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Telegram profile photo for Reza Jafari

Channel

Reza Jafari

@reza_jafari_ai

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Citations · Telegram's recommendations · Cite this entry

8,771subscribers

+1,097 since we began measuring on 7 August 2026

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

Register entry

Telegram ID-1001962709179
TypeChannel
Username@reza_jafari_ai
CreatedBetween 1 April 2023 and 31 October 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live16 September 2026
Measurements held14
Confirmed unchanged1 time, most recently 16 September 2026
On Telegramt.me/reza_jafari_ai

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 11 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

7,6738,7748,223.57 August 2026 — 7,674 subscribers7 August 2026 — 7,674 subscribers8 August 2026 — 7,673 subscribers11 August 2026 — 8,414 subscribers15 August 2026 — 8,495 subscribers18 August 2026 — 8,591 subscribers21 August 2026 — 8,624 subscribers24 August 2026 — 8,650 subscribers27 August 2026 — 8,671 subscribers30 August 2026 — 8,678 subscribers3 September 2026 — 8,773 subscribers8 September 2026 — 8,774 subscribers12 September 2026 — 8,770 subscribers16 September 2026 — 8,771 subscribers8,7717 August 202616 September 2026
14 measurements spanning 40 days, net +1,097. 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 7,508–8,939 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
16 Sept 2026, 02:388,771+1
12 Sept 2026, 17:208,770-4
8 Sept 2026, 23:008,774+1
3 Sept 2026, 16:018,773+95
30 Aug 2026, 23:078,678+7
27 Aug 2026, 15:028,671+21
24 Aug 2026, 15:478,650+26
21 Aug 2026, 09:278,624+33
18 Aug 2026, 10:228,591+96
15 Aug 2026, 03:178,495+81
11 Aug 2026, 19:358,414+741
8 Aug 2026, 09:337,673-1
7 Aug 2026, 14:317,674no change
7 Aug 2026, 14:257,674first reading

Engagement

46 posts held, back to 29 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 23 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
22.1%
avg views ÷ 8,771 subscribers
Avg views / post
1,940
7 posts measured
Reaction rate
1.56%
reactions ÷ views · ER floor
Posts in window
7
of 46 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 28 August 2026
Posts held46 (29 July 202628 August 2026)
Views total13,571
Reactions total212
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken28 Aug 2026, 16:37 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

Video runtime
1m 32s
Average length
46s

Measured directly from 2 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

1,620 reactions across 46 posts, in 4 distinct kinds. The most used accounts for 50.1% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
81150.1%
👍46628.8%
🔥30218.6%
🤣412.53%

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 46 of the 46 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 1,620 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 46 most recent posts we hold, published 29 July 2026 to 28 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.

Telegram Stars

Stars received
12
across the posts below
Posts paid on
5
of 46 we hold a reading for · 11%
Most on one post
5
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @reza_jafari_ai. 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 46 most recent posts we hold for this entry, published 29 July 2026 to 28 August 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

28 Aug 2026, 12:22 UTC911 views22 reactionsread 28 August 2026
Video

این ربات بامزه‌ای که می‌بینید اسمش Microduckـه یه ربات دوپای کوچیک و ۲۵ سانتیه که ۳۹۹ دلار قیمت داره و می‌تونید خودتون با استفاده از Reinforcement Learning مهارت‌های جدید بهش یاد بدید؛ از راه رفتن و نشستن گرفته تا برداشتن وسایل و حتی بلند شدن بعد از زمین خوردن! جالب‌تر اینکه این ربات توی ۲۴ ساعت اول حدود ۲.۶ میلیون دلار فروش داشته! پشت این پروژه هم Thomas Wolf، هم‌بنیان‌گذار HuggingFace قرار داره. 👑 توضیحات در

20👍2

28 Aug 2026, 04:15 UTC≈1,250 views17 reactionsread 28 August 2026
Photo

این ارزیابی از Composio هم خیلی جالب بوده. خلاصه بخوام بهتون بگم، ۵ تا از مدل‌های خوب open-weight رو روی ۳۰ تا تسک چندمرحله‌ای بررسی کردن. نتیجه اینه که GLM 5.3 بیشترین تسک رو با موفقیت انجام داده، اما DeepSeek V4 Flash هم سریع‌ترین بوده و هم کم‌هزینه‌ترین. از طرف دیگه، GLM 5.3 Flash به‌نظر می‌رسه بهترین تعادل رو داشته؛ فقط ۱ تسک کمتر از GLM 5.3 حل کرده، ولی هزینه‌ی هر تسک موفق براش حدود یک‌چهارم بوده. نکته‌ی جالب

👍86🔥3

27 Aug 2026, 19:24 UTC≈1,580 views69 reactionsread 28 August 2026
Photo

اگه این دوره‌ای که اینجا معرفی کردم رو دیده باشید، احتمالاً اسم Azalia Mirhoseini براتون آشناست؛ یه استاد و پژوهشگر ایرانی که حالا طبق انتخاب مجله TIME، جزو ۱۰۰ نفر تأثیرگذار دنیا در حوزه هوش مصنوعی قرار گرفته. آزالیا میرحسینی سال‌هاست روی استفاده از هوش مصنوعی برای طراحی چیپ و تراشه کار می‌کنه و در حال حاضر یکی از بنیان‌گذاران شرکت Ricursive Intelligence هم هست. نکته جالب اینه که قبلاً هم در گوگل روی استفاده از AI

60👍9

26 Aug 2026, 10:34 UTC≈2,100 views60 reactionsread 28 August 2026
Photo

کلاس درس دیتا با یک فیلم سینمایی به‌تازگی فیلم Pressure (2026) رو دیدم و واقعاً باید بگم به نظرم می‌تونه برای هر کسی که با داده، تحلیل و تصمیم‌گیری سروکار داره، یه کلاس درس کامل باشه. فیلم در ظاهر درباره‌ی ۷۲ ساعت قبل از D-Day و پیش‌بینی وضعیت آب‌وهواست؛ ولی در واقع خیلی بیشتر از این حرف‌هاست. درباره‌ی اینه که وقتی با داده‌های ناقص، متناقض و کلی عدم‌قطعیت روبه‌رو هستیم و زمان هم نداریم، چطور باید تصمیم بگیریم. از

45👍11🔥4

25 Aug 2026, 17:46 UTC≈2,110 views24 reactionsread 28 August 2026

اگر بخوام سه مدل Wan 3، MiniMax H3 و Seedance 2.5، که جزو جدیدترین مدل‌های تولید ویدیو هستن، رو با هم مقایسه کنم، باید بگم در تولید خروجی‌های رئال و واقع‌گرایانه (Realistic)، مدل Seedance 2.5 عملاً به سطحی رسیده که تشخیص خروجی اون از ویدیوی واقعی نزدیک به غیرممکنه. @rzdjafari

18🔥6

24 Aug 2026, 19:28 UTC≈2,630 views6 reactionsread 28 August 2026

از دوستان اگر کسی هست که میتونه در تهیه زیرساخت ابری گرافیکی کمک و راهنمایی کنه ممنون میشم به آیدی زیر بهم پیام بده @rzdjafari

4👍2

24 Aug 2026, 18:57 UTC≈2,990 views14 reactionsread 28 August 2026
Photo

هفته رایگان DataCamp دوباره شروع شده! از امروز تا 8 شهریور فرصت دارید به همه دوره‌های این پلتفرم به‌صورت کامل و رایگان دسترسی داشته باشید. می‌تونید توی این مدت مهارتی که دنبالش بودید رو یاد بگیرید و حتی مدرکش رو هم بگیرید. اگه به فکر یادگیری هستید، این یه فرصت عالیه که نباید از دستش بدید! 🔗 لینک سایت DataCamp 👑 توضیحات در مورد دوره منتورینگ 🏆 نحوه ثبت‌نام در دوره منتورینگ 🤝 تجارب موفق قبلی بچه‌ها از منتورینگ

7👍4🔥3

24 Aug 2026, 14:42 UTC≈2,520 views11 reactionsread 28 August 2026
Photo

چقدر به هوش مصنوعی اختیار بدیم؟ یکی از چیزهایی که توی طراحی تجربه کاربری برای Agentهای هوشمند خیلی مهمه، اینه که مشخص کنیم هوش مصنوعی چقدر اجازه داره خودش تصمیم بگیره و عمل کنه. مفهوم Autonomy Slider دقیقاً برای همین موضوعه؛ یعنی کاربر بتونه میزان اختیار Agent رو بر اساس شرایط، میزان اعتمادش و حساسیت کاری که داره تنظیم کنه. در یک طرف، کنترل کامل دست کاربره و در طرف دیگه، Agent می‌تونه کارها رو تقریباً به‌صورت مستقل

9🔥2

23 Aug 2026, 17:48 UTC≈2,520 views42 reactionsread 28 August 2026
Video

وقتی ترم 1 مهندسی مکانیک درس زبان عمومی ارائه در مورد هوش مصنوعی بهم افتاد :) @reza_jafari_ai

🤣41👍1

23 Aug 2026, 08:25 UTC≈2,790 views14 reactionsread 28 August 2026
Photo

پشت پرده‌ی ایجنت‌ها: ۶۰ الگوی معماری که همه‌جا تکرار می‌شن بیشتر آموزش‌های مربوط به ایجنت‌ها بر اساس حوزه دسته‌بندی شدن؛ مثلاً سلامت و درمان، مالی و غیره، انگار که ایجنت‌ها در پشت‌صحنه واقعاً با هم فرق دارن. ولی Vahe توی این کتاب کامل می‌گه این برداشت گمراه‌کننده‌ست: اگه پرامپت‌ها رو کنار بذاری، می‌بینی تقریباً همه‌ی ایجنت‌ها از همون چند الگوی معماری مشخص استفاده می‌کنن. اون ۶۰ تا از این الگوها رو در ۸ قابلیت مختل

9🔥3👍2

23 Aug 2026, 03:52 UTC≈2,670 views43 reactionsread 28 August 2026
Photo

بهترین تحلیلی که تا حالا ارائه دادم، فقط یه اسلاید بود. سه هفته روی اون کار کردم. بیشتر از چهل تا کوئری زدم، دو مسیر کاملاً به بن‌بست خورد و یه سگمنت‌بندی رو هم کلاً دور ریختم. ذی‌نفع پروژه هیچ‌کدوم از اینا رو ندید. چیزی که دید فقط یه اسلاید، یه نمودار و یه جمله بود: این چیزیه که تغییر کرده، دلیلش اینه و کاری که باید براش انجام بدیم هم اینه. اوایل کار، این موضوع اذیتم می‌کرد. با خودم می‌گفتم: «این همه کار کردم و ه

31👍9🔥3

22 Aug 2026, 03:35 UTC≈2,760 views35 reactionsread 28 August 2026

برای تبدیل شدن به یک AI Engineer خوب، فقط بلد بودن کار با LLM کافی نیست. باید بتونید یک سیستم کامل AI رو از مرحله‌ی انتخاب مدل و آماده‌سازی داده گرفته تا ساخت agent، ارزیابی، deployment و مدیریت در production طراحی و اجرا کنید. نکته‌ی مهم اینه که خروجی سیستم‌های AI برخلاف نرم‌افزارهای سنتی همیشه قابل‌پیش‌بینی نیست؛ بنابراین کار یک AI Engineer بیشتر از اینکه یک فرایند خطی باشه، یک چرخه‌ی مداوم از ساختن، تست کردن، بررس

26👍6🔥3

Showing the 12 most recent of 46 posts we hold for @reza_jafari_ai. 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.

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.

الهام لواسانی | آموزش زبان انگلیسی
@elienglish_academy · 36,484
Telegram ranks this channel #11 of 66 here — alongside 65 others — read 14 September 2026
Data Science | علم داده
@DataScience_ir · 50,088
Telegram ranks this channel #19 of 92 here — alongside 91 others — read 25 August 2026
AFARINESH | خانه آیلتس آفرینش
@afarinesh · 78,965
Telegram ranks this channel #20 of 87 here — alongside 86 others — read 19 August 2026
Kooshiar
@kooshiar3 · 25,895
Telegram ranks this channel #26 of 93 here — alongside 92 others — read 14 September 2026
Mehrsasharoleslam
@mehrsasharoleslam · 36,477
Telegram ranks this channel #26 of 92 here — alongside 91 others — read 1 September 2026
AvalAI | هوش مصنوعی
@aval_ai · 25,609
Telegram ranks this channel #31 of 92 here — alongside 91 others — read 13 September 2026
ApplyKite
@ApplyIR2UK · 38,126
Telegram ranks this channel #35 of 88 here — alongside 87 others — read 31 August 2026
هوش مصنوعی |یادگیری ماشین| علم داده
@Ai_Tv · 26,564
Telegram ranks this channel #37 of 94 here — alongside 93 others — read 12 September 2026
مهندس یار
@mohandesyar · 65,499
Telegram ranks this channel #37 of 90 here — alongside 89 others — read 21 August 2026
Dr Ahmadian
@drmjahmadian · 91,143
Telegram ranks this channel #41 of 93 here — alongside 92 others — read 17 August 2026
Canada Dream
@Canada_channel · 38,936
Telegram ranks this channel #44 of 79 here — alongside 78 others — read 31 August 2026
آهنگ جدید ریمیکس لاتی
@Behtarinrimixlati · 80,666
Telegram ranks this channel #47 of 60 here — alongside 59 others — read 19 August 2026
Machine Learning | یادگیری ماشین
@MachineLearning_ir · 34,380
Telegram ranks this channel #49 of 90 here — alongside 89 others — read 3 September 2026
💢 تفکرات پیمان
@tafakkoratpeyman · 26,342
Telegram ranks this channel #50 of 89 here — alongside 88 others — read 12 September 2026
Share the Joy
@sharethejoy · 30,831
Telegram ranks this channel #80 of 87 here — alongside 86 others — read 6 September 2026

This channel appears in 15 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 16 September 2026 — this entry's latest reading, not the date you are reading this.

“Reza Jafari” (@reza_jafari_ai), 8,771 subscribers as measured 16 September 2026. Telegram Register, tgregister.com/channel/reza_jafari_ai.

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.