21 measurements spanning 22 days, net +141. 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 25,647–25,932 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 21
Measured (UTC)
Subscribers
Change
30 Aug 2026, 03:47
25,899
+19
29 Aug 2026, 02:28
25,880
+3
28 Aug 2026, 03:36
25,877
+26
27 Aug 2026, 00:53
25,851
+13
26 Aug 2026, 02:56
25,838
+17
24 Aug 2026, 23:57
25,821
+36
23 Aug 2026, 09:44
25,785
+12
21 Aug 2026, 23:37
25,773
-3
20 Aug 2026, 19:06
25,776
+6
19 Aug 2026, 18:26
25,770
+12
18 Aug 2026, 15:23
25,758
+7
17 Aug 2026, 18:08
25,751
+14
16 Aug 2026, 14:22
25,737
+12
14 Aug 2026, 23:08
25,725
+20
13 Aug 2026, 13:07
25,705
+25
12 Aug 2026, 09:43
25,680
-13
11 Aug 2026, 09:36
25,693
-25
10 Aug 2026, 08:01
25,718
-25
9 Aug 2026, 11:13
25,743
-15
7 Aug 2026, 19:30
25,758
first reading
Engagement
47 posts held, back to 26 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 48 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
16.6%
avg views ÷ 25,899 subscribers
Avg views / post
4,300
36 posts measured
Reaction rate
0.987%
reactions ÷ views · ER floor
Posts in window
39
of 47 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 30 August 2026
Posts held
47 (26 July 2026 – 30 August 2026)
Views total
154,863
Reactions total
1,529
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
30 Aug 2026, 08:46 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
254
Videos
55
Links
227
Lifetime counters from Telegram’s own channel header, read 30 August 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
10m 06s
Average length
55s
Measured directly from 11 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
1,827 reactions across 43 posts, in 27 distinct kinds. The most used accounts for 49.8% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
910
49.8%
🔥
218
11.9%
😢
116
6.35%
🙏
88
4.82%
❤🔥
82
4.49%
👍
81
4.43%
👌
69
3.78%
🏆
62
3.39%
👏
47
2.57%
😍
31
1.70%
🤩
23
1.26%
🎉
22
1.20%
🕊
16
0.876%
🥰
11
0.602%
💯
10
0.547%
🤯
10
0.547%
😁
6
0.328%
😱
5
0.274%
🫡
4
0.219%
⚡
3
0.164%
7 further kinds
13
0.712%
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 43 of the 47 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 1,827reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 47 most recent posts we hold, published 26 July 2026 to 30 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.
🤖 با این تیم ۸ نفره هوش مصنوعی، به آینده سلام کن ! 👋🏼
⚠️ این ابزار یه مقدار با AIهای معمولی فرق داره
📌 توی Atoms به جای اینکه فقط با یک چتبات طرف باشی، یه تیم از ۸ ایجنت تخصصی داری که هرکدوم مسئول یه بخش از پروژهات هستن:
👨💼 Mike | رهبر تیم
کارها رو بین بقیه ایجنتها تقسیم میکنه، مراحل پروژه رو هماهنگ میکنه و کل تیم رو جلو میبره.
📋 Emma | مدیر محصول
ایدهات رو بررسی میکنه، نیازهای پروژه رو مشخص میکنه و اون رو…
🔥 این یکی از خفنترین ابزارهای گوگله که برای ساخت و ادیت ویدئو دیدم!
تصور کن فقط یک عکس یا یک ویدئوی ساده از خودت داشته باشی و بعد با چند خط پرامپت:
🎬 ویدئوت رو حرفهای ادیت کنی
🎙 از یک عکس، آواتار سخنگوی فارسی بسازی
✨ متن، افکت و المانهای سهبعدی به ویدئو اضافه کنی
🎭 خودت رو به استایلهای مختلف تبدیل کنی
🎥 و حتی فقط با دادن یک قصه، استوریبرد کامل یک فیلم سینمایی بسازی!
🌟همه این کارها رو بصورت کاملا رایگان داخل G…
🌟رفقا، این پست پیش درآمد ویدئوی آموزش Gemini Omni هستش که طبق روال همیشه، فایل های پرامپت و لینک دسترسی رو براتون داخلش قرار دادم✅
🔗دسترسی مستقیم به گوگل لَبز : https://labs.google/fx/tools/flow
📌لینک ویدئو هم تا چند دقیقه دیگه همینجا باهاتون به اشتراک میذارم تا توی چند دقیقه بفهمید این ابزار چقدر خفنه... امیدوارم لذت ببرید 🤩
درود رفقا 👋🏼 کیا میدونن وایب کدینگ (Vibe Coding) و وایب پرامپتینگ (Vibe Prompting) چیه❓
📌 اگر نمیدونین، یعنی بهجای اینکه خودت بشینی خطبهخط کد یا پرامپت حرفه ای بنویسی، با کمک هوش مصنوعی چیزی که میخوای رو با زبان طبیعی خودت توضیح بدی و بذاری AI برات اون کاراو انجام بده 🤖
💢مثلاً میگی:
▫️یه سایت فروشگاهی بساز که ورود کاربر، سبد خرید و درگاه پرداخت داشته باشه.
▫️یا برای این عکس یه پرامپت بنویس که کاراکتر داخلش این …
🌟 ویدئوی معرفی خلاقانه باحالی هم براش ساختن😍
اگه دوست داری بدونی این غول کوچولوی اپل چقدر خفنه! این ویدئو رو ازدست نده 🌟
👈🏼 تجربه سه ماهه من با مک مینی - غول کوچولوی اپل
#macminim6 #macminim5pro #macmini
رفقاااا!!! خبر داغ از اپل اومده! 🍏🔥
اپل بالاخره بعد از✌🏼سال انتظار مکمینی جدید رو رونمایی کرد اونم با تراشههای M6 و M5 Pro.
طراحی همون کوچولوی دوستداشتنی قبلیه، ولی قدرت و هوش مصنوعیش دیگه حرفی باقی نمیذاره! 🤩
📌مدل پایه با پردازنده M6 (اولین تراشه ۲ نانومتری اپل) عرضه شده؛ ۱۲ هسته CPU و ۱۲ هسته GPU.
اپل میگه سریعترین عملکرد تکرشتهای دنیارو داره و نسبت به M4 تا ۴۰٪ قویتره.💥 پردازنده گرافیکیشم با شتابدهندهه…
🦁 استیکرساز ChatGPT از راه رسید؛ با خروجی برای واتساپ و آیمسیج!
🔥 حالا دیگه میتونید عکسها، ایدهها یا حتی شوخیهای شخصی خودتونو به پک استیکر اختصاصی تبدیل کنید.
📌این استیکرها با پسزمینه شفاف ساخته میشن و میتونید ازشون توی واتساپ و آیمسیج استفاده کنید.
✅مراحل ساخت پک استیکر با ChatGPT
1️⃣وارد ChatGPT بشید و از منوی کناری، بخش Images و بعد Stickers رو انتخاب کنید.
2️⃣اول سبک پک استیکر را مشخص کنید.
3️⃣در مر…
🌟 کدوم هوش مصنوعی ویدیو ساز بهتر فارسی صحبت میکنه؟
📌 من توی یه تست، چندتا مدل هوش مصنوعی از نظر توانایی صحبت کردن به زبان فارسی رو با هم مقایسه کردم
🔄 رتبهبندی نهایی تست:
1️⃣ Omni Flash
2️⃣ Grok
3️⃣ Flux
4️⃣ H3
5️⃣ Veo
✅ بله، فعلا Omni Flash از نظر من که ویدئوهای زیادی با هوش مصنوعی ساختم، بهترین تلفظ و لیپسینک رو برای زبان فارسی داره.
💫 خیلی از شما هم ازم خواسته بودین آموزش ساخت ویدئو با زبان فارس، استفاده از …
🚨 الان بیشتر مدلهای دنیا وارد «منطقه کشتار DeepSeek» شدن❗️
🤔 حالا این یعنی چی؟!
💢شاید فکر کنید چون DeepSeek رایگان، اوپن سورس و محصول چینه; پس دیگه کسی سمتش نمیره!
اما بلعکس ، همین رایگان بودنه تونسته کلی از مدل های دیگه رو به دردسر بندازه!
🌟 اصطلاح DeepSeek Kill Zone به مدل هایی اشاره داره که نه از DeepSeek قوی ترن، نه ارزون تر!
یعنی کاربر وقتی میتونه رایگان یا با هزینه خیلی ناچیز نتیجه مشابه بگیره، چرا باید سراغ…
🚨 واقعیت تلخ یا فرصت بزرگ؟ هوش مصنوعی داره جای خیلی از شغلها رو میگیره...
▪️تا همین چند سال پیش برای طراحی پوستر، دوبله، تولید محتوا ، ادیت ویدئو، ساختن تیزر تبلیغاتی یا حتی نوشتن کد، حتماً به نیروی انسانی نیاز بود؛ اما امروز هوش مصنوعی بخش زیادی از این کارها رو در چند دقیقه انجام میده.
⚠️ الان بیشترین تأثیر رو روی این حوزهها گذاشته:
🔹 گرافیستها (برای طراحیهای ساده و تبلیغاتی)
🔸 دوبلورها و گویندهها (با مدل…
❤26🏆8🔥6👏1
Showing the 12 most recent of 47 posts we hold for @samiotech. 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
@samiotech 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
29 August 2026
Most recent edit
29 August 2026
Mentions
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.
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 30 August 2026 — this
entry's latest reading, not the date you are reading this.
“SAMIOTECH | تازههای تکنولوژی و هوش مصنوعی” (@samiotech), 25,899 subscribers as measured 30 August 2026. Telegram Register, tgregister.com/channel/samiotech.
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.