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 9 September 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
35 measurements spanning 51 days, net -741. 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 30,250–31,213 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 35
Measured (UTC)
Subscribers
Change
26 Sept 2026, 16:17
30,361
-86
19 Sept 2026, 17:57
30,447
-21
17 Sept 2026, 05:57
30,468
-27
15 Sept 2026, 04:19
30,495
-30
13 Sept 2026, 11:00
30,525
-25
11 Sept 2026, 15:58
30,550
-35
9 Sept 2026, 00:57
30,585
-63
5 Sept 2026, 17:38
30,648
-24
3 Sept 2026, 15:21
30,672
-21
2 Sept 2026, 07:33
30,693
-13
1 Sept 2026, 11:03
30,706
-13
31 Aug 2026, 12:37
30,719
-24
30 Aug 2026, 11:55
30,743
-8
29 Aug 2026, 11:16
30,751
-6
28 Aug 2026, 11:47
30,757
-18
27 Aug 2026, 13:03
30,775
-21
26 Aug 2026, 13:13
30,796
-18
25 Aug 2026, 12:15
30,814
-19
24 Aug 2026, 10:16
30,833
-25
22 Aug 2026, 21:04
30,858
first reading
Engagement
123 posts held, back to 29 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 84 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
5.29%
avg views ÷ 30,361 subscribers
Avg views / post
1,610
62 posts measured
Reaction rate
0.609%
reactions ÷ views · ER floor
Posts in window
62
of 123 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 26 September 2026
Posts held
123 (29 July 2026 – 26 September 2026)
Views total
99,630
Reactions total
607
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
27 Sept 2026, 05:19 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
≈3,150
Videos
≈1,750
Links
≈3,590
Lifetime counters from Telegram’s own channel header, read 27 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
3h 40m
Average length
5m 22s
Measured directly from 41 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
1,203 reactions across 123 posts, in 25 distinct kinds. The most used accounts for 55.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
666
55.4%
👍
200
16.6%
🔥
140
11.6%
😁
71
5.90%
🤣
30
2.49%
🆒
14
1.16%
🤔
13
1.08%
👏
10
0.831%
💯
9
0.748%
⚡
7
0.582%
🤯
7
0.582%
🙈
5
0.416%
🤪
5
0.416%
😱
4
0.333%
👌
3
0.249%
🗿
3
0.249%
😡
3
0.249%
😢
3
0.249%
😨
2
0.166%
🙉
2
0.166%
5 further kinds
6
0.499%
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 123 of the 123 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 1,203 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 123 most recent posts we hold, published 29 July 2026 to 26 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
2
across the posts below
Posts paid on
1
of 123 we hold a reading for · 0.8%
Most on one post
2
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @NeuralToday. 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 123 most recent posts we hold for this entry, published 29 July 2026 to 26 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.
Advertising
Ad load
1.63%
2 of 123 posts carry an ad marker
Regulatory tokens
2
posts carrying an erid · 2 distinct tokens
Median views · ads
1,900
over 2 measured posts
Median views · rest
1,820
over 121 measured posts
An ad marker, not a judgement about a post. A post is counted here because it carries one of two explicit markings: an erid token, which Russian law has required on paid placements since 2022 and which is issued against a specific advertising contract, or a #реклама / #ad hashtag in the body, which is the channel declaring it itself. The first is documentary; the second is a self-declaration and is weaker. No classifier reads the text and decides — nothing on this site guesses that a post is an advertisement.
This is a floor, and it can only ever be a floor. A channel that runs paid placements without marking them produces no marker for us to count, and an unmarked ad is indistinguishable from an ordinary post on the public surface. The ad load above therefore means “the share of posts that declared themselves”, never “the share of posts that were paid for”. A low figure is not evidence of a channel that runs few ads.
Both figures are medians, and no ratio between them is published. Each is a view reading that actually occurred on a post, picked by percentile_disc rather than averaged, so one viral post cannot move it and no interpolated value is invented between two readings. The sample on one side is under five posts, which is too thin to compare. The two figures are shown side by side with the count behind each, and deliberately not divided into a headline like “ads get x% fewer views” — an arithmetic that is easy to print and, at this sample size, means nothing.
Advertising tokens recorded on this entry
erid
Posts
First seen
Last seen
2VtzquyNAdp
1
3 August 2026
3 August 2026
2VtzqxYzWjL
1
30 July 2026
30 July 2026
A token repeated across several posts is one advertising contract placed more than once, which is what the identifier is for. The strings are reproduced exactly as they appeared in the post or in its click-through URL and are not validated against any registry — we record the marker a channel published, and whether it resolves to a real contract is a question for the register that issued it.
Measured over the 123 most recent posts we hold, published 29 July 2026 to 26 September 2026. Views are the latest single reading held for each post, and any reading at or above 1,000 is rounded by Telegram to three significant figures.
Один навык Claude Code, который нужен для создания таких видео.
Он анализирует ваш репозиторий и за один запуск собирает полноценный промо-ролик с анимированной графикой, звуковым оформлением и текстом для запуска.
https://github.com/latent-spaces/brag
📢 Bard & Gemini
Google отправляет свои TPU в космос. Буквально.
Уже на следующей неделе чипы полетят на орбиту на Falcon 9, где будут выполнять AI-нагрузки под воздействием радиации и экстремальных температур.
Это первый шаг к идее космических дата-центров, которые смогут использовать огромное количество солнечной энергии. Следом Google планирует испытать лазерную связь между спутниками.
📢 Bard & Gemini
AI-агент OpenAI взломал Австралийский госпортал
18 июня агенту поручили изучить расходы на здравоохранение. Для этого он отправился на портал статистики Medicare, столкнулся с ограничениями доступа и добрался до непубличных разделов.
На этом не остановился: агент не только прочитал файлы, но и записал полученные данные в базу. По данным австралийских властей, речь шла об агрегированной статистике, а не о личных мед…
DeepSeek выпустила официальный десктопный клиент Harness для Windows и macOS
Теперь DeepSeek Harness можно запускать обычным двойным кликом - без установки Node.js, терминала и открытой вкладки в браузере.
Пока доступна предварительная версия 0.1.7 RC для Windows x64 и Mac на Apple Silicon. Установщики уже опубликованы на домене DeepSeek, а в репозитории появилась документация для десктопного приложения.
Кто давно…
ИИ-агенты начинают работать связками — один координирует, остальные выполняют
Для сложных задач одного агента часто недостаточно: ему приходится искать информацию, работать с документами, обращаться к разным сервисам и проверять результат. Поэтому всё чаще используется схема, где задача распределяется между несколькими специализированными агентами.
Вокруг этого развивается отдельный слой инфраструктуры: skills зада…
Google выкатила Gemini 3.8 Flash TTS и Flash-Lite TTS - новые модели для генерации речи
По заявлению Google, новинки уже заняли первые места в профильных бенчмарках. Flash-Lite при этом рассчитана на более дешёвую генерацию аудио.
Что умеют модели:
• Поддерживают 100+ языков и диалектов, включая русский, и предлагают более 2000 готовых голосов с разными акцентами.
• Могут клонировать голос по 30-секундной записи и…
Для GPT-6 Sol и Opus 5.5 уже вышли официальные гайды по промптингу
Разработчики рассказали, как выжать максимум из новых моделей. И подходы немного отличаются:
GPT-6 Sol и Luna: чётко формулируем цель, желаемый формат ответа и степень автономности модели. Промпт лучше начинать с коротких инструкций, добавляя контекст по мере необходимости. Для простых задач можно обойтись без расширенного рассуждения.
Opus 5.5: ос…
Google показала движок для создания армий ИИ-агентов и для старта не обязательно уметь писать код.
Система позволяет запускать помощников в отдельных песочницах, подключать MCP-серверы и скиллы, ставить агентов на паузу без лишнего расхода ресурсов и возвращать их к работе после сбоев без потери контекста.
Вдобавок, журнал действий каждого бота и заявленная поддержка миллиардов задач в одном кластере.
Проект ещё р…
Есть новая версия вечного вопроса «а мы вообще есть в выдаче?». Только теперь речь не про Google и Яндекс, а про ChatGPT и другие нейросети.
Люди всё чаще спрашивают у них не просто информацию, а конкретные рекомендации: какой сервис выбрать, где заказать услугу, какую компанию рассмотреть. Нейросеть сразу выдаёт несколько вариантов — и среди них может быть ваш конкурент, а вас вообще не быть.
Отсюда и появился GEO…
Anthropic выкатила Claude Opus 5.5 — мощнее, быстрее и дешевле предыдущего Opus
По заявлению компании, новая модель сопоставима по возможностям с Fable 5.1 и GPT-6 Astra, а на Terminal-Bench, Cursor-Bench и ряде других тестов показывает результаты выше.
При этом Opus 5.5 стала дешевле Opus 5: теперь миллион входных токенов стоит $4 вместо $5, а выходных — $20 вместо $25. Anthropic также заявляет, что модель тратит …
И OpenAI подтянулась с новым релизом: встречайте GPT-6 Sol и Luna
Sol стала примерно вдвое дешевле и теперь стоит $2/$10 за 1 млн токенов. Luna подешевела ещё сильнее – до $0.1/$0.5
Плюсом подписчикам выдали по одному сохранённому сбросу лимита 👋
Обе модели уже доступны в подписках и API, а Luna ещё и бесплатно.
❤7
Showing the 12 most recent of 123 posts we hold for @NeuralToday. 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.
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 6 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.
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 7 September 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.
Айтишная @aitshnya · 70,273 Telegram ranks this channel #3 of 93 here — alongside 92 others — read 20 August 2026
Нейролента @neirosety · 30,195 Telegram ranks this channel #11 of 87 here — alongside 86 others — read 7 September 2026
PRO | Нейросети @pro_neiroset · 31,807 Telegram ranks this channel #11 of 86 here — alongside 85 others — read 5 September 2026
Chad GPT | Нейросети @AI_Chad · 21,241 Telegram ranks this channel #13 of 79 here — alongside 78 others — read 24 September 2026
Костыль @kostylofficial · 1,295,474 Telegram ranks this channel #16 of 72 here — alongside 71 others — read 12 August 2026
Midjourney | Диджитал @digital_midjourney · 29,307 Telegram ranks this channel #17 of 81 here — alongside 80 others — read 8 September 2026
GPT-4 Community @gpt4_tg · 54,143 Telegram ranks this channel #20 of 90 here — alongside 89 others — read 23 August 2026
Исходный код @source_code · 33,558 Telegram ranks this channel #21 of 93 here — alongside 92 others — read 4 September 2026
MDJ School | IT, нейросети @mdj_school · 24,649 Telegram ranks this channel #26 of 88 here — alongside 87 others — read 15 September 2026
GeekNeural @geekneural · 63,099 Telegram ranks this channel #27 of 92 here — alongside 91 others — read 21 August 2026
openai_fan @backspace_media · 10 Telegram ranks this channel #30 of 95 here — alongside 94 others — read 25 August 2026
КиберХаб - IT и Нейросети @kyberhub · 60,729 Telegram ranks this channel #36 of 88 here — alongside 87 others — read 22 August 2026
PROAI @pro_ai_news · 89,977 Telegram ranks this channel #49 of 92 here — alongside 91 others — read 16 August 2026
NeuroADEPT @neuroadepts · 41,375 Telegram ranks this channel #63 of 85 here — alongside 84 others — read 29 August 2026
Айтишка - Digital & IT @ITtishka · 21,426 Telegram ranks this channel #78 of 88 here — alongside 87 others — read 23 September 2026
Stable Diffusion News | Нейросети @StableDiffusionBest · 32,596 Telegram ranks this channel #79 of 84 here — alongside 83 others — read 4 September 2026
This channel appears in 16 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 26 September 2026 — this
entry's latest reading, not the date you are reading this.
“Bard AI | Нейросети & IT” (@NeuralToday), 30,361 subscribers as measured 26 September 2026. Telegram Register, tgregister.com/channel/NeuralToday.
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.