компьютер не голую языковую модель, а связку с готовой локал…

👍7❤1

3 Nov 2026, 14:30 UTC≈1,250 views4 reactionsread 8 November 2026
Photo

Открытый триллионник Mistral Large 4 по кличке Le Chonk Французы из Mistral выложили в открытый доступ веса своего нового флагмана Mistral Large 4, получившего внутри команды говорящее прозвище Le Chonk за внушительный объем в один триллион параметров. За счет MoE-архитектуры на каждый токен здесь активируется всего 52 миллиарда параметров при контекстном окне в миллион токенов. Три недели назад модель показывали т…

❤3👍1

3 Nov 2026, 06:31 UTC980 views8 reactionsread 8 November 2026
Video

Точечная ретушь без пластилинового мыла в Ideogram 4.5 Любой, кто пытался докрутить сгенерированный макет через обычные диалоговые модели вроде GPT Image или Nano Banana, знает эту боль - уже на третьей итерации правок картинка превращается в пережатое месиво. Попросил поменять цвет куртки, а нейросеть заодно перекроила черты лица, замылила фоновую текстуру и превратила мелкий шрифт на вывеске в инопланетные руны. …

🔥5❤3

Showing the 12 most recent of 64 posts we hold for @neyroskuf. 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.

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 4 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.

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 8 November 2026 — this entry's latest reading, not the date you are reading this.

“Нейроскуф | Про Нейросети&AI” (@neyroskuf), 8,749 subscribers as measured 8 November 2026. Telegram Register, tgregister.com/channel/neyroskuf.

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.