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Channel

(sci)Berloga Всех Наук и Технологий

@sberlogabig

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

7,925subscribers

+59 since we began measuring on 6 August 2026

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

Register entry

Telegram ID-1001560440781
TypeChannel
Username@sberlogabig
Created25 January 2022measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live19 September 2026
Measurements held14
Confirmed unchanged1 time, most recently 19 September 2026
On Telegramt.me/sberlogabig

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 47% 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

7,8527,9257,888.56 August 2026 — 7,866 subscribers7 August 2026 — 7,864 subscribers10 August 2026 — 7,866 subscribers13 August 2026 — 7,861 subscribers16 August 2026 — 7,862 subscribers19 August 2026 — 7,858 subscribers23 August 2026 — 7,855 subscribers26 August 2026 — 7,854 subscribers29 August 2026 — 7,852 subscribers1 September 2026 — 7,865 subscribers5 September 2026 — 7,866 subscribers10 September 2026 — 7,864 subscribers14 September 2026 — 7,916 subscribers19 September 2026 — 7,925 subscribers6 August 202619 September 2026
14 measurements spanning 44 days, net +59. 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 7,841–7,936 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
19 Sept 2026, 06:397,925+9
14 Sept 2026, 12:567,916+52
10 Sept 2026, 13:397,864-2
5 Sept 2026, 00:377,866+1
1 Sept 2026, 04:447,865+13
29 Aug 2026, 05:357,852-2
26 Aug 2026, 00:057,854-1
23 Aug 2026, 00:287,855-3
19 Aug 2026, 23:227,858-4
16 Aug 2026, 20:587,862+1
13 Aug 2026, 01:377,861-5
10 Aug 2026, 07:207,866+2
7 Aug 2026, 03:467,864-2
6 Aug 2026, 09:057,866first reading

Engagement

21 posts held, back to 17 May 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 19 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
10.1%
avg views ÷ 7,925 subscribers
Avg views / post
803
2 posts measured
Reaction rate
1.74%
reactions ÷ views · ER floor
Posts in window
2
of 21 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 24 August 2026
Posts held21 (17 May 202624 August 2026)
Views total1,605
Reactions total28
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken28 Aug 2026, 20:15 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
1m 43s
Average length
1m 43s

Measured directly from 1 video 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

337 reactions across 21 posts, in 6 distinct kinds. The most used accounts for 51.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥17251.0%
8324.6%
👍5115.1%
🤩154.45%
🎉92.67%
😁72.08%

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 21 of the 21 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 337 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 21 most recent posts we hold, published 17 May 2026 to 24 August 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

24 Aug 2026, 05:56 UTC725 views10 reactionsread 28 August 2026
Forwarded from @chelovek_nauk

Недавно мы в институте провели семинар об ИИ в математике с потрясающими приглашёнными спикерами: - Легендарный Дмитрий Рыбин рассказал об агентах для совершения открытий и сложных задач - Невероятный Василий Ильин рассказал об автоматической и надёжной формализации математики, а также провёл ликбез, что вообще такое формализация и Lean Мы в основном занимаемся биологией, поэтому спикеры подготовили доклады, которые

7🔥3

22 Aug 2026, 18:37 UTC880 views18 reactionsread 28 August 2026
Forwarded from @datastorieslanguages

​​Cayley puzzles: 666 on claude vs codex Я уже рассказывал, что занимаюсь решением cayley головоломок. В этот раз я пошёл штурмовать головоломки 555 и 666. Почему они сложнее предыдущих? Дело в том, что с каждым увеличением пространства решений и диаметра нам всё сложнее решать задачу. Во-первых, модели у нас двигаются к решению итеративно - каждый дополнительный шаг увеличивает ошибку. Во-вторых, чем длиннее пути,

🔥171

18 Aug 2026, 16:11 UTC≈1,350 views11 reactionsread 28 August 2026
Photo

Анализ NGS-данных от А до Б: открытый мастер-класс по контролю качества Высокопроизводительное секвенирование позволяет находить патогенные мутации, изучать экспрессию генов или расшифровывать древнюю ДНК. Хотя этап секвенирования библиотек объедиалняет NGS-методы, в остальном они могут сильно различаться. Например, где-то мы хотим получить равномерное покрытие генома, а где-то, наоборот, стремимся к ярким пикам. Чт

🔥65

13 Aug 2026, 11:54 UTC≈1,620 views6 reactionsread 28 August 2026
Photo

Продолжается набор на новую программу «Биоинформатика для биологов. Ступень III» https://clck.ru/3VDQsY | Прием заявок до 6 сентября, 23:59 МСК Это самостоятельная двухмесячная программа для специалистов с опытом в биоинформатике с опорой на избранные главы практикума по биоинформатике и передовые вопросы машинного обучения. С 26 сентября по 28 ноября Программа состоит из 5 дисциплин: • Практикум по биоинформатике

2🔥2😁2

10 Aug 2026, 06:01 UTC≈1,930 views15 reactionsread 28 August 2026
Photo

Открытая онлайн-дискуссия «AI-агенты в single-cell» 12 августа в 19:00 Бластим приглашает на встречу «AI-агенты в анализе данных секвенирования единичных клеток: необходимость или информационный пузырь?» На одной площадке встретятся ведущие эксперты из МГУ, МФТИ и Медицинского университета Вены, чтобы поделиться позитивным и горьким опытом. Главный вопрос: может ли AI-агент взять на себя значительную часть рутинно

🔥94🎉2

5 Aug 2026, 14:30 UTC≈1,780 views10 reactionsread 28 August 2026
Photo

🔥AI R&D DAY — конференция для исследовательских команд и создателей ИИ-систем Мы активно готовимся к масштабной встрече в Москве 17 сентября и приглашаем вас стать частью этого события! Один день, 600 участников, 22 доклада, 2 трека — концентрат практического опыта, знаний и инструментов, готовых к внедрению сразу по возвращению в офис. И, конечно, мега-возможности для нетворкинга с коллегами и экспертами сообщества

👍64

4 Aug 2026, 10:00 UTC≈1,400 views17 reactionsread 28 August 2026
Forwarded from @datastorieslanguages

​​CayleyPy: Professor Tetraminx puzzle Месяц назад я рассказывал как участвовал в ресерч соревнованиях Cayley. С тех пор я поучаствовал в ещё одном соревновании - Professor Tetraminx. Напоминаю, что суть задачи - из рандомного состояния головоломки (после N поворотов) дойти в исходное за минимальное количество шагов. Поскольку это по факту групповой ресерч, не были цели собрать топ-решения самостоятельно - мы хоте

🔥98

3 Aug 2026, 14:00 UTC≈1,370 views6 reactionsread 28 August 2026
Photo

Завтра – последний день ранней цены на онлайн-воркшоп «Альфа, альфа, альфа»! bioinf.me/education/workshops/alpha_workshop 4 августа заканчивается период сниженной стоимости на онлайн-воркшоп по инструментам AlphaGenome, AlphaFold и AlphaMissense (8 и 15 августа). С 5 августа цена вырастет с 9 000 ₽ до 14 000 ₽. Воркшоп пройдет онлайн 8 и 15 августа и будет состоять из двух больших блоков: 🌑 8 августа – AlphaGenome

👍2🔥2😁2

27 Jul 2026, 09:19 UTC≈1,960 views12 reactionsread 28 August 2026
Photo

💡 За одно лето: машинное обучение с нуля до собственных проектов Про искусственный интеллект доносится из каждого утюга: что ни день, то очередная супермощная модель или прорывное открытие. Тут научились распознавать, здесь детектировать, там генерировать. В НИИ все тоже говорят об ИИ. Читаешь новые статьи — везде нейросети и куча заумных терминов. Многим ученым тоже хочется начать применять машинное обучение в сво

🔥7🤩31👍1

17 Jul 2026, 11:39 UTC≈2,270 views22 reactionsread 28 August 2026
Photo

Коллеги, привет! Меня зовут Василий Леоненко, я кандидат физико-математических наук, занимаюсь вычислительной эпидемиологией и моделированием живых систем. Я люблю предсказывать и прогнозировать. Люблю, когда модели интерпретируемы, а прогнозы понятны и однозначны. Поэтому я всегда предпочитал строгие математические законы и дифференциальные уравнения. Но жизнь меня заставила изменить свою точку зрения. В понедельн

👍13🔥54

15 Jul 2026, 20:15 UTC≈1,790 views30 reactionsread 28 August 2026
Forwarded from @forodirchNEWSPhoto

⚡️международный рекорд по сборке мегаминкса побит! Один из подходов на видео, и на соседнем -- запутывание. Результат 9.6 секунд. До этого известный результат 8 минут :-) Поздравляю команду starkit и Илью Осокина. И немножко горжусь что причастен :-) на днях будут хорошие видео и официальная новость. Такие дела:-)

21🔥9

10 Jul 2026, 07:19 UTC≈2,580 views18 reactionsread 28 August 2026
Photo

Мусор на входе — мусор на выходе: как выйти из порочного круга в ML? Когда речь заходит о машинном обучении, все сразу начинают обсуждать алгоритмы, метрики и функции потерь. Между тем любые модели, даже самые навороченные нейросети, учатся на данных. От их качества напрямую зависит успех. Если подать шумные и «грязные» датасеты, то и результаты окажутся бессмысленными. Поэтому львиную долю времени специалисты ML и

🔥11🤩32🎉2

Showing the 12 most recent of 21 posts we hold for @sberlogabig. 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

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 7 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.

Appears in Telegram’s recommendations for other channels

The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.

Sci_Career
@sci_career · 30,335
Telegram ranks this channel #17 of 92 here — alongside 91 others — read 7 September 2026
АНЧА БАРАНОВА
@anchabaranova · 35,710
Telegram ranks this channel #19 of 98 here — alongside 97 others — read 2 September 2026
Ordo Nexus
@nexus_search · 66,521
Telegram ranks this channel #25 of 74 here — alongside 73 others — read 22 August 2026
Русский research
@trueresearch · 26,453
Telegram ranks this channel #28 of 95 here — alongside 94 others — read 12 September 2026
Зоопарк из слоновой кости
@ivoryzoo · 31,450
Telegram ranks this channel #28 of 97 here — alongside 96 others — read 6 September 2026
Медач | Medical Channel
@medach · 28,118
Telegram ranks this channel #47 of 97 here — alongside 96 others — read 10 September 2026
gonzo-обзоры ML статей
@gonzo_ML · 24,323
Telegram ranks this channel #63 of 93 here — alongside 92 others — read 16 September 2026
Data Secrets
@data_secrets · 93,800
Telegram ranks this channel #66 of 98 here — alongside 97 others — read 17 August 2026
Онкология простыми словами
@oncolya · 27,282
Telegram ranks this channel #80 of 98 here — alongside 97 others — read 11 September 2026
LLM под капотом
@llm_under_hood · 29,146
Telegram ranks this channel #85 of 96 here — alongside 95 others — read 9 September 2026
Machinelearning
@ai_machinelearning_big_data · 280,660
Telegram ranks this channel #88 of 95 here — alongside 94 others — read 10 August 2026
Machine learning Interview
@machinelearning_interview · 30,308
Telegram ranks this channel #94 of 98 here — alongside 97 others — read 7 September 2026

This channel appears in 12 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.

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 19 September 2026 — this entry's latest reading, not the date you are reading this.

“(sci)Berloga Всех Наук и Технологий” (@sberlogabig), 7,925 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/sberlogabig.

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.