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Channel

Algotic Ai

@algoticlab

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

7,241subscribers

+1,051 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1003788627240
TypeChannel
Username@algoticlab
Descriptionاینجا در مورد هوش مصنوعی و کاربردش در تولید محصولات و ابزارهای واقعی حرف میزنیم سیستم ترجمه تخصصی و تولید زیرنویس فارسی برای ویدیوهای یوتوب Tubyapp.com/fa
CreatedBetween 1 February 2026 and 27 July 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live10 November 2026
Measurements held26
Confirmed unchanged1 time, most recently 10 November 2026
On Telegramt.me/algoticlab

Topic

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 12 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 the other topics.

Growth

6,1907,2416,715.56 August 2026 — 6,190 subscribers6 August 2026 — 6,261 subscribers9 August 2026 — 6,445 subscribers12 August 2026 — 6,547 subscribers16 August 2026 — 6,589 subscribers18 August 2026 — 6,612 subscribers22 August 2026 — 6,643 subscribers25 August 2026 — 6,670 subscribers27 August 2026 — 6,690 subscribers31 August 2026 — 6,756 subscribers3 September 2026 — 6,826 subscribers8 September 2026 — 6,847 subscribers12 September 2026 — 6,873 subscribers15 September 2026 — 6,878 subscribers19 September 2026 — 6,942 subscribers30 September 2026 — 7,018 subscribers6 October 2026 — 7,045 subscribers13 October 2026 — 7,137 subscribers15 October 2026 — 7,140 subscribers18 October 2026 — 7,152 subscribers22 October 2026 — 7,159 subscribers25 October 2026 — 7,167 subscribers28 October 2026 — 7,180 subscribers3 November 2026 — 7,221 subscribers6 November 2026 — 7,235 subscribers10 November 2026 — 7,241 subscribers6 August 202610 November 2026
26 measurements spanning 96 days, net +1,051. 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 6,032–7,399 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 26
Measured (UTC)SubscribersChange
10 Nov 2026, 01:507,241+6
6 Nov 2026, 06:557,235+14
3 Nov 2026, 06:267,221+41
28 Oct 2026, 11:587,180+13
25 Oct 2026, 02:077,167+8
22 Oct 2026, 01:357,159+7
18 Oct 2026, 13:217,152+12
15 Oct 2026, 19:487,140+3
13 Oct 2026, 04:367,137+92
6 Oct 2026, 21:177,045+27
30 Sept 2026, 05:007,018+76
19 Sept 2026, 17:586,942+64
15 Sept 2026, 13:206,878+5
12 Sept 2026, 03:416,873+26
8 Sept 2026, 06:006,847+21
3 Sept 2026, 04:186,826+70
31 Aug 2026, 00:456,756+66
27 Aug 2026, 23:556,690+20
25 Aug 2026, 09:186,670+27
22 Aug 2026, 08:166,643first reading

Engagement

61 posts held, back to 27 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 26 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
37.3%
avg views ÷ 7,241 subscribers
Avg views / post
2,700
16 posts measured
Reaction rate
0.502%
reactions ÷ views · ER floor
Posts in window
16
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
WindowRolling 30 days · latest post in window 8 November 2026
Posts held61 (27 July 2026 – 8 November 2026)
Views total43,220
Reactions total217
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken11 Nov 2026, 02:47 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
30
Videos
198
Links
184

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
29h 27m
Average length
38m 25s

Measured directly from 46 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

982 reactions across 60 posts, in 16 distinct kinds. The most used accounts for 61.5% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤60461.5%
👍21722.1%
🔥434.38%
🙏262.65%
😭222.24%
🤣222.24%
👏181.83%
😁70.713%
👎50.509%
😍40.407%
😢40.407%
🍾30.305%
🐳20.204%
💯20.204%
🥰20.204%
💅10.102%

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 61 of the 61 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 1,033 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 61 most recent posts we hold, published 27 July 2026 to 8 November 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.

Recent posts

Telegram’s own ‘edited’ marker: 3 of 16 posts held from the last 30 days (18.8%) 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).

8 Nov 2026, 13:27 UTC≈1,310 views12 reactionsread 11 November 2026
Photo

اینجا هم دیدم چند تا مدل خوب رو داره رایگان ارایه میده تا بیستم نوامبر ۲۰۲۶ Qwen 3.8 Max DeepSeek V4.1 flash GLM 5.3 flash Perchai.app

❤9👍3

7 Nov 2026, 17:33 UTC≈1,500 views11 reactionsread 11 November 2026
Video

🚀 کاراکتر ثابت در همه تصاویر با سه اسکیل رایگان Gemini [با زیرنویس اختصاصی فارسی] 🔻 سرفصل‌های کلیدی ویدیو: 🔹 افزونه (Character Creator): ساخت طراحی ساده کاراکتر در ۳۵ سبک هنری 🔹 افزونه (Character Sheet): شیت مدل با نمای جلو، پهلو، پشت و سه حالت چهره 🔹 افزونه (Same Character): قرار دادن همان کاراکتر در هر صحنه تازه 🔹 ترفند (Fixes): رفع متن ناخواسته روی شیت و برگشتن جزئیات لباس لینک دانلود اسکیل‌های مطرح شده در این و…

❤8👍3

5 Nov 2026, 08:22 UTC≈2,870 views33 reactionsread 11 November 2026

متاسفانه امروز در X پست‌های زیادی دیدم از کاربران ایرانی که حساب کلادشون بسته شده بود. علیرغم همه نکات امنیتی که رعایت کرده بودند این اتفاق افتاده و هیچ راه دسترسی به پروژه‌ها و سوابق کارشون ندارند. اگر شما هم داخل ایران هستید و از کلاد استفاده میکنید، در اولین فرصت بکاپ بگیرید و به راه جایگزین فکر کنید.

😭22❤7😢3👏1

1 Nov 2026, 09:08 UTC≈3,720 views13 reactionsread 11 November 2026
Video

🚀 جایگزین متن‌باز کلاد دیزاین (Open Design) [با زیرنویس اختصاصی فارسی] این ویدیو به معرفی ابزار متن‌باز و رایگان Open Design می‌پردازد که به عنوان جایگزینی برای Claude Design عمل می‌کند. سازنده ویدیو توضیح می‌دهد که چگونه این ابزار به کاربران اجازه می‌دهد بدون محدودیت‌های نرم‌افزارهای تجاری، از مدل‌های هوش مصنوعی، کدهای مختلف و سیستم‌های طراحی متنوع برای ساخت وب‌سایت، تصاویر و حتی فایل‌های صوتی استفاده کنند. در واقع…

❤9👍4

27 Oct 2026, 09:31 UTC≈3,810 views12 reactionsread 11 November 2026
Video

🚀 راه‌های رسیدن به ۱۲۸ گیگابایت VRAM برای هوش مصنوعی لوکال [با زیرنویس اختصاصی فارسی] این ویدیو به بررسی روش‌های مختلف برای داشتن ۱۲۸ گیگابایت حافظه گرافیکی (VRAM) جهت اجرای مدل‌های هوش مصنوعی قدرتمند در خانه می‌پردازد. در واقع، این محتوا توضیح می‌دهد که چرا داشتن این مقدار حافظه به یک استاندارد برای اجرای مدل‌های محبوبی مثل Qwen 3.8 Flash-Next تبدیل شده و با تحلیل گزینه‌های گران‌قیمت مانند سیستم‌های مک، کارت‌های گر…

👍6❤5🔥1

24 Oct 2026, 12:22 UTC≈3,280 views6 reactionsread 11 November 2026
Video

🚀 روز بی‌سابقه هک در تاریخ نرم‌افزار [با زیرنویس اختصاصی فارسی] هوش مصنوعی و ابزارهای مدرن به هکرها کمک می‌کنن تا آسیب‌پذیری‌های خطرناک رو در پروژه‌های open-source پیدا کنن و حملات واقعی اجرا کنن. در این ویدیو با یک روز تاریخی آشنا می‌شی که چندین پروژه مهم مثل PHP، Node.js و GitLab با CVE مواجه شدن و همزمان سرویس‌هایی مثل Railway مورد حمله قرار گرفتن. یاد می‌گیری چرا حملات واقعی نگران‌کننده‌تر از افشای CVE هستن و NS…

👍6

24 Oct 2026, 12:17 UTC≈2,740 views9 reactionsread 11 November 2026
Video

🚀 ۷ کاربرد هوش مصنوعی برای بهبود زندگی دیجیتال [با زیرنویس اختصاصی فارسی] این ویدیو به شما یاد می‌دهد که چطور به جای اینکه اجازه دهید هوش مصنوعی فقط محتوای بی‌کیفیت و «زباله» تولید کند، از آن به عنوان ابزاری قدرتمند برای حذف شلوغی‌ها و اضافات زندگی دیجیتالتان استفاده کنید. شما یاد می‌گیرید که چگونه با کمک هوش مصنوعی، نرم‌افزارهای تلویزیون یا دستگاه‌های هوشمندتان را شخصی‌سازی کنید، فیدهای شبکه‌های اجتماعی و ایمیل‌های…

❤6🔥2👍1

23 Oct 2026, 21:00 UTC≈2,640 views7 reactionsread 11 November 2026

این لینک دعوت به گروه چت Algotic هست که برای تبادل نظر و مطرح کردن سوالات مرتبط با موضوع کاناله. در این مدت هم دوستان خوبی کنارمون بودند که تجربه‌شون رو با بقیه به اشتراک گذاشتند و ازشون ممنونم. https://t.me/+BY0JdP-drs1jNjc0

❤7

23 Oct 2026, 20:53 UTC≈2,300 views7 reactionsread 11 November 2026

لینک‌ اسکیل‌های مطرح شده در ویدیو بالا: 1. GitNexus: https://github.com/abhigyanpatwari/GitNexus 2. Matt Pocock Skills: https://github.com/mattpocock/skills 3. UI UX Pro Max: https://github.com/nextlevelbuilder/ui-ux-pro-max-skill 4. claude-mem: https://github.com/thedotmack/claude-mem 5. ECC (Everything Claude Code): https://github.com/affaan-m/ECC 6. Caveman: https://github.com/J…

❤7

23 Oct 2026, 20:51 UTC≈1,960 views12 reactionsread 11 November 2026
Video

🚀 ۶ اسکیل OpenCode 2.0 که ورک‌فلو ‌هارو تا ۱۰ برابر بهینه می‌کنن [با زیرنویس اختصاصی فارسی] شش اسکیل اوپن‌سورس برای اوپن‌کد ۲.۰ معرفی شده که می‌تونه ورک‌فلو برنامه‌نویسی رو به شکل قابل توجهی بهتر کنه. این اسکیل‌ها گراف دانش کدبیس، مهارت‌های مهندسی ساختاریافته، سیستم طراحی، حافظه پایدار و فشرده‌سازی توکن رو به اوپن‌کد اضافه می‌کنن. همه این ابزارها رایگان و متن‌باز هستن و شامل پروژه‌هایی مثل GitNexus، claude-mem و Ca…

❤9👍3

23 Oct 2026, 16:32 UTC≈2,130 views9 reactionsread 11 November 2026
Video

🚀 ۵ مرحله ساخت درام کوتاه داستانی با هوش مصنوعی [با زیرنویس اختصاصی فارسی] توی این ویدیو یاد می‌گیری چطوری با استفاده از هوش مصنوعی، ویدیوهای داستانی و درام بسازی که اونقدر واقعی به نظر می‌رسن که انگار سکانسی از یه فیلم سینمایی هستن. بهت یاد می‌ده چطور یه داستان جذاب و پرکشش بنویسی، شخصیت‌های ثابت و باکیفیت طراحی کنی و در نهایت با ابزارهای معرفی شده، صحنه به صحنه ویدیو رو تولید کنی. علاوه بر این، چند تا راهکار عملی …

❤6👍3

23 Oct 2026, 13:54 UTC≈2,060 views24 reactionsread 11 November 2026

دوستان میتونید از مدل توانمند DeepSeek V4.1 flash به رایگان روی OpenCode استفاده کنید

🔥18🤣3🐳2🥰1

Showing the 12 most recent of 61 posts we hold for @algoticlab. 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.

Forward network

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 7 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.

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 10 November 2026 — this entry's latest reading, not the date you are reading this.

“Algotic Ai” (@algoticlab), 7,241 subscribers as measured 10 November 2026. Telegram Register, tgregister.com/channel/algoticlab.

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.