Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 9 August 2026 and assigned it the closest of 31 fixed categories, at 98% 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 the other topics.
Observations
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Content that also appears on other registered channels
Posts published here appear in near-verbatim form on 1 other registered channel. This entry also sits inside a group of 107 channels linked by matching posts, directly or through other channels in the group; two members of the group may share no posts with each other. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
Matching posts — open both and compare (6 of the pairs behind the counts below)
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. 9 of the 10 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.
“Published first” means first in this corpus. We hold 60 comparable posts for this entry, running 4 June 2026 to 9 November 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).
Of the group of 107 channels, the one whose matching posts we hold earliest is @moscowmap. That channel is not among the channels listed above, so this entry may share no posts with it and this does not say where this entry’s content came from. It is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_copy, last confirmed 11 November 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
Channels linked by matching posts
This channel is in a group of 107 registered channels linked by matching posts, directly or through other channels in the group. This channel may share no posts with some of the channels listed below, and listed channels may share none with each other. Links are found by comparing text fingerprints across every channel on the register.
Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
56 more channels are in this same group but not listed individually here.
Growth
63 measurements spanning 95 days, net -28,275. 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 89,517–144,549 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 63
Measured (UTC)
Subscribers
Change
10 Nov 2026, 13:15
97,851
-1,015
8 Nov 2026, 22:40
98,866
-2,422
7 Nov 2026, 16:09
101,288
-402
6 Nov 2026, 16:46
101,690
-724
5 Nov 2026, 16:49
102,414
-530
4 Nov 2026, 19:46
102,944
-991
3 Nov 2026, 16:16
103,935
-301
2 Nov 2026, 16:49
104,236
-1,590
1 Nov 2026, 15:08
105,826
-904
31 Oct 2026, 16:00
106,730
-1,549
30 Oct 2026, 16:26
108,279
-1,153
29 Oct 2026, 17:35
109,432
-1,185
28 Oct 2026, 17:51
110,617
-1,010
27 Oct 2026, 18:38
111,627
-233
26 Oct 2026, 19:01
111,860
-1,225
25 Oct 2026, 22:20
113,085
-357
24 Oct 2026, 20:45
113,442
+7,379
23 Oct 2026, 20:25
106,063
-3,759
22 Oct 2026, 20:29
109,822
+13,955
21 Oct 2026, 15:41
95,867
first reading
Engagement
61 posts held, back to 4 June 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 196 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
59.0%
avg views ÷ 97,851 subscribers
Avg views / post
57,800
18 posts measured
Reaction rate
—
this channel exposes no reaction counts
Posts in window
18
of 61 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
Window
Rolling 30 days · latest post in window 10 November 2026
Posts held
61 (4 June 2026 – 10 November 2026)
Views total
1,039,600
Reactions total
—
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
11 Nov 2026, 04:07 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
492
Videos
428
Links
840
Lifetime counters from Telegram’s own channel header, read 11 November 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.
Video runtime
4m 43s
Average length
40s
Measured directly from 7 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.
Recent posts
Telegram’s own ‘edited’ marker: 8 of 18 posts held from the last 30 days (44.4%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
Claude обзавёлся собственными таблицами и онлайн-доской.
В Sheets можно вместе с нейросетью разбирать данные, создавать формулы и работать с несколькими вкладками. В Whiteboards — раскладывать идеи на общей доске, а потом просить ИИ собрать из них внятное резюме.
Заодно приложения партнёров, включая Adobe и Atlassian, теперь могут открываться прямо внутри Claude — без прыжков между вкладками.
Следом обещают Claude…
Anthropic выпустила сразу две новые нейросети — Claude Fable 5.2 и Claude Mythos 5.2. Обе обходят Opus 5.5 почти во всём.
Fable 5.2 генерирует ответы до 30% быстрее предыдущей версии, а использование через API обойдётся в $8 за миллион входных и $40 за миллион выходных токенов. Mythos 5.2 пока доступна только организациям, получившим специальное одобрение.
🗣️ Айтишник
Claude Code можно отправить работать в Blender.
Для этого сделали sand3d — открытую Python-библиотеку, с которой ИИ собирает 3D-объекты из кода. Не просто рисует картинку, а описывает отдельные детали, соединения и то, как они двигаются.
Среди примеров — стиральная машина с открывающейся дверцей, вращающимся барабаном и выдвижным лотком. Готовую модель можно экспортировать для браузера, симулятора или подготовки к …
«Сделай мне такой же сайт» теперь можно поручить ИИ.
Craft Anything изучает, как устроен чужой сайт или приложение, собирает собственную версию, сравнивает её с оригиналом и дорабатывает отличия. Не просто рисует похожий экран, а пытается воспроизвести работу продукта.
Проект открытый, есть версии для Windows, macOS и Linux. Но пока это ранняя альфа — обещать идеальную копию по одной фразе рано.
Референс постепенн…
ChatGPT теперь делает гифки: OpenAI выпустила Images 2.6.
Можно оживить фото товара, персонажа или даже набросок ручкой на тетрадном листе. Вместо статичной картинки получить зацикленную анимацию для поста, реакции или мема. Заодно ускорили генерацию и улучшили сохранение внешности персонажей и деталей при правках. Чтобы просьба „поменяй фон“ не превращала героя в другого человека. Обновление уже доступно в ChatGPT …
Tencent выпустила Hy4 — нейросеть, которая не только отвечает, но и работает за компьютером
В новой версии появились понимание изображений и управление приложениями. Модель умеет разбирать сложные графики, работать с интерфейсами и выполнять многошаговые задачи — в том числе в Blender и CAD.
Обновили и работу с документами: Hy4 может вместе с пользователем редактировать Word, Excel и PowerPoint.
Модель уже доступн…
ИИ-агенту дали навык Stageshow — теперь он сам собирает макеты интерфейсов: от отдельных элементов до целых экранов. В комплекте — анимации и примеры в духе Figma, Slack и Notion. Агент ещё и записывает результат на видео, чтобы его можно было проверить
🗣️ Айтишник
Франция хочет брать плату за интернет-трафик с Netflix, Google и других IT-компаний.
Депутаты одобрили поправку к проекту бюджета на 2027 год: €0,055 за каждый гигабайт данных. Формально платить должны компании, но расходы могут переложить на пользователей
🗣️ Айтишник
NVIDIA выпустила нейросеть для расшифровки аудио на 40 языках
Nemotron 3.5 Transcribe различает говорящих и ставит таймкоды. Можно сохранить слова-паразиты или получить чистый текст
🗣️ Айтишник
MacBook впервые получил сенсорный экран — Apple представили новинку с PROLED-дисплеем и управлением пальцами.
Ноутбук будет иметь две диагонали экрана: 14 и 16 дюймов. Также представили чипы M5 Pro, M5 Max и новое поколение M6.
Спустя 10 лет на MacBook вернули светящееся яблочко.
Цена за такой ноутбук начинается от $2899 (233 тыс. рублей).
🗣️ Айтишник
В России хотят ограничить зарубежный трафик — Минцифры снова обсуждают лимиты на объём данных, сообщает Forbes.
Весь трафик с иностранных доменов предлагают пропускать через ТСПУ, а министерству могут разрешить ограничивать доступ после превышения лимита.
🗣️ Айтишник
Apple выпустили новый iPad mini с OLED-экраном и защитой от воды. Его называют самым большим апдейтом в серии.
Экран увеличился до 8,5 дюйма, корпус стал тоньше. Фронталку наконец перенесли на длинную боковую рамку, под видеозвонки.
Внутри стоит чип A20 Pro: игры и ИИ-задачи работают в разы быстрее, а небольшие нейронки можно запускать прямо на планшете.
Цена — от $699, в продаже с 6 ноября.
🗣️ Айтишник
Showing the 12 most recent of 61 posts we hold for @it_teech. 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
@it_teech edited 1 post 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
6 November 2026
Most recent edit
6 November 2026
Posts recorded as deleted after publishing
We recorded 1 post on @it_teech as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
First seen missing
19 August 2026
Most recent seen missing
19 August 2026
Median time before seen missing
5 days
Seen missing in the last 30 days
0
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
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.
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 17 August 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
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.
КиберГик @cb_geek · 88,905 Telegram ranks this channel #1 of 70 here — alongside 69 others — read 17 August 2026
Айтишник | Апи | Технологии @atishnik · 55,874 Telegram ranks this channel #5 of 81 here — alongside 80 others — read 23 August 2026
involta - технологии, наука, будущее, IT, интернет! @involta · 33,715 Telegram ranks this channel #12 of 89 here — alongside 88 others — read 3 September 2026
TechNews @techlucker · 42,607 Telegram ranks this channel #14 of 79 here — alongside 78 others — read 28 August 2026
По Фактам @pofactam_tg · 119,694 Telegram ranks this channel #40 of 76 here — alongside 75 others — read 17 August 2026
«Про Всё» @pro_vsse · 45,602 Telegram ranks this channel #47 of 62 here — alongside 61 others — read 19 August 2026
This channel appears in 6 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 10 November 2026 — this
entry's latest reading, not the date you are reading this.
“Айтишник” (@it_teech), 97,851 subscribers as measured 10 November 2026. Telegram Register, tgregister.com/channel/it_teech.
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.