Культурно освещаю самые и не самые важные новости из мира AI, и облагораживаю их своим авторитетным профессиональным мнением.
Ex-Staff Research Scientist в Meta Generative AI. Сейчас CEO&Founder AI стартапа в Швейцарии.
Aвтор: @asanakoy
PR: @ssnowysnow
Created
23 July 2020 — measured — cross-checked against a third-party dataset (ext.tg_channel)
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 20 August 2026 and assigned it the closest of 31 fixed categories, at 100% 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
34 measurements spanning 43 days, net +1,296. 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 95,399–97,083 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 34
Measured (UTC)
Subscribers
Change
18 Sept 2026, 01:39
96,889
+44
15 Sept 2026, 17:56
96,845
+37
14 Sept 2026, 04:19
96,808
+36
12 Sept 2026, 12:35
96,772
-18
10 Sept 2026, 13:39
96,790
+62
7 Sept 2026, 09:20
96,728
+111
4 Sept 2026, 15:00
96,617
+117
3 Sept 2026, 01:15
96,500
+25
2 Sept 2026, 00:54
96,475
+32
1 Sept 2026, 02:46
96,443
+21
31 Aug 2026, 00:18
96,422
+7
30 Aug 2026, 01:07
96,415
+24
28 Aug 2026, 21:52
96,391
+35
27 Aug 2026, 20:17
96,356
+37
26 Aug 2026, 18:04
96,319
+24
25 Aug 2026, 17:17
96,295
+27
24 Aug 2026, 16:16
96,268
+28
22 Aug 2026, 22:49
96,240
+35
21 Aug 2026, 09:55
96,205
+8
20 Aug 2026, 11:37
96,197
first reading
Engagement
78 posts held, back to 16 July 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 105 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
33.3%
avg views ÷ 96,889 subscribers
Avg views / post
32,300
37 posts measured
Reaction rate
0.866%
reactions ÷ views · ER floor
Posts in window
37
of 78 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 22 September 2026
Posts held
78 (16 July 2026 – 22 September 2026)
Views total
1,194,800
Reactions total
10,342
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
23 Sept 2026, 14:20 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
≈2,040
Videos
≈1,060
Links
≈2,380
Lifetime counters from Telegram’s own channel header, read 23 September 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Video runtime
13m 04s
Average length
49s
Measured directly from 16 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
19,592 reactions across 77 posts, in 15 distinct kinds. The most used accounts for 32.6% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
6,394
32.6%
😁
4,052
20.7%
❤
3,640
18.6%
👍
2,317
11.8%
🤯
1,646
8.40%
🦄
317
1.62%
🤩
295
1.51%
😍
213
1.09%
😱
188
0.96%
💯
126
0.643%
🫡
114
0.582%
💔
94
0.48%
❤🔥
84
0.429%
⚡
75
0.383%
🙏
37
0.189%
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 78 of the 78 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 19,994 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 78 most recent posts we hold, published 16 July 2026 to 22 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
99
across the posts below
Posts paid on
27
of 78 we hold a reading for · 35%
Most on one post
33
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @ai_newz. 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 78 most recent posts we hold for this entry, published 16 July 2026 to 22 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.
GPT 6 Sol и Luna
Лучше чем 5.6, при этом в два раза дешевле и использует меньше лимитов Codex. Sol теперь стоит $2/$10 за миллион токенов, прямо как Sonnet. Цену Luna вообще скинули до $0.1/$0.5 за миллион токенов, то есть цену по сравнению с оригинальной 5.6 Luna сбросили в 10 раз. Ну и подписчикам завезли banked reset.
Блогпост
@ai_newz
Anthropic выпустили Opus 5.5
По бенчам на уровне Fable 5.1, уже доступен в чате, клод коде и апи. Цену за токен снизили по сравнению с Opus 5 — теперь она $4/$20 за миллион токенов. Кроме этого повысили пятичасовые лимиты и дали banked ресет.
@ai_newz
Вышел Grok 4.7
Заметный прирост при той же цене и скорости. Маск ранее заявлял что Grok 4.7 должен быть новый претрейн на 2.1 триллиона параметров, но похоже планы поменялись. А тем временм Grok 4.8 с 2.5T параметров должен был закончить тренировку на прошлой неделе и, скорее всего, сейчас уже на стадии RL.
@ai_newz
Вас тоже напрягают записывальщики митингов, которых все сейчас таскают по созвонам? (меня да, особенно пока мы в stealth режиме). А ведь еще часто записывают, ничего мне не говоря, через wispr или granola.
Как и следовало ожидать нашлись люди, которые придумали продукт для противостояния этому.
Локально крутится LLM, которая адверсариально натренирована против wispr и прочих voice2text моделей. Она в риалтайме доба…
Нейродайджест за неделю (#130)
LLM
- Astra в Blender — Два примера видосов, которые модель делает через Blender.
- GigaChat 3.5 Reasoning — Сбер открыли веса MoE 432B-A28B. Шесть экспертов обучали через online RL, затем объединили в одну модель.
Генеративные модели
- ChatGPT Images 2.5 — Более точечные правки и меньше искажений при последовательном редактировании. В Flare примерно в 1,9 раза быстрее Sunburst, но ус…
😮 это все из-за нового гигачата - слишком мощным оказался )))
А если серьезно, то подумайте кому это выгодно – сдерживать своих конкурентов, а также раздувать хайп об угрозах AGI, перед выходом на IPO. AGI уже вот-вот появится, если прям ща все не запретить!))
Ну, а китацы точно клали болт на эти вопли в X, они ничего замедлять уж точно не собираются.
@ai_newz
Krea Agents
Krea собрали среду с тул-юзом для скиллов и пайплайнов. Главная фича тут файловая система. Материалы проекта можно раскладывать по файлам и подгружать в контекст. По словам Krea, агент публикует медиа в соцсети и импортирует мудборды из Pinterest.
Сама идея собирать нейро-контент с агентом не нова. Но обычно для сервисов приходится подключать API или MCP. Здесь Krea как агрегатор уже держит под рукой мо…
Сбер выпустил GigaChat 3.5 Reasoning - обученную с нуля модель с рассуждениями
Веса открыты, лежат на Hugging Face, модель можно использовать в коммерческих продуктах. В основе архитектура 432B-A28B MoE. Это не файнтюн существующей модели из опен-сорса, модель построили с нуля.
Post-train обучение строилось на online RL: не один домен, а шесть отдельных экспертов, каждый со своей наградой, которые потом собрали обр…
Nano Banana для аудио
Tencent выкатили AuK для генерации и редактирования речи. Это 1.5B модель, которая через один интерфейс превращает текст в речь и правит готовые записи по текстовой инструкции. Она клонирует голос по референсу, меняет слова без перезаписи всей фразы, убирает акцент и шум, крутит тембр, эмоцию, скорость и высоту, а ещё отделяет спикера или вокал от микса.
Обучали на 1.95 млн часов "эффективного…
Интересная инфографика от Epoch, показывающий насколько быстро растёт компьют используемый большим лабам. За два года с декабря 2023 по декабрь 2025 количество компьюта доступного OpenAI выросло в 17 раз (под конец 2025, скорее всего, обогнав Google DeepMind), а у Anthropic за один 2025 год — в 6 раз.
Важно что тут показываются именно конечные потребители, а не владельцы компьюта, ведь OpenAI и Anthropic именно что …
Ситуация на image арене с выходом GPT-Image-2.5
Есть две версии модели GPT-Image-2.5: Flare и Sunburst.
Flare работает примерно в 1.85-1.9x быстрее чем Sunburst (по моим замерам), но похуже качеством. Причем цена у Flare и Sunburst одинаковая, и такая же как и на GPT-Image-2 (если брать max reasoning).
Забавно, как произошла инфляция ризонинга. У GPT-Image-2 самый высокий ризонинг назывался High, а у 2.5 после hig…
OpenAI релизнули ChatGPT Images 2.5
В этом релизе помимо качества генерации сконцентрировались на более точном редактировании фото, чтобы модель меняла только нужные детали. Особенно это заметно на multi-turn редактировании изображений, где с каждый шагом редактирование изображение едет меньше чем раньше.
Вместе с моделью, в ChatGPT релизнули возможность генерить изображения на основе скетчей и шаблоны для популярн…
❤100🔥60👍22🦄6🤩2😁2😱2
Showing the 12 most recent of 78 posts we hold for @ai_newz. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Posts edited after publishing
@ai_newz 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
22 August 2026
Most recent edit
22 August 2026
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Republished by 72 registered channels. The 48 listed are the ones that have forwarded the most posts; the rest are counted here but not each listed.
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 131 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 23 listed below are the most frequent namers; the rest are counted above but not each listed.
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 16 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.
Neurogen @neurogen_news · 22,930 Telegram ranks this channel #1 of 88 here — alongside 87 others — read 19 September 2026
gonzo-обзоры ML статей @gonzo_ML · 24,323 Telegram ranks this channel #1 of 93 here — alongside 92 others — read 16 September 2026
Нейроскептик @neuroskep · 29,484 Telegram ranks this channel #1 of 90 here — alongside 89 others — read 8 September 2026
Метаверсище и ИИще @cgevent · 52,361 Telegram ranks this channel #1 of 92 here — alongside 91 others — read 25 August 2026
e/acc @cryptoEssay · 62,598 Telegram ranks this channel #1 of 96 here — alongside 95 others — read 21 August 2026
Сиолошная @seeallochnaya · 79,594 Telegram ranks this channel #1 of 97 here — alongside 96 others — read 19 August 2026
Data Secrets @data_secrets · 93,800 Telegram ranks this channel #1 of 98 here — alongside 97 others — read 17 August 2026
Denis Sexy IT 🤖 @denissexy · 137,325 Telegram ranks this channel #1 of 95 here — alongside 94 others — read 13 August 2026
Machinelearning @ai_machinelearning_big_data · 280,660 Telegram ranks this channel #1 of 95 here — alongside 94 others — read 10 August 2026
CyberYozh AI Security @CyberYozh_AI_security · 26,576 Telegram ranks this channel #2 of 91 here — alongside 90 others — read 12 September 2026
Sber AI @SberAIScience · 27,279 Telegram ranks this channel #2 of 95 here — alongside 94 others — read 10 September 2026
LLM под капотом @llm_under_hood · 29,146 Telegram ranks this channel #2 of 96 here — alongside 95 others — read 9 September 2026
Ai molodca @strangedalle · 46,847 Telegram ranks this channel #2 of 94 here — alongside 93 others — read 27 August 2026
Lama AI @lama_channel_gpt · 24,736 Telegram ranks this channel #3 of 90 here — alongside 89 others — read 15 September 2026
TechSparks @techsparks · 46,537 Telegram ranks this channel #3 of 97 here — alongside 96 others — read 27 August 2026
Малоизвестное интересное @theworldisnoteasy · 74,000 Telegram ranks this channel #3 of 94 here — alongside 93 others — read 19 August 2026
Tips AI | IT & AI @tips_ai · 25,376 Telegram ranks this channel #4 of 95 here — alongside 94 others — read 14 September 2026
Machine learning Interview @machinelearning_interview · 30,308 Telegram ranks this channel #4 of 98 here — alongside 97 others — read 7 September 2026
addmeto @addmeto · 71,835 Telegram ranks this channel #4 of 95 here — alongside 94 others — read 20 August 2026
AI Университет @neural_university_webinar · 37,547 Telegram ranks this channel #5 of 96 here — alongside 95 others — read 31 August 2026
Силиконовый Мешок @prompt_design · 85,657 Telegram ranks this channel #5 of 96 here — alongside 95 others — read 18 August 2026
Двоичный кот @binarcat · 30,854 Telegram ranks this channel #7 of 93 here — alongside 92 others — read 9 September 2026
AI Insider @ai_ins · 42,069 Telegram ranks this channel #10 of 94 here — alongside 93 others — read 29 August 2026
Смотри, Морозов и ИИ @mmmorozov · 61,416 Telegram ranks this channel #10 of 96 here — alongside 95 others — read 23 August 2026
This channel appears in 185 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. 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 18 September 2026 — this
entry's latest reading, not the date you are reading this.
“эйай ньюз” (@ai_newz), 96,889 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/ai_newz.
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.