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Channel

Технозаметки Малышева

@tsingular

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

12,652subscribers

+925 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001884458659
TypeChannel
Username@tsingular
CreatedBetween 1 October 2022 and 30 September 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live17 September 2026
Measurements held33
Confirmed unchanged1 time, most recently 17 September 2026
On Telegramt.me/tsingular

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 11 September 2026 and assigned it the closest of 31 fixed categories, at 99% 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

11,72712,65212,189.56 August 2026 — 11,727 subscribers7 August 2026 — 11,728 subscribers8 August 2026 — 11,729 subscribers8 August 2026 — 11,730 subscribers10 August 2026 — 11,731 subscribers11 August 2026 — 11,728 subscribers12 August 2026 — 11,730 subscribers13 August 2026 — 11,734 subscribers14 August 2026 — 11,743 subscribers16 August 2026 — 11,741 subscribers17 August 2026 — 11,816 subscribers18 August 2026 — 11,817 subscribers19 August 2026 — 11,816 subscribers20 August 2026 — 11,822 subscribers21 August 2026 — 11,821 subscribers23 August 2026 — 11,819 subscribers24 August 2026 — 11,848 subscribers25 August 2026 — 11,852 subscribers26 August 2026 — 11,853 subscribers27 August 2026 — 11,855 subscribers28 August 2026 — 11,857 subscribers29 August 2026 — 11,858 subscribers30 August 2026 — 11,857 subscribers31 August 2026 — 11,854 subscribers1 September 2026 — 11,880 subscribers2 September 2026 — 11,883 subscribers4 September 2026 — 11,916 subscribers6 September 2026 — 12,007 subscribers10 September 2026 — 12,422 subscribers12 September 2026 — 12,427 subscribers13 September 2026 — 12,432 subscribers15 September 2026 — 12,453 subscribers17 September 2026 — 12,652 subscribers6 August 202617 September 2026
33 measurements spanning 42 days, net +925. 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 11,588–12,791 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 33
Measured (UTC)SubscribersChange
17 Sept 2026, 20:3512,652+199
15 Sept 2026, 17:0012,453+21
13 Sept 2026, 23:0112,432+5
12 Sept 2026, 08:5712,427+5
10 Sept 2026, 03:1712,422+415
6 Sept 2026, 23:5812,007+91
4 Sept 2026, 12:0211,916+33
2 Sept 2026, 23:3611,883+3
1 Sept 2026, 18:1311,880+26
31 Aug 2026, 14:5411,854-3
30 Aug 2026, 14:1911,857-1
29 Aug 2026, 16:1711,858+1
28 Aug 2026, 16:4711,857+2
27 Aug 2026, 16:2311,855+2
26 Aug 2026, 17:2811,853+1
25 Aug 2026, 20:0211,852+4
24 Aug 2026, 19:1711,848+29
23 Aug 2026, 01:1611,819-2
21 Aug 2026, 17:0811,821-1
20 Aug 2026, 12:1811,822first reading

Engagement

241 posts held, back to 5 August 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 47 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
13.7%
avg views ÷ 12,652 subscribers
Avg views / post
1,730
45 posts measured
Reaction rate
1.30%
reactions ÷ views · ER floor
Posts in window
45
of 241 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 2 September 2026
Posts held241 (5 August 2026 – 2 September 2026)
Views total77,756
Reactions total1,013
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken2 Sept 2026, 23:33 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.

What this channel posts

Video runtime
3h 39m
Average length
2m 56s

Measured directly from 75 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

5,706 reactions across 241 posts, in 43 distinct kinds. The most used accounts for 26.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥1,53726.9%
😁98117.2%
⚡58610.3%
👍4147.26%
🤣4097.17%
❤3546.20%
✍3035.31%
💯1873.28%
🤯1352.37%
custom 52267488372756413871312.30%
🤔1001.75%
👾741.30%
🆒671.17%
custom 5231475401540247959530.929%
👀490.859%
❤‍🔥390.683%
😢370.648%
😭360.631%
🏆290.508%
👻260.456%
23 further kinds1592.79%

Custom emoji. 2 of the rows above are 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 counts beside them are 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 241 of the 241 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 5,706 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 241 most recent posts we hold, published 5 August 2026 to 2 September 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.

Telegram Stars

Stars received
12
across the posts below
Posts paid on
6
of 241 we hold a reading for · 2%
Most on one post
5
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @tsingular. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.

Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.

This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.

Counted over the 241 most recent posts we hold for this entry, published 5 August 2026 to 2 September 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.

Recent posts

2 Sept 2026, 19:18 UTC705 views12 reactionsread 2 September 2026
Video

Higgsfield выпустили плагин для смартфона, который превращает его в контроллер камеры в сцене. В итоге нейрорендер получил еще больше реализма в кадре. Осталось подключить модели, которые видео рендерят быстрее реального времени и можно прикручивать к играм. #higgsfield #нейрорендер ------ @tsingular

🔥6custom 52267488372756413873❤2⚡1

2 Sept 2026, 19:09 UTC740 views5 reactionsread 2 September 2026
Video

Nousportal запустили реффералку. теперь при покупке подписки вы получите $15 скидки. Т.е. план будет стоить не $20 для вас, а всего $5 Регаться по ссылке #NousResearch #скидки ——— @tsingular

❤‍🔥3⚡1✍1

2 Sept 2026, 18:12 UTC895 views10 reactionsread 2 September 2026
Photo

Gemini 3.8 Flash и отдельная версия для кибербеза Google выкатил Gemini 3.8 Flash: лучшую свою модель для кодинга и рассуждений при цене и скорости 3.7, плюс отдельный вариант 3.8 Flash Cyber для ИБ. Оба варианта построены на общем ядре, прокачанном в том числе тренировкой на задачах кибербезопасности. 🔧 Что умеет базовая 3.8 Flash: На DeepSWE v1.1 обходит большинство больших фронттир-моделей в автономном решении …

🔥8⚡1✍1

2 Sept 2026, 16:24 UTC992 views10 reactionsread 2 September 2026
Photo

Keenable SELECT: веб как таблица, к которой пишешь SQL Стартап Keenable, который в августе вышел из стелса с $26 млн от Accel, показал вторую большую идею: SELECT, отдельный MCP-сервер, где агент запрашивает данные из открытого веба одним SQL-запросом и получает таблицу вместо стены ссылок. Да, по сути каждый сайт становится строкой таблицы: сервер сам гоняет поиски, скачивает страницы, вытаскивает запрошенные поля…

🔥5custom 52267488372756413873⚡1👍1

2 Sept 2026, 14:28 UTC≈1,070 views16 reactionsread 2 September 2026
Forwarded from @xor_journalVideo

Google выпустила Gemini 3.8 Flash — новая быстрая модель уже обходит гигантов в кодинге. По данным WSJ, во внутренних тестах сотрудники Google предпочитали её ответы Claude Opus. Сама модель обещает быть дешевой и заточенной под кодинг и агентные задачи. Gemini 3.8 Flash уже начала появляться у пользователей, так что ждем официального релиза. Сентябрь жаркий на модели 😻 @xor_journal

🔥11🤣5

2 Sept 2026, 12:03 UTC≈1,240 views12 reactionsread 2 September 2026
Photo

bb: агентная IDE, которая строит сама себя На рынке мультиагентных сред свежий игрок: bb, 2,9 тысячи звёзд и 5 344 коммита под лицензией MIT. Идея в том, что тут агенты сами достраивают свою рабочую среду: сервер держит всё состояние в SQLite, демон на каждой машине готовит workspace и запускает процессы агентов, а вход в систему один и тот же из десктопа, веба, CLI и HTTP API. 🔧 Как устроено: Провайдеры подключают…

⚡4🤯4❤2🔥2

2 Sept 2026, 08:51 UTC≈1,250 views11 reactionsread 2 September 2026
Photo

PT Dephaze: LLM в дистрибутиве ищет пароли в сетевых папках Positive Technologies встроила локальную LLM в автопентестер PT Dephaze: теперь продукт сам ищет логины и пароли в корпоративных файлах и строит на них атаки. Именно похищенные учётные записи используются в четырех из пяти кибератак 2026 года. 🔧 Что под капотом: Модель едет в коробке, вместе с дистрибутивом, и не отправляет данные в интернет или третьим ли…

🔥6✍2❤2⚡1

2 Sept 2026, 08:10 UTC≈1,080 views32 reactionsread 2 September 2026
Forwarded from @data_secretsVideo

Fable 5.1 это конечно хорошо, но вы видели, что выпустил стартап Фей-Фей Ли? Встречаете Atlas – первую в истории мультимодальную world model. Она генерирует изображения и видео с контролем камеры на уровне пикселей и (!!!) может реконструировать их в 3D сцены в явном формате point cloud и 3D Gaussian splats. Также обучена Space-time симуляции (четвертый пример). Длительность видео – до 1 минуты в 1440p, и можно при…

🔥14⚡7🤯6❤4✍1

2 Sept 2026, 07:55 UTC≈1,100 views19 reactionsread 2 September 2026
Photo

HiveTraceGuard-Pro: маленький охранник для больших моделей Российская команда HiveTrace выложила в open source компактную guardrail-модель на 0,6B параметров, которой можно закрыть и вход, и выход LLM. Главное: она понимает русский и английский, отдаёт ровно один токен, safe или unsafe, и при этом в топе мирового лидерборда именно на русских данных. 🔧 Что она делает: Работает в двух режимах: input guard проверяет з…

🔥13❤4⚡1🆒1

2 Sept 2026, 07:26 UTC≈1,100 views11 reactionsread 2 September 2026
Video

Lieflat Charts: новый дизайнер навык для агента для построения точных диаграмм Китайская лаборатория выпустила skill для агентов, который превращает сырые данные не в дефолтные графики, а в аккуратные, «редакторские» макеты, как в качественном журнале. В коллекции уже 49 шаблонов графиков и 12 целых шаблонов отчётных макетов, адаптированных для Claude Code, Codex и других агентов, поддерживающих формат SKILL.md. 🔧…

🔥6⚡2✍2🆒1

2 Sept 2026, 07:12 UTC≈1,200 views9 reactionsread 2 September 2026
Photo

Антропики опубликовали системный промпт Клода Fable 5.1 изучаем тут: https://platform.claude.com/docs/en/release-notes/system-prompts/claude-fable-5-1 для тех, кто без интернета файл в комментариях #Fable #prompt ——— @tsingular

✍5⚡2👌1🤝1

2 Sept 2026, 05:20 UTC≈1,330 views22 reactionsread 2 September 2026
Photo

#юмор #dev ——— @tsingular

😁18⚡2🔥2

Showing the 12 most recent of 241 posts we hold for @tsingular. 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.

Posts edited after publishing

@tsingular edited 4 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.

An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.

First edit seen
13 August 2026
Most recent edit
27 August 2026

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 31 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.

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.

Гараж Автоэлектрика
@garage_electro · 51,414
Telegram ranks this channel #57 of 62 here — alongside 61 others — read 25 August 2026

This channel appears in 1 seed channel's Telegram-generated recommendation list 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 17 September 2026 — this entry's latest reading, not the date you are reading this.

“Технозаметки Малышева” (@tsingular), 12,652 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/tsingular.

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.