تقریبا دو سال پیش یه چیزی رو شروع کردم ولی فکر کردم هنوز خامه (: حالا می خوام ادامه اش بدم. اونم بحث درک بدون ترس از هوش مصنوعی است. توی این ویدئو فقط تئوریک سعی می کنم بگم این اصطلاح «ایجنت» که هی می گن و هر روز یه مدلش میاد و پر هیجان می گیم بیاین نصب کنین و اینها چیه. توی ویدئوی بعدی می ریم سراغ نصب یکیش. و بعدش بر اساس درخواست های شما و سطح سواد و توان من پیش می ریم (: https://youtu.be/t5Ld-tw8q9I

Channel
TechNila
@TechNila
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
63subscribers
+0 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
Register entry
| Telegram ID | -1001181313984 |
|---|---|
| Type | Channel |
| Usernames | @TechKraken @TechNila |
| Description | Sapere aude ∞ 𝗧𝗲𝗰𝗵nology a𝗻d 𝗮𝗹𝗶↺ Introduction: t.me/TechKraken/7 Website: TechKraken.ir Anonymous Contact: t.me/TechKrakenBot Donations (TON): ton://transfer/TechKraken.ton |
| Created | Between 1 March 2018 and 30 June 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 10 August 2026 |
| Last confirmed live | 10 August 2026 |
| Measurements held | 4 |
| On Telegram | t.me/TechNila |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 10 Aug 2026, 07:00 | 63 | no change |
| 10 Aug 2026, 06:50 | 63 | no change |
| 10 Aug 2026, 03:16 | 63 | no change |
| 7 Aug 2026, 15:21 | 63 | first reading |
Engagement
20 posts held, back to 30 June 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 2 pagesof Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 58.7%
- avg views ÷ 63 subscribers
- Avg views / post
- 37.0
- 8 posts measured
- Reaction rate
- 4.48%
- 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 5 of 8 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 6 August 2026 |
|---|---|
| Posts held | 20 (30 June 2026 – 6 August 2026) |
| Views total | 296 |
| Reactions total | 9 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 10 Aug 2026, 07:00 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
- 66
- Videos
- 9
- Links
- 156
Lifetime counters from Telegram’s own channel header, read 10 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.
Reaction mix
22 reactions across 12 posts, in 3 distinct kinds. The most used accounts for 54.5% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤🔥 | 12 | 54.5% | |
| 🤩 | 6 | 27.3% | |
| 💔 | 4 | 18.2% |
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 12 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 22reactions 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 30 June 2026 to 6 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
🧬 ژندرمانیِ ناشنوایی Otoferlin پروتئینیه که عامل سیگنالدهی مژکهای گوش به دستگاه شنوایی مغزه و توسط ژن OTOF ایجاد میشه؛ اختلال توی این ژن میتونه باعث ناشنوایی یا کمشنوایی بشه و محققا چندسالی هست که تونستن با یکبار تزریق این ژن درون مایع perilymph گوش، ناشنوایی رو درمان کنن! در سنین پایینتر، درمان بهتر جواب داده. نکته جالب خارج از این خبر: بیششنوایی و احتمالاً میزوفونیا با اوتیسم ارتباط داره، البته شوپنهاور م…
🤩3
یکی از پیشنیازهای مدلهای وزنباز که transformers هست، توی نسخه جدیدش یه فانکشن رو بهطور کلی حذف کرده! درحالیکه مدلهای HuggingFace هنوز از اون استفاده میکنن. یعنی؟ یه مدل رو میخوای لود کنی، وارد dependency-hell میشی! درصورتیکه میشد فقط با یک خط if ساده، متدِ منسوخ رو استفاده کنه و کل ساختار کدهای آماده رو یکشبه داغون نکنه و کمی به کاربران فرصت بده!! یا حداقل تیم HF باید مدیریت میکرد این migration رو (وَ sni…
🤖 دو هفته کلنجار... Hermes Agent: The Hard Way (Iran Mode!) ⚠️ این پست برای افراد غیرکامپیوتری یا بیعلاقه به تکنولوژی مناسب نیست و بیشتر شامل تجربیات و معدود ایدههای محدودِ نویسندهست! اگه نمیدونین AI Agent مثل Hermes Agent چیه و چه فرقی با ChatGPT و... داره، اول از AI دربارهش بپرسین و بعد اگه دوست داشتین ادامه رو بخونین. اینروزها که بحثِ Hermes Agent داغه باید بگم که کلِ اون پروژههای Hyper-V و V2RayDAR و V2Pro…
👨💻 ادیتورهای مدرنِ ترمینال بهجای nano اگه توی سِرور و ترمینال با فایلهای بزرگ کار میکنین و هنوز از nano استفاده میکنین، بهنظرم وقتشه به edit مهاجرت کنین! یه ادیتورِ ساده که توسط مایکروسافت ساختهشده، با محیطی شبیه VSCode برای ترمینال؛ البته micro هم هست اما شخصاً با edit راحتترم. نصب روی لینوکس: sudo apt update && sudo apt install -y libicu-dev && ARCH=$(uname -m) && PATTERN=$([ "$ARCH" = "x86_64" ] && echo 'x…
❤🔥1
بعد از یه وقفهی خیلی طولانی، کتابِ How Emotions Are Made رو تموم کردم (طولانی چون فارسی و انگلیسی رو با هم پیش میبرم!! بهلطفِ سانسور و دقیقنبودن گزارههای علمی در زبان فارسی!). بعضی از قسمتهاش خیلی مهمن، که بدونیم سوگیریها چطور ایجاد میشن و حتی روی سایر موجودات زنده اثر میذارن!! اگه برای خودمون هم نخوندیم، بهنظرم کتابیه که پیش از بچهدار شدن یا حتی گرفتن یه پِت، بهتره مطالعه بشه (یا خلاصهش رو از یوتوب ببینی…
❤🔥2
لینوس توروالدز، سازنده و مسئول هسته لینوکس، در واکنش به استفاده از هوش مصنوعی برای کدنویسی و چک کردن کدها گفته لینوکس از اون پروژه های ضد هوش مصنوعی نیست و اگر کسی با این قضیه مشکل داره میتونه لینوکس رو فورک کنه یا اینکه بیخیال لینوکس بشه و بره پی کارش! این قضیه، از استفاده از ابزار هوش مصنوعی Sashiko برای پیدا کردن باگها و مشکلات امنیتی موجود در پچ های لینوکس شروع شد که Laurent Pinchart، یکی از توسعه دهندگان لینوکس…
❤🔥1
حس میکنم کمکم و بهصورت جدیتر، بوی قطعی اینترنت میاد. اگه تا الان متخصص نرمافزار و شبکه و رمزنگاری نشدین و کارِتون وابسته به اینترنته، وقتشه! کانالهای کمککننده: @iaghapour @MatinSenPaii @wbnet @radicalvpn دربارهی پروژهها و اپلیکیشنهای کاربردی هم: جوینده یابندهست. پینوشت: البته هر کاری هم بکنیم با قطعی برق و آنتن و دیتاسنتر و... عملاً اینترنت و حتی اینترانت پَر میشه. شبکهی Mesh هم که متأسفانه افراد زیادی…
💔2
تلگرام راه اندازی ربات تلگرام بدون نیاز به سرور را برای زبان جاوا اسکریپت فعال کرد Telegram serverless https://core.telegram.org/bots/serverless
🤩3
🌐 پروکسیِ SOCKS5 و HTTP با V2Ray بهلطفِ AI، گاهی از اول ساختنِ یهچیزی کمتر از اینکه دنبالش بگردی زمان میبره! البته گشتم و چیز سبک و سادهای نیافتم، ساختمش. قبلش V2RayA رو تست کردم که مکانیزم اتصالش زیادی دستی بود! V2ProDock رو ساختم واسه استفاده توسط APIهای مختلف، توی محیط مجازی، روی اینترنت ایران! که VPNها اونجوری که باید جواب نمیدن اما V2Ray و پروکسی نجاتدهندهست! توی پسزمینه، V2RayDAR کانفیگها رو جمع میک…
❤🔥3
آینده با AI از نگاه امیر حرمتی، مهندس گوگل و دیتابریکس 00:45:40 #YouTube
ساخت Agent بهجای کُدنویسی! بعد اینجا (در همین لحظه) میری مصاحبه، یه live-coding میذارن که توش مثلاً یادت میره یکی از قواعد SOLID رو رعایت کنی و ریجکت میشی!! =))))
Showing the 12 most recent of 20 posts we hold for @TechNila. 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
Republishes
Channels on the register whose posts this channel has forwarded.
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
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 August 2026 — this entry's latest reading, not the date you are reading this.
“TechNila” (@TechNila), 63 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/TechNila.
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.