Telegram RegisterThe public register of Telegram

Channel

Inference Skald

@InferenceSkald

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

49subscribers

+0 since we began measuring on 9 August 2026

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

Register entry

Telegram ID-1003531999254
TypeChannel
Username@InferenceSkald
Description- Эпические сказания о технологиях и интеллектуальных системах. - Делюсь реальным опытом создания production AI систем. Новости, тренды, направления, tips&tricks через призму опыта. - Глава отдела, solution architect, 25 лет в IT. - Посты раз в 3-7 дней.
Created27 April 2026measured — dated from the channel’s first post
First recorded10 August 2026
Last confirmed live10 August 2026
Measurements held2
On Telegramt.me/InferenceSkald

Growth

499 Aug 2026, 15:45 — 49 subscribers10 Aug 2026, 12:31 — 49 subscribers9 Aug 2026, 15:4510 Aug 2026, 12:31
2 measurements taken within a single day. 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 48–50 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
10 Aug 2026, 12:3149no change
9 Aug 2026, 15:4549first reading

Engagement

9 posts held, back to 27 April 2026the 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.

ERR · 30 days
64.3%
avg views ÷ 49 subscribers
Avg views / post
31.5
2 posts measured
Reaction rate
15.9%
reactions ÷ views · ER floor
Posts in window
2
of 9 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 28 July 2026
Posts held9 (27 April 202628 July 2026)
Views total63
Reactions total10
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken10 Aug 2026, 12:31 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
6
Links
6

Lifetime counters from Telegram’s own channel header, read 10 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.

Reaction mix

55 reactions across 8 posts, in 6 distinct kinds. The most used accounts for 61.8% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍3461.8%
🔥1527.3%
👏23.64%
😱23.64%
11.82%
👀11.82%

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 8 of the 9 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 55reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 9 most recent posts we hold, published 27 April 2026 to 28 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.

Recent posts

28 Jul 2026, 08:15 UTC32 views5 reactionsread 10 August 2026

🤔 Почему так произошло? Из-за системы доверия к модели. Разработчики хорошо планируют, но верификация ослабевает по мере роста доверия. AI под шумок всё упрощает, скрывая ошибки. Даже опытные сеньоры начинают "скользить, дрифтить”. В целом бенефиты AI проявляются в двух режимах: Augmentation (дополнение и усиление наших возможностей) и Automation (автоматизация процессов). Выглядит так, что уровни 3-4 это полная авт

👍3🔥2

28 Jul 2026, 08:13 UTC31 views5 reactionsread 10 August 2026
Photo

5 уровней адаптации AI с неопределённой вероятностью достижения Совсем недавно Борис Черны (создатель Claude Code из Anthropic) сделал твит, который хорошо описал то, что крутилось в голове, но никак не могло структурироваться. Он создал таблицу с этапами внедрения AI в разработку софта, объясняя почему одни разработчики еле внедряют AI, а другие уже условно "улетели в космос". Я даже перевёл табличку на русский для

👍3🔥2

25 Jun 2026, 06:46 UTC149 views9 reactionsread 10 August 2026
Photo

🚀 Быстрые LLM модели - ключ к новым возможностям. Ниже обзор скоростей разных моделей на рынке на Июнь 2026. И флекс на тему что это даёт. ❓ Зачем важна скорость в технологиях? - Быстрые паровые корабли изменили правила игры в мировой торговле. - Быстрые платёжные системы создали новые бизнес-модели, мгновенные переводы, микротранзакции и тд. - Быстрые камеры и сенсоры привели к автономному транспорту. Часто технол

👍5🔥4

17 Jun 2026, 07:54 UTC74 views5 reactionsread 10 August 2026

OpenAI признала чистый убыток в $39 млрд за 2025 год при выручке $13 млрд. ...При этом ежемесячная выручка OpenAI к концу года достигла $2 млрд. 👉🏻 Что это значит? У одного из лидеров убытки, которые нужно компенсировать рано или поздно. Итого выручка: 2*12 = $24 млрд в 2026. Убытки примерно на уровне 2025-го: $39 млрд. Если они хотят получать прибыль $10 млрд в год, им нужно поднимать ценник на свои продукты ровно

👍3👀1😱1

30 May 2026, 18:21 UTC88 views5 reactionsread 10 August 2026

⭐️ Мои наблюдения по итогам использования Hermes: * Hermes превосходит OpenClaw по безопасности и количеству возможностей * Локальные модели (3B/4B/8B) пока ещё слабые. Многие пользователи разочаровываются после какого-то времени. Но Hermes умеет делегировать простые задачи разным моделям. Именно здесь небольшие LLM раскрывают свои сильные стороны * LLM модели, которые сейчас дают отличное соотношение качества и сто

👏2🔥2👍1

30 May 2026, 18:21 UTC61 views7 reactionsread 10 August 2026
Photo

Так-с, теперь у меня есть Hermes — мой персональный ассистент, который очень хорошо меня знает. Я инвестировал некоторое время на его обучение (с помощью Skills), чтобы он выполнял за меня рутинные задачи, и сейчас стараюсь делегировать ему ещё больше работы. Общаюсь с ним голосом и, если нужно, он отвечает мне голосом в ответ. Всё через Telegram. Слышали про OpenClaw и Hermes? Это одна из главных причин, почему сей

👍6😱1

26 May 2026, 06:06 UTC68 views7 reactionsread 10 August 2026
Photo

Выходит, что AI пока не может нас заменить 🎉 Галлюцинации, игнорирование исходных инструкций, игнорирование собственной истории действий и неверная трактовка наблюдений из окружения - это всё ещё актуально и требует приличных усилий, чтобы в какой-то мере сдерживать эти недостатки. В итоге система сдерживания (harness) сама становится сложной и хрупкой. Но можно значительно автоматизировать нашу повседневную рутину.

👍61

11 May 2026, 20:04 UTC71 views12 reactionsread 10 August 2026
Photo

Почти середина 2026-го года, но уже интересно посмотреть на отчёты крупных агентств и институтов по анализу рынка AI решений. Что же сбылось, что нет. И что вообще происходит на рынке. Во первых, есть такой индекс - Tech hype cycle - ежегодный отчёт от Gartner. Он показывает на каком этапе развития/принятия находится сейчас технология. И сколько лет нужно, когда она станет реально рабочим инструментом, принимаемым в

👍7🔥5

Showing the 9 most recent of 9 posts we hold for @InferenceSkald. 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 — 985,992 of 1,478,351entries 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

Names

Channels on the register whose handles appear in this channel's posts.

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 10 August 2026 — this entry's latest reading, not the date you are reading this.

“Inference Skald” (@InferenceSkald), 49 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/InferenceSkald.

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.