Telegram RegisterThe public register of Telegram

Channel

Efineuro

@efineuro

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

20subscribers

+0 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1003162286979
TypeChannel
Username@efineuro
DescriptionCreative art neuro https://www.instagram.com/efimistan/ Personal: @efimistan https://www.linkedin.com/in/efim-pilyugin-767568234/
Created27 September 2025measured — dated from the channel’s first post
First recorded11 August 2026
Last confirmed live12 August 2026
Measurements held2
On Telegramt.me/efineuro

Growth

206 August 2026 — 20 subscribers11 August 2026 — 20 subscribers6 August 202611 August 2026
2 measurements spanning 5 days. 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 19–21 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
11 Aug 2026, 15:1520no change
6 Aug 2026, 12:1720first reading

Engagement

8 posts held, back to 27 September 2025the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.

Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 8 posts for this entry, the most recent from 7 June 2026. An engagement rate over an empty window would be a number about nothing.

What this channel posts

Photos
4
Videos
3
Links
5

Lifetime counters from Telegram’s own channel header, read 11 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
2m 59s
Average length
1m 00s

Measured directly from 3 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

48 reactions across 6 posts, in 5 distinct kinds. The most used accounts for 39.6% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
1939.6%
🔥1633.3%
💯612.5%
🥰510.4%
🌭24.17%

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 6 of the 8 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 48reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 8 most recent posts we hold, published 27 September 2025 to 7 June 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

7 Jun 2026, 18:57 UTC55 views1 reactionsread 11 August 2026
Forwarded from @sinnerkot_talksVideo

artdirectiondeepdive.com Большая часть образовательного материала ADDD была и будет бесплатной для всех, так как ресурс в первую очередь направлен на повышение уровня специалистов и развитие индустрии. Но если вам не хватает знаний, вы хотите получить большую информацию и состоять в закрытом сообществе — то для вас существует подписка. artdirectiondeepdive.com

🔥1

7 Jun 2026, 18:56 UTC52 views1 reactionsread 11 August 2026
Forwarded from @sinnerkot_talksVideo

artdirectiondeepdive.com Прошло 1,5 года с момента релиза первой версии ADDD. На первой итерации удалось отточить то, как должен выглядеть формат, как должны проходить занятия, какой информации не хватает. И понять главное - чем же это должно стать в итоге, и в каком виде? Сегодня, я готов представить вам релиз полностью обновленной версии ADDD. Полноценной системы перехода от дизайнера к арт-директору. artdirecti

🔥1

8 Apr 2026, 17:54 UTC141 views11 reactionsread 11 August 2026
Forwarded from @designprostPhoto

Этот выпуск – эксперимент: мы с Ефимом Пилюгиным и Константином Степанчкуком решили сделать подкаст в формате панельной дискуссии. Ефим за несколько лет перепробовал десятки ИИ-инструментов для видеопроектов, провел собственное исследование и вывел данные в презентацию (ссылка в конце описания к выпуску). Обсуждаем, как нейросети меняют дизайн-процессы, какие ИИ-тренды возникают на глобальном рынке, чем ИИ-инструмен

3🔥3🥰3🌭2

1 Mar 2026, 23:35 UTC163 views5 reactionsread 11 August 2026
Photo

VR‑сцена для студии BLIT Следующий проект случился уже на новом уровне для испанской студии BLIT, и формат был VR. Это был не эксперимент, а реальный продакшн с чёткими дедлайнами. Внутри проекта было несколько сцен, и за одну из них отвечал я. Задача: показать Барселону в духе модернизма 1920‑х, но без опоры на конкретные здания. Нужно было создать атмосферу старого города с элементами эпохи и характером узких ули

3🥰2

28 Sept 2025, 19:12 UTC303 views17 reactionsread 11 August 2026
Video

Первый проект с ИИ Хочу сразу ввести вас в лор канала и сделать это через свой первый проект, где я применил ИИ. Делал я его с помощью Fooocus (под капотом Stable Diffusion XL). Мне тогда очень понравился интерфейс и сам процесс работы. Это был 2023–2024 год, время, когда видео-генераторы только зарождались, но статика уже могла удивлять. Основная задача стояла, приблизиться к визуалу Пабло Пикассо. И тут мне повез

9🔥5💯3

27 Sept 2025, 18:52 UTC255 views13 reactionsread 11 August 2026

Привет! Решил наконец-то завести этот канал. Я не могу сказать, что обладаю какой-то узкой экспертностью, но и ограничиваться «базовым пакетом» знаний тоже не про меня. Где-то я силён больше, где-то меньше. За свою карьеру успел поработать и как монтажёр, и как 3D-дженералист в крупных проектах. Поэтому здесь я хочу делиться чем-то действительно интересным. Этот канал, не совсем про «технарщину» и не совсем про чист

🔥64💯3

Showing the 8 most recent of 8 posts we hold for @efineuro. 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.

Citation-graph rank

Citation-graph rank — 784,309 of 1,336,469entries 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

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 1 registered channel — 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.

“Efineuro” (@efineuro), 20 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/efineuro.

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.