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Channel

آکادمی هوش مصنوعی تورینگ

@TuringAcademyAI

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Posts edited after publishing · Polls · Citations · Handles named that no longer answer · Cite this entry

47,322subscribers

-609 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 31,623–100,000.

Register entry

Telegram ID-1002264579301
TypeChannel
Username@TuringAcademyAI
Descriptionجایی برای یادگیری کاربردهای هوش مصنوعی! وبسایت ما 👇🏻 https://turingai.ir اینستاگرام ما👇🏻 Instagram.com/turingacademy.ai ارتباط با ما: @TuringAcademyaiSupport
CreatedBetween 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live15 October 2026
Measurements held38
Confirmed unchanged1 time, most recently 15 October 2026
On Telegramt.me/TuringAcademyAI

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 9 September 2026 and assigned it the closest of 31 fixed categories, at 82% 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

47,32248,40747,864.57 August 2026 — 47,931 subscribers7 August 2026 — 47,931 subscribers8 August 2026 — 47,958 subscribers9 August 2026 — 48,002 subscribers10 August 2026 — 47,954 subscribers11 August 2026 — 47,905 subscribers12 August 2026 — 47,876 subscribers13 August 2026 — 47,899 subscribers14 August 2026 — 48,085 subscribers16 August 2026 — 48,130 subscribers17 August 2026 — 48,117 subscribers18 August 2026 — 48,111 subscribers19 August 2026 — 48,120 subscribers21 August 2026 — 48,156 subscribers22 August 2026 — 48,181 subscribers24 August 2026 — 48,190 subscribers25 August 2026 — 48,206 subscribers26 August 2026 — 48,212 subscribers27 August 2026 — 48,192 subscribers28 August 2026 — 48,172 subscribers30 August 2026 — 48,327 subscribers31 August 2026 — 48,387 subscribers1 September 2026 — 48,403 subscribers2 September 2026 — 48,407 subscribers3 September 2026 — 48,380 subscribers4 September 2026 — 48,383 subscribers8 September 2026 — 48,306 subscribers11 September 2026 — 48,261 subscribers13 September 2026 — 48,206 subscribers14 September 2026 — 48,248 subscribers16 September 2026 — 48,166 subscribers19 September 2026 — 48,083 subscribers26 September 2026 — 47,847 subscribers4 October 2026 — 47,685 subscribers8 October 2026 — 47,566 subscribers13 October 2026 — 47,397 subscribers14 October 2026 — 47,357 subscribers15 October 2026 — 47,322 subscribers7 August 202615 October 2026
38 measurements spanning 69 days, net -609. 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 47,159–48,570 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 38
Measured (UTC)SubscribersChange
15 Oct 2026, 13:4447,322-35
14 Oct 2026, 13:4647,357-40
13 Oct 2026, 05:3047,397-169
8 Oct 2026, 19:5447,566-119
4 Oct 2026, 11:3747,685-162
26 Sept 2026, 01:0047,847-236
19 Sept 2026, 08:3648,083-83
16 Sept 2026, 19:1648,166-82
14 Sept 2026, 19:3848,248+42
13 Sept 2026, 03:0148,206-55
11 Sept 2026, 02:5648,261-45
8 Sept 2026, 06:4048,306-77
4 Sept 2026, 23:2048,383+3
3 Sept 2026, 09:4848,380-27
2 Sept 2026, 03:5748,407+4
1 Sept 2026, 05:4448,403+16
31 Aug 2026, 03:4448,387+60
30 Aug 2026, 04:3648,327+155
28 Aug 2026, 07:1848,172-20
27 Aug 2026, 06:4448,192first reading

Engagement

470 posts held, back to 3 August 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 142 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
2.70%
avg views ÷ 47,322 subscribers
Avg views / post
1,280
119 posts measured
Reaction rate
0.485%
reactions ÷ views · ER floor
Posts in window
120
of 470 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. It is computed over the 110 of 119 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 15 October 2026
Posts held470 (3 August 2026 – 15 October 2026)
Views total152,244
Reactions total688
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken16 Oct 2026, 02:51 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
≈1,640
Videos
≈149
Links
≈1,010

Lifetime counters from Telegram’s own channel header, read 16 October 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
11m 08s
Average length
20s

Measured directly from 34 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

2,642 reactions across 449 posts, in 16 distinct kinds. The most used accounts for 68.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤1,79768.0%
👍29911.3%
🔥1806.81%
🤣1806.81%
👏622.35%
🤔311.17%
👎200.757%
⚡180.681%
😐160.606%
👀110.416%
😎80.303%
🆒70.265%
🤬50.189%
💯30.114%
🤯30.114%
🫡20.076%

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 450 of the 470 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 2,642 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 470 most recent posts we hold, published 3 August 2026 to 15 October 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
2
of 469 we hold a reading for · 0.4%
Most on one post
1
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @TuringAcademyAI. 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 470 most recent posts we hold for this entry, published 3 August 2026 to 15 October 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.

Recent posts

15 Oct 2026, 16:02 UTC497 viewsread 16 October 2026
Poll

شما کدومو انتخاب می‌کنید و نظرتون چیه؟ 🤔

  1. محتوای هوش مصنوعی کمتر ببینم 👎33%
  2. همین مقدار خوبه 👍10%
  3. محتوای هوش مصنوعی بیشتری ببینم ✊41%
  4. اصلاً مهم نیست هوش مصنوعی باشه یا نه؛ فقط با کیفیت باشه 😐37%

The shares total 121%, above 100: this poll accepts more than one answer per voter. No per-option vote count is published, so the number of voters who chose each option is not derivable and is not shown.

15 Oct 2026, 15:59 UTC498 views1 reactionsread 16 October 2026

یک بحث این روزهای شبکه‌های اجتماعی اینه که با زیاد شدن محتوای ساخته‌ شده با هوش مصنوعی، پلتفرم‌ها کم‌کم دارن روی چیزی که بهش میگن “AI Slop” یعنی محتوای هوش مصنوعی انبوه، تکراری و کم‌ کیفیت سخت‌گیرتر میشن. 👹 مثلا TikTok حتی داره ابزارهایی تست می‌کنه که کاربر بتونه تعیین کنه چقدر محتوای هوش مصنوعی توی فید خودش ببینه. بقیه شبکه های اجتماعی هم همینطور. حالا اگه همین قابلیت فردا روی اینستاگرام، یوتیوب و یا هر شبکه اجتماع…

🤔1

15 Oct 2026, 14:44 UTC565 views2 reactionsread 16 October 2026

⬜️ نمونه پرامپت آماده: Edit the uploaded image. CRITICAL PRESERVATION REQUIREMENT: Preserve exactly: [PRODUCT / SUBJECT] Preserve character-for-character: "[TEXT 1]" "[TEXT 2]" "[TEXT 3]" Also preserve: - spelling - numbers - capitalization - line breaks - text placement - typography proportions - layout - geometry - material - perspective ONLY change: [BACKGROUND / LIGHTING / ENVIRONMENT] Do NOT: - rewrite tex…

❤2

15 Oct 2026, 14:29 UTC490 views2 reactionsread 16 October 2026
Photo

حفظ دقیق متن در ویرایش تصویر اگر فقط به هوش مصنوعی بگیم «متن روی محصول رو تغییر نده» ممکنه جواب بده، ولی برای کار جدی، این دستور زیادی کلیه. اگر واقعاً براتون مهمه که نوشته‌ها، عددها، چیدمان و خود محصول دست‌ نخورده بمونن، بهتره پرامپت رو طوری بنویسید که دقیقاً مشخص باشه چه چیزی باید قفل بمونه و چه چیزی اجازه تغییر داره. برای این مدل ویرایش‌ها میتونید از یک ساختار خیلی ساده استفاده کنید. 😎 🔺 مواردی که باید قفل بشن …

❤2

15 Oct 2026, 12:34 UTC594 views5 reactionsread 16 October 2026
Photo

چقدر نتیجه تست دیشب یک‌ طرفه بود. 😂 تقریباً همه خروجی 🅰️ رو بیشتر پسندیدن و قبول داشتن. 😎 احتمالا هم بیشتر به خاطر کیفیت کار بوده چون خودمم اونو بیشتر به عنوان یک کار تبلیغاتی پسندیدم. حالا کدوم به کدوم بود؟! تصویر 🅰️ توسط Gemini ساخته شده بود و 🅱️ هم توسط GPT. 😁 اگر فقط رأی مخاطب یعنی شما رو ببینیم خب Gemini برنده واضح تست بوده. اما هدف اصلی این تست این بود ببینیم کدوم مدل می‌تونه محیط رو کاملاً عوض کنه ولی همزما…

❤5

14 Oct 2026, 15:59 UTC931 views10 reactionsread 16 October 2026
Photo

بریم سراغ تستمون 🧐 یک محصول غیر واقعی ساختیم که روی بسته‌بندیش چند نوشته مشخص وجود داره: NOVA BEAN ETHIOPIA LIGHT ROAST 250 g LOT 04-26 BREW SLOW بعد همون عکس مرجع محصول رو به GPT و Gemini دادیم. پرامپت هم دقیقاً یکسان بود. وظیفه مدل‌ها این بود که محصول رو هیچ تغییری ندن. تمام نوشته‌ها باید حرف‌ به‌ حرف همون باقی بمونن. فقط محیط عکس رو تبدیل کنن به یک Coffee Shop حرفه‌ای و تمیز. ✅ قوانین مثل همیشه مشخصه: • منبع یکسا…

🔥6❤4

14 Oct 2026, 13:57 UTC873 views6 reactionsread 16 October 2026
Photo

طبق رأی شما، باید بریم سراغ «حفظ دقیق متن و نوشته داخل ویرایش عکس» 😎 یک سؤال، چرا وقتی به هوش مصنوعی می‌گیم «فقط پس‌زمینه این محصول رو عوض کن» گاهی اسم برند، عددها، کلمات روی بسته‌بندی یا حتی شکل حروف هم تغییر می‌کنن؟ 🤔 چون خیلی از مدل‌های تصویرساز موقع ویرایش کردن، نوشته رو مثل فوتوشاپ همون پیکسل‌های قبلی نگه نمی‌دارن. تصویر رو دوباره میسازن! و برای مدل، نوشته روی محصول فقط «متن» نیست، در واقع یک الگوی بصریه. مثل…

❤5👎1

13 Oct 2026, 17:36 UTC≈1,020 viewsread 16 October 2026
Poll

شما انتخاب کنین. 😎 تست بعدی بریم سراغ کدوم تست؟

  1. حفظ دقیق متن و نوشته داخل ویرایش عکس32%
  2. تست پیروی از دستورات23%
  3. حذف یک شیء بدون خراب کردن بقیه تصویر24%
  4. ساخت تصویر از روی نمونه21%

Shares as published. No per-option vote count is published by Telegram, so none is shown.

13 Oct 2026, 17:33 UTC≈1,000 views3 reactionsread 16 October 2026

تست بعدی بریم سراغ کدوم تست؟ 🧐 🟡 حفظ دقیق متن و نوشته داخل ویرایش عکس مثلاً ببینیم موقع تغییر محیط، نوشته روی بسته‌بندی یا پوستر سالم می‌مونه یا نه. 🟡 تست پیروی از دستورات یک پرامپت سخت با چندین شرط به GPT و Gemini بدیم و ببینیم کدوم واقعاً دستورها رو دقیق‌تر اجرا می‌کنه. 🟡 حذف یک شیء بدون خراب کردن بقیه تصویر یک شیء رو حذف کنیم و ببینیم کدوم مدل پس‌زمینه، سایه‌ها و جزئیات اطراف رو طبیعی‌تر بازسازی می‌کنه. 🟡 ساخت…

❤3

13 Oct 2026, 16:32 UTC924 views8 reactionsread 16 October 2026
Photo

چطور بفهمیم چهره واقعاً ثابت مونده؟ وقتی چند عکس هوش مصنوعی از یک شخص می‌بینیم، معمولاً اولین قضاوتمون اینه «آره، شبیهشه.» ولی برای ساخت یک شخصیت ثابت، این معیار کافی نیست. دو نفر می‌تونن خیلی شبیه هم باشن، ولی هنوز دو نفر متفاوت باشن. اگر می‌خواید بفهمید هوش مصنوعی واقعاً ظاهر یک شخصیت رو حفظ کرده یا نه، بهتره صورت رو به چند بخش جدا بررسی کنید. من برای تست‌های تورینگ از این چهارچوب استفاده می‌کنم. ☕️ 🔺 چشم‌ها فقط…

❤7👍1

13 Oct 2026, 14:36 UTC892 views6 reactionsread 16 October 2026
Photo

وقت بررسی نتیجه تست دیشبه. 🧐 این بار به دو مدل دقیقاً یک عکس مرجع دادیم و ازشون خواستیم همون شخص رو در ۳ محیط کاملاً متفاوت قرار بدن ولی هویتش به هیچ عنوان تغییر نکنه. سه سناریو داشتیم شامل محیط کاری، خیابون بارونی و کافه. قوانین هم برای هر دو یکسان بود. • مرجع یکسان • پرامپت یکسان • بدون اصلاح خروجی • بدون انتخاب بهترین بین چند تولید عکس (همون انتخاب اول) تا اینجا هم رقابت از نظر شما نزدیکه بوده طبق ری‌اکت‌ها. و حا…

❤5👏1

12 Oct 2026, 15:31 UTC≈1,090 views16 reactionsread 16 October 2026

Posted without readable text

🔥8⚡6❤1👏1

Showing the 12 most recent of 470 posts we hold for @TuringAcademyAI. 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

@TuringAcademyAI edited 5 posts 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
9 August 2026
Most recent edit
5 October 2026

Polls

The 6 most recent of 13 polls we hold for this entry, as Telegram rendered them when we read the post. A poll’s figures keep moving after that, so each one is dated.

15 Oct 2026, 16:02 UTCAnonymous Poll49 voters

شما کدومو انتخاب می‌کنید و نظرتون چیه؟ 🤔

  1. محتوای هوش مصنوعی کمتر ببینم 👎33%
  2. همین مقدار خوبه 👍10%
  3. محتوای هوش مصنوعی بیشتری ببینم ✊41%
  4. اصلاً مهم نیست هوش مصنوعی باشه یا نه؛ فقط با کیفیت باشه 😐37%

The shares total 121%, above 100: this poll accepts more than one answer per voter. No per-option vote count is published, so the number of voters who chose each option is not derivable and is not shown.

13 Oct 2026, 17:36 UTCAnonymous Poll62 voters

شما انتخاب کنین. 😎 تست بعدی بریم سراغ کدوم تست؟

  1. حفظ دقیق متن و نوشته داخل ویرایش عکس32%
  2. تست پیروی از دستورات23%
  3. حذف یک شیء بدون خراب کردن بقیه تصویر24%
  4. ساخت تصویر از روی نمونه21%

Shares as published. No per-option vote count is published by Telegram, so none is shown.

11 Oct 2026, 18:03 UTCAnonymous Poll64 voters

مشابه پست امروز، دوست دارین چه موردی رو بررسی کنیم و تست کنیم با هم و در نهایت در موردش آموزش بذاریم؟! 🤔

  1. حفظ چهره یک شخص در چند محیط مختلف45%
  2. حفظ دقیق نوشته و جزئیات روی محصول16%
  3. یک پرامپت روی چند مدل ویدیوساز22%
  4. تغییر لباس بدون تغییر چهره و بدن17%

Shares as published. No per-option vote count is published by Telegram, so none is shown.

6 Oct 2026, 16:31 UTCAnonymous Poll122 voters

روی چه نوع Workflow دوست دارین کار کنیم؟! ✍️

  1. تولید و مدیریت محتوا70%
  2. پشتیبانی مشتری6%
  3. فروش و مدیریت Lead13%
  4. گزارش‌گیری و داده11%

Shares as published. No per-option vote count is published by Telegram, so none is shown.

4 Oct 2026, 15:05 UTCAnonymous Poll167 voters

کدام عکس یا عکس‌ها با هوش مصنوعی ساخته شده؟! 🤔

  1. 171%
  2. 226%
  3. 355%
  4. 464%

The shares total 216%, above 100: this poll accepts more than one answer per voter. No per-option vote count is published, so the number of voters who chose each option is not derivable and is not shown.

3 Oct 2026, 15:09 UTCAnonymous Poll61 voters

شما کدام خروجی به نظرتون مناسب‌تره و انتخابش میکنین؟! 🤔

  1. A70%
  2. B30%

Shares as published. No per-option vote count is published by Telegram, so none is shown.

Percentages only — there are no per-option vote counts here, because Telegram publishes none. The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.

The shares need not add up to 100. Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.

Read from the 470 most recent posts we hold, published 3 August 2026 to 15 October 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.

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 2 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.

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 15 October 2026 — this entry's latest reading, not the date you are reading this.

“آکادمی هوش مصنوعی تورینگ” (@TuringAcademyAI), 47,322 subscribers as measured 15 October 2026. Telegram Register, tgregister.com/channel/TuringAcademyAI.

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.