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 30 September 2026 and assigned it the closest of 31 fixed categories, at 92% 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
3 measurements spanning 41 days, net -1. 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 29–30 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
17 Sept 2026, 15:38
29
-1
11 Aug 2026, 04:15
30
no change
7 Aug 2026, 13:58
30
first reading
Engagement
8 posts held, back to 27 October 2024 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of 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 12 November 2024. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
46s
Average length
15s
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
28 reactions across 3 posts, in 3 distinct kinds. The most used accounts for 57.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
custom 5208724465852110767
16
57.1%
🔥
10
35.7%
👍
2
7.14%
Custom emoji. One row above is a 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 count beside it is 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 3 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 28 reactions 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 October 2024 to 12 November 2024, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
🆓 Быстрый, удобный ии бот прямо в строке!
🔔 Был реализован очень полезный инлайн бот на базе gpt 4o mini 💬
Что это значит?
Вы можете вызвать бота через @GemQbot в начале строки в ЛЮБОМ чате и задать вопрос, ответ на который будет сгенерирован за считанные секунды 😮
💎 Преимущество над аналогами в том, что не нужно писать в личку бота и куда либо подписываться, а ещё хуже, платить ❌
Так же, если есть идеи, пожелан…
👋 Теперь доступна функция обратной связи!
Вы можете легко связаться со мной через бота. Просто напишите любое сообщение, и я сразу его увижу. 😐
Буду рад вашим вопросам, предложениям и отзывам — всё читаю и стараюсь отвечать быстро.
@FeedbackElBot
В настоящее время я занят другим проектом, но недавно начал осваивать библиотеку Three.js и создал этот симпатичный кристаллик 💎.
Думаю, в скором времени сделаю более сложный и красивый проект! 🔥
> Код
Доброго времени суток, около года назад, практикуясь в написании различных скриптов на python, нашёл готовую модель нейросети для анализа видео и распознавания объектов, YOLO (You Only Look Once).
В примере я использовал его для анализа и классификации транспортного потока. Здесь YOLO показала себя как мощный инструмент. ⭐️
Можно и самому поэкспериментировать в данной области:
> Код
🤡 JetBrains буквально шлют куда подальше
При попытке использовать их продукт из России (Если ты хочешь использовать имеющийся ключ или просто пытаешься скачать из России),
поэтому я считаю, что я имею полное право распространить обход.
1. Скачиваете любой продукт JetBrains с их официального сайта, выбирайте сразу Ultimate форматы, за которые они хотят деньги.
2. Открываете 3.jetbra.in
3. Выбираете любое живое зерка…
Всё чаще и чаще я начал замечать заинтересованность людей в пентестинге. Если вы тоже хотите попробовать себя в этом, начните с Burp Suite — инструмента, который помогает искать уязвимости, такие как XSS и SQL-инъекции. Даже в бесплатной версии он даёт огромные возможности.
Рамазан Рамазанов
В 99% случаев при багхантинге использую только Burp Suite
А чтобы быстрее освоиться, загляните на standoff365.com — форум, где…
Showing the 8 most recent of 8 posts we hold for @elcavern. 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.
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 17 September 2026 — this
entry's latest reading, not the date you are reading this.
“el cave” (@elcavern), 29 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/elcavern.
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.
