Channel
@sinthesium
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
111subscribers
+1 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1003604936350 |
|---|---|
| Type | Channel |
| Username | @sinthesium |
| Created | Between 1 December 2025 and 31 May 2026— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 9 August 2026 |
| Last confirmed live | 13 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 13 August 2026 |
| On Telegram | t.me/sinthesium |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 13 Aug 2026, 05:16 | 111 | +1 |
| 9 Aug 2026, 07:16 | 110 | no change |
| 6 Aug 2026, 05:36 | 110 | first reading |
12 posts held, back to 2 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 1 pageof Telegram’s post history, 20 posts per page.
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 6 of 7 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 6 August 2026 |
|---|---|
| Posts held | 12 (2 July 2026 – 6 August 2026) |
| Views total | 587 |
| Reactions total | 22 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 9 Aug 2026, 07:16 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.
30 reactions across 9 posts, in 3 distinct kinds. The most used accounts for 60.0% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🔥 | 18 | 60.0% | |
| 👍 | 11 | 36.7% | |
| ❤ | 1 | 3.33% |
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 9 of the 12 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 30reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 12 most recent posts we hold, published 2 July 2026 to 6 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.
Магия, которую никто не программировал Модель учили одному: угадывать следующее слово. Это единственное, что было заложено в задачу напрямую. Смысл разложился в пространстве в виде близких и далёких точек сам, как побочный эффект — этого никто отдельно не программировал. Модель не видела кота глазами и не знает, что такое мурлыканье в человеческом смысле. Но геометрически точка «кот» оказалась в нужном месте, рядом …
👍3
Вначале лепка, потом — 3D-печать Компания Unbound создала интересный и уникальный инструмент под названием Loop: скульптинг объёмных SDF-форм с ИИ. На этапе грубой концепции пользователь размещает в пространстве примитивы, задавая их форму, размер и положение, а ИИ сразу достраивает вылепленную заготовку до нужного уровня реализма — добавляет цвет, детали и материал. Вместо полигональной сетки, привычной 3D-художни…
🔥5
Как слова находят своих соседей До обучения таблица весов заполнена случайными числами. У слова «кот» в этот момент нет ничего общего со словом «собака», как и вообще ни с чем: связи между точками ещё не существует. Модель в таком состоянии не умеет ничего. Дальше берут гигантский объём текста — книги, статьи, форумы, значительную часть открытого интернета — и подают его модели маленькими кусками, прося угадать сле…
🔥4👍2
Куда вкладывают слово Таблица весов устроена как гигантская сетка: строк в ней столько же, сколько токенов в словаре (порядка 100 тысяч), а столбцов у типичной крупной модели — от нескольких сотен до нескольких тысяч, в зависимости от размера. Каждому токену соответствует своя строка чисел. Такой набор называют вектором, или эмбеддингом — от английского embedding, «вложение»: слово буквально вкладывается в числовое …
👍2
Posted without readable text
Как модель понимает слово «кот», ни разу его не увидев Файл с весами модели Claude занимает несколько сотен гигабайт, у моделей поменьше — десятки. Это не JSON и не Excel, а плотно упакованные друг за другом миллиарды чисел с плавающей точкой. Их называют весами, или параметрами. Рядом с этим файлом лежит программа на Python, обычно пара тысяч строк кода, и умеет она ровно одно: брать числа из файла, перемножать и с…
👍2🔥2
Где ИИ на самом деле теряет деньги Дефицит памяти и рост цен на жёсткие диски — заметный, но верхнеуровневый симптом. Реальная инженерная проблема глубже: стоимость обработки запроса у языковых моделей растёт не линейно с объёмом текста, а квадратично. Это конкретный механизм, а не абстракция. Современные языковые модели при обработке текста сопоставляют каждое слово со всеми остальными словами во входном фрагменте …
🔥2
Как проходит твой суббота, друг?🤓
Posted without readable text
Как утилита для сжатия файлов случайно стала сердцем GPT Метод, которым сегодня режут текст на токены все крупные модели (GPT, Claude, Gemini), придумал программист из Колорадо-Спрингс Филип Гейдж. Еще в феврале 1994 года он опубликовал в журнале статью «Новый алгоритм для сжатия данных». Задача была бытовой: как сжать файл на диске. Предложенное им решение состояло в поиске в файле самой частой пары байтов и замене…
👍2🔥1
За что на самом деле платят нейросети Внутри компьютера нет ни одной буквы — только числа. Процессор — это набор транзисторов, и у каждого два состояния: 0 и 1, и буквы туда просто не помещаются. Поэтому ещё до того, как текст попадает в модель, стандарт UTF-8 переводит каждый символ в число. Например, слово cat (кот) превращается в три байта — 99, 97, 116. Работать с текстом побайтово моделям невыгодно: страниц ми…
🔥2❤1
Октябрь в Шэньчжэне или какими должны быть аддитивные технологии, чтобы не бравировать, а извлекать пользу для рентабельного производства Клуб производственников Сколково собирает группу для бизнес-экспедиции по аддитивным технологиям — на заводы и выставку TCT Shenzhen. В нынешнем формате клуб проводит такую поездку второй год подряд. Экспедиция пройдёт 12–18 октября 2026 года. В маршрут входят Шанхай, Сучжоу и Шэ…
🔥2
Showing the 12 most recent of 12 posts we hold for @sinthesium. 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 — 18,327 of 1,350,102entries 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.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Republishes
Channels on the register whose posts this channel has forwarded.
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.
Named by 3 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.
Names
Channels on the register whose handles appear in this channel's posts.
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.
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 13 August 2026 — this entry's latest reading, not the date you are reading this.
“Синтезиум AI” (@sinthesium), 111 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/sinthesium.
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.