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Channel

novikov vibe

@novikovvibe

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

303subscribers

+15 since we began measuring on 7 August 2026

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

Register entry

Telegram ID-1003762220704
TypeChannel
Username@novikovvibe
CreatedBetween 1 February 2026 and 30 June 2026— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live15 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 15 August 2026
On Telegramt.me/novikovvibe

Growth

288303295.57 August 2026 — 288 subscribers7 August 2026 — 288 subscribers7 August 2026 — 290 subscribers15 August 2026 — 303 subscribers7 August 202615 August 2026
4 measurements spanning 8 days, net +15. 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 286–305 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
15 Aug 2026, 15:25303+13
7 Aug 2026, 19:54290+2
7 Aug 2026, 05:33288no change
7 Aug 2026, 05:18288first reading

Engagement

14 posts held, back to 11 July 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
62.2%
avg views ÷ 303 subscribers
Avg views / post
189
5 posts measured
Reaction rate
0.739%
reactions ÷ views · ER floor
Posts in window
5
of 14 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. It is computed over the 3 of 5 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 4 August 2026
Posts held14 (11 July 20264 August 2026)
Views total943
Reactions total4
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Aug 2026, 05:33 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.

Reaction mix

8 reactions across 6 posts, in 2 distinct kinds. The most used accounts for 75.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥675.0%
225.0%

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 7 of the 14 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 8reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 14 most recent posts we hold, published 11 July 2026 to 4 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

4 Aug 2026, 14:31 UTC70 views1 reactionsread 7 August 2026

openai выкатили новость, от которой математики начали трогать себя в причинных местах) их новая модель astra решила 10 задач, которые люди не могли решить десятилетиями. не олимпиадные задачки - реальные открытые проблемы из шести областей. одну из них обсуждали с 1999 года, и никто не мог даже подступиться самое жирное - все доказательства проверены формально, через lean 4. это значит, что машина проверила каждый

🔥1

3 Aug 2026, 12:31 UTC91 viewsread 7 August 2026

seedance 2.5 вышла 31 июля. разобрал, что там внутри - и это серьёзная заявка. главное: 30 секунд за один проход. было 15. и это не растянутый один момент - модель сама строит драматургию из нескольких связанных шотов. плюс многораундовое продление с сохранением персонажей и ритма - можно собирать многоминутные видео без склейки. до 50 референсов на вход: 30 картинок, 10 видео, 10 аудио. самая мощная фича — clay r

27 Jul 2026, 18:54 UTC207 views1 reactionsread 7 August 2026

anthropic выкинул 80% инструкций, которые они писали для своего же ии-помощника. и качество не упало а наоборот. всё благодаря новым моделям 5 серии. я сам это впервые почувствовал на fable-5. она не тупила когда нехватало инструкций, а даже наоборот - придумывала лучшие решения. что поменялось: правила → доверие. раньше надо было разжёвывать каждый шаг. сейчас достаточно объяснить принцип - «делай так, чтобы впис

1

21 Jul 2026, 14:03 UTC311 viewsread 7 August 2026
Photo

Google переименовал NotebookLM в Gemini Notebook. По сути, это тот же инструмент, но теперь ещё плотнее связан с экосистемой Gemini. Если ты раньше тратил часы на перечитывание документов перед встречами, поиском нужного пункта в договоре или сбором информации из десятков заметок, попробуй простой тест. Загрузи 3–4 документа по одной теме и задай вопрос, который обычно решаешь вручную. Сервис отвечает только на осн

20 Jul 2026, 12:53 UTC264 views2 reactionsread 7 August 2026
Photo

замечаю, что многие продукты отлично работают пока ты их кому-нибудь не показал) но теперь тестировать идеи можно на ai-персонах, а не только на живых людях что случилось: на github выложили crowdmind - бесплатное приложение для создания ai-персон и прогона через них разных стимулов. задаёте характеристики персоны, показываете ей текст, картинку или идею, смотрите реакцию. открытый проект, можно ставить локально. п

🔥2

13 Jul 2026, 15:39 UTC363 views1 reactionsread 7 August 2026

9 /у fable 5 более стабильное «адаптивное мышление» для глубокого анализа. если задача требует «удержания» сотен страниц документации и сложных исследовательских рассуждений, fable 5 не теряет фокус, в то время как sol может начать «плавать» в огромных контекстах. при этом у fable 5 рассуждение встроено в процесс и всегда активно, тогда как у sol уровень «мыслительных усилий» нужно настраивать вручную. 10 /высокая а

1

13 Jul 2026, 15:39 UTC336 views0 reactionsread 7 August 2026

6 /sol быстрее, но требует осторожности с режимом ultra. gpt-5.6 sol работает на 61% быстрее конкурента, однако её продвинутый режим рассуждений (ultra) потребляет значительно больше токенов на внутренние размышления. если использовать ultra для всех рутинных задач, финансовая выгода модели испарится. 7 /приватность данных (zero data retention) — серьёзный козырь sol для корпораций. fable 5 в обязательном порядке со

13 Jul 2026, 15:38 UTC309 viewsread 7 August 2026

3 /у sol есть скрытая наценка на длинный контекст, о которой важно помнить. базовая цена sol ($5 за 1 млн входных и $30 за 1 млн выходных токенов) кажется вдвое выгоднее fable 5 ($10 / $50). однако при запросах свыше 272 000 токенов весь промпт sol тарифицируется по ставке $10/$45, что практически сравнивает её по цене с fable 5, которая держит единую цену на весь свой миллион токенов контекста. 4 /fable 5 безоговор

13 Jul 2026, 15:38 UTC294 viewsread 7 August 2026
Photo

1 /минимальный разрыв в базовом интеллекте при кардинально разной цене. gpt-5.6 sol набрал 59 баллов в индексе интеллекта artificial analysis, уступив fable 5 всего один балл (60 баллов). при этом стоимость выполнения задачи у модели openai составляет около трети от стоимости fable 5 ($1,04 против $2,75). это смещает фокус выбора с «самой умной» модели на самую экономически эффективную. 2 /разделение ролей: fable 5

11 Jul 2026, 10:52 UTC347 views2 reactionsread 7 August 2026
Photo

4. Картинки — все сгенерируй в например в агрегаторе kie.ai модель GPT image 2) в палитре. Продукт воспроизведи 1-в-1 по фото-референсу (image-to-image). Прозрачность модели фейковая (белый/шахматка) → генерируй на сплошном фоне и вырезай flood-fill'ом от краёв в настоящую альфу; проверь alpha у каждого выреза. 5. Hero — слоями, не одним кадром. Продукт и окружение — отдельные прозрачные слои. Параметры (масштаб, нак

🔥2

Showing the 12 most recent of 14 posts we hold for @novikovvibe. 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 — 1,273,202 of 1,550,220entries 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.

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

“novikov vibe” (@novikovvibe), 303 subscribers as measured 15 August 2026. Telegram Register, tgregister.com/channel/novikovvibe.

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.