Telegram RegisterThe public register of Telegram
Telegram profile photo for پادکست هوش مصنوعی | AI Natives

Channel

پادکست هوش مصنوعی | AI Natives

@ai_natives

On this record: Growth · Engagement · Reactions · Posts · Polls · Cite this entry

2,502subscribers

+34 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1002062996647
TypeChannel
Username@ai_natives
CreatedBetween 1 November 2023 and 31 May 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live30 August 2026
Measurements held9
Confirmed unchanged1 time, most recently 30 August 2026
On Telegramt.me/ai_natives

Growth

2,4682,5022,4857 August 2026 — 2,468 subscribers7 August 2026 — 2,471 subscribers11 August 2026 — 2,478 subscribers14 August 2026 — 2,483 subscribers17 August 2026 — 2,492 subscribers21 August 2026 — 2,496 subscribers24 August 2026 — 2,489 subscribers27 August 2026 — 2,496 subscribers30 August 2026 — 2,502 subscribers7 August 202630 August 2026
9 measurements spanning 23 days, net +34. 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 2,463–2,507 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
30 Aug 2026, 21:532,502+6
27 Aug 2026, 20:132,496+7
24 Aug 2026, 20:272,489-7
21 Aug 2026, 02:532,496+4
17 Aug 2026, 16:272,492+9
14 Aug 2026, 01:072,483+5
11 Aug 2026, 01:582,478+7
7 Aug 2026, 20:332,471+3
7 Aug 2026, 16:472,468first reading

Engagement

20 posts held, back to 10 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 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
18.3%
avg views ÷ 2,502 subscribers
Avg views / post
459
8 posts measured
Reaction rate
1.78%
reactions ÷ views · ER floor
Posts in window
8
of 20 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 6 of 8 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 7 August 2026
Posts held20 (10 July 20267 August 2026)
Views total3,668
Reactions total47
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Aug 2026, 16:47 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.

Reaction mix

91 reactions across 14 posts, in 6 distinct kinds. The most used accounts for 44.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
4044.0%
👍3033.0%
🔥1213.2%
🙏44.40%
👌33.30%
🥰22.20%

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 14 of the 20 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 91reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 20 most recent posts we hold, published 10 July 2026 to 7 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.

Recent posts

7 Aug 2026, 14:24 UTC249 views5 reactionsread 7 August 2026
Photo

چند روزی هست دانشگاه Stanford دوره Self Improving AI Agents رو شروع کرده، اگر علاقه دارید استفاده کنید. لینکش: https://www.youtube.com/playlist?list=PLangBM27OtEA

🔥5

6 Aug 2026, 15:16 UTC433 views10 reactionsread 7 August 2026

برای دوستانی که تازه به کانال اومدن: 1. اگر تازه می‌خواید وارد دنیای هوش مصنوعی بشید، پیشنهاد می‌کنم اول این ویدئو رو ببینید. https://www.youtube.com/watch?v=0kQmytBX9Rc&list=PLFf9tFmijLOE توی این ویدئو درباره نقش‌های اصلی این حوزه مثل Data Scientist، ML Engineer، AI Engineer و همچنین نقش‌های پژوهشی صحبت کردم و تفاوت‌ها، مسئولیت‌ها و مسیر هر کدوم رو توضیح دادم تا از همون ابتدا دید بهتری نسبت به این حوزه داشته باشی

10

4 Aug 2026, 11:38 UTC447 viewsread 7 August 2026
Poll

شما روی ساخت و طراحی ایجنت‌ها کار می‌کنید؟ (چه یادگیری و چه کار تخصصی)

  1. بله40%
  2. خیر60%

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

4 Aug 2026, 11:18 UTC444 views9 reactionsread 7 August 2026
Photo

حرفی که خیلی تو ذهنم بود ولی حالشو نداشتم پست بنویسم براش: این روزا خیلیا با یه دوره N8N میخوان بهت بقبولونن که دیگه متخصص هوش مصنوعی شدی ولی نه n8n فقط یه ابزار اتوماسیونه نه یه میان‌ بر برای یادگیری هوش مصنوعی با n8n یاد می‌گیری چطوری چندتا مدل هوش مصنوعی رو کنار هم بچینی و باهاشون کار کنی همین چند تا نود میکشی به هم وصلشون میکنی و یه ورکفلو قشنگ تحویل میدی ولی اینکه یه مدل چطوری آموزش می‌بینه چرا گاهی خرابکاری می

👍62👌1

4 Aug 2026, 11:02 UTC408 views5 reactionsread 7 August 2026
Photo

این مورد دوم، "To raise VC's funds"، خیلی جالبه. خیلی از شرکت‌های اروپایی رو می‌بینم که یک ایجنت ساختن، کلی ویدئو و دمو ازش منتشر کردن، اما وقتی وارد سایتشون می‌شم نوشتن: "Sign up for the waiting list". حتی داخل همون ویدئوها هم باگ‌های واضحی دیده می‌شه. برای من این سؤال پیش میاد که آیا واقعاً هدفشون ساختن یک ایجنت آماده برای استفاده هست، یا بیشتر برای بالا بردن شانس جذب سرمایه و جلب توجه VCها این کار را انجام دادن؟

👍41

2 Aug 2026, 13:39 UTC525 views8 reactionsread 7 August 2026

خیلی دنبال یه منبع خوب برای یاد گرفتن LangGraph گشتم؛ از دوره و ویدیو گرفته تا ریپوهای مختلف. آخرش به این داکیومنت رسیدم. به نظرم از خیلی از منابعی که دیدم بهتره، گفتم اینجا هم باهاتون به اشتراک بذارم. https://www.luochang.ink/dive-into-langgraph-en/quickstart/ .

4🙏4

28 Jul 2026, 07:14 UTC860 views1 reactionsread 7 August 2026

خودمونم قبلا ویدئو راجع بهش درست کردیم به همراه کد در پایتون. اگر ندیدن ببینیدش. مخصوص پروداکشن.

🥰1

28 Jul 2026, 07:13 UTC808 views1 reactionsread 7 August 2026

این ویدئو خیلی جالب و با انیمشن میاد مسیری که یک پرامپت در vLLM طی میکنه رو نمایش میده. https://www.youtube.com/watch?v=yHAcgyntYDQ

🥰1

25 Jul 2026, 20:10 UTC805 views11 reactionsread 7 August 2026

یک نکته کاربردی: داشتم یه دوره می‌دیدم. مدرس با اعتمادبه‌نفس کامل می‌گفت باید توی ایجنت‌هامون حتما از Reflection استفاده کنیم تا جواب دقیق‌تری بگیریم. خب اینکه Reflection می‌تونه دقت رو بیشتر کنه، حرف درستی‌ه... ولی به چه قیمتی؟ یعنی یه حلقه بذاریم که ایجنت مدام خودش رو بررسی کنه تا بالاخره به جواب درست برسه؟ پس هزینه توکن‌ها چی؟ زمان پاسخ‌گویی چی؟ اگر همزمان چند تا کاربر از ایجنت استفاده کنن، این تأخیر و هزینه چ

👍72👌2

23 Jul 2026, 17:20 UTC≈1,130 views11 reactionsread 7 August 2026

تا امروز هرچی بیشتر با AI Agentها کار کردم، بیشتر به این نتیجه رسیدم که یکی از بدترین ایده‌ها برای یک پروژه Enterprise، ساخت Data Analyst Agent هست. البته برای آموزش و یادگیری فوق‌العاده هست. خودم هم چنین پروژه‌ای انجام داده‌ام و برای یاد گرفتن مفاهیمی مثل Tool Calling، RAG و Agent Workflow تجربه‌ی خیلی خوبی بود. اما وقتی صحبت از دنیای واقعی و Enterprise میشه داستان کاملاً فرق می‌کنه. مشکل فقط وصل شدن به دیتاسورس‌ه

👍101

Showing the 12 most recent of 20 posts we hold for @ai_natives. 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.

Polls

The poll we hold for this entry, as Telegram rendered it when we read the post. A poll’s figures keep moving after that, so each one is dated.

4 Aug 2026, 11:38 UTCAnonymous Poll65 voters

شما روی ساخت و طراحی ایجنت‌ها کار می‌کنید؟ (چه یادگیری و چه کار تخصصی)

  1. بله40%
  2. خیر60%

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 20 most recent posts we hold, published 10 July 2026 to 7 August 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.

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.

“پادکست هوش مصنوعی | AI Natives” (@ai_natives), 2,502 subscribers as measured 30 August 2026. Telegram Register, tgregister.com/channel/ai_natives.

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.