3 measurements taken within a single day, net -1. 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 1,470–1,471 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
12 Aug 2026, 17:53
1,470
-1
12 Aug 2026, 06:30
1,471
no change
12 Aug 2026, 06:16
1,471
first reading
Engagement
20 posts held, back to 10 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 1 pageof Telegram’s post history, 20 posts per page.
ERR · 30 days
18.8%
avg views ÷ 1,470 subscribers
Avg views / post
276
17 posts measured
Reaction rate
1.22%
reactions ÷ views · ER floor
Posts in window
17
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 15 of 17 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 9 August 2026
Posts held
20 (10 June 2026 – 9 August 2026)
Views total
4,693
Reactions total
52
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
12 Aug 2026, 06:30 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 08s
Average length
34s
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
77 reactions across 17 posts, in 4 distinct kinds. The most used accounts for 41.6% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
32
41.6%
🤣
29
37.7%
👍
12
15.6%
👏
4
5.19%
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 18 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 77reactions 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 June 2026 to 9 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.
آقا ما توی ناین کرفت حدود دو ماهه که VPS هم ارائه میدیم 👀
ناینکرفت چند ساله که روی گیمسرور، مخصوصاً ماینکرفت و تراریا، کار میکنه. توی این مدت، هم در ناینکرفت و هم چند بیزنس دیگه، کلی تجربهی مدیریت سرور، شبکه و حفظ آپتایم جمع کردیم.
امسال گفتیم وقتی زیرساخت و تجربهش رو داریم، چرا VPS ندیم؟
الان VPSهای ناینکرفت رو راه انداختیم؛ فعلاً پلنهای اقتصادی با لوکیشن ایران داریم که برای خیلی از نیازها کاملاً جواب …
جایگزین متن باز Fonto، رایگان، تحت وب
دیگه برای استوریاتون پول اشتراک ندید😁
و اگر دوست داشتید، از بالا(علامت قلب) به سازنده دونیت کنید تا لایسنس تجاری بخره و فونتهای خفنتر واستون بذاره.
لینک پروژه:
https://github.com/FontWoW/FontWoW.github.io
لینک سایت:
https://fontwow.github.io
هدف داک داک گو فروش عینک نبوده و نیست، هدفش یاد اوری این نکته مهمه که بهترین راه برای مقابله با عینکهای که از کاربر جاسوسی میکنند و هوش مصنوعی دارند، نخریدن اوناست.
@PhiloLearn
داشتم میگشتم که رسیدم به این شبیه ساز سیاهچاله
https://blackhole.plav.in
و خب این ریپازیتوری که باهاش شبیه ساز رو ساختن که توسعه پیدا کرده برای شبیه سازی رفتار نور اگر اشتباه نکنم:
https://github.com/aplavin/Synchray.jl
@PhiloLearn
این شبکه عصبی دو تا ویژگی داره:
1-شبکههای بازگشتی از اطلاعات گذشته استفاده میکنند.
2-در شبکههای بازگشتی، پارامترها یا وزنها بین زمانها به اشتراک گذاشته میشوند. به این معنا که همان وزنها برای هر مرحله زمانی استفاده میشوند.
به صورت کلی این شکبه میاد ورودی رو از ما دریافت میکنه با وزن حافظه قبلی که آموزش دیده ترکیب میکنه و میره مرحله بعدی یعنی مثلا من یک گربه مشکی دارم میاد پنج لایه درست میکنه:
من + یک + گربه + …
یه چیز بشدت باحال و بامزه و شاید کاربردی پیدا کردم.
اومدن نحوه عملکرد دیتابیس پستگرس رو به صورت ۳ بعدی و قابل گشتن در آوردن و تمام بخش هاش رو خیلی جذاب توضیح دادن.
لینک شهر پستگرس:
https://nikolays.github.io/PGSimCity/
لینک ریپازیتوری:
https://github.com/NikolayS/PGSimCity
@PhiloLearn
این شبکه عصبی وقتی معرفی شد اومد نواقصات و مشکلات شبکه عصبی بازگشتی(RNN) رو پوشش داد و تونست تحول بزرگی در حوزه هوش مصنوعی بده و مدل های زبانی بزرگی مثل GPT کمک کنه توسعه پیدا بکنن
این مدل به جای اینکه مثل RNN بیاد کلمات رو یکی یکی پشت سر هم بررسی کنه تا بتونه کلمات رو درک کنه که در این مسیر ممکنه اطلاعات رو گم یا فراموش بکنه یا نتونه ارتباط درستی بین کلمات پیدا کنه میاد تمامی داده هارو هم زمان بررسی میکنه به شکل موا…
حقیقتا علاقه ی خیلی زیادی دارم به اتفاقاتی که باعث سنجیده شدن حد و حدود حریم خصوصی و نفوذ قانون میشن (با توجه به اینکه قانون خارج از ایران محدودیت داره).
مثلا خبری که به تازگی دیده بودم این بود که یه فردی رو تو فرودگاه آتلانتا آمریکا میبرن برای بازجویی. گفته میشه که بدون این که حقوقش بهش اعلام بشه و بدون اینکه وکیل فرد حضور داشته باشه شروع میکنن به بازجویی فرد به بهانه محتوای سوءاستفاده جنسی از کودکان. ازش میخوان…
غولهای تکنولوژی نامه نوشتن که هوش مصنوعی متنباز رو ممنوع نکنید
شرکت Nvidia یه نامه سرگشاده منتشر کرده و از سیاستگذارها خواسته جلوی مدلهای هوش مصنوعی متنباز رو نگیرن.
این نامه بعد از یه گزارش اومده که میگفت بعضی مقامهای دولت Trump دنبال محدود کردن این جور مدلها بودن. طبق گزارش Axios، وزارت بازرگانی آمریکا سال پیش داشت به فکر مسدود کردن دسترسی به نرمافزار شرکتهای چینی میافتاد، چون خیلی از محبوبترین مدلها…
👍3❤1
Showing the 12 most recent of 20 posts we hold for @Philolearn. 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.
Citation-graph rank
Citation-graph rank — 546,528 of 1,151,006entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
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 1 registered channel — 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.
Named by
Channels on the register whose posts name this channel's handle.
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 12 August 2026 — this
entry's latest reading, not the date you are reading this.
“PhiloLearn | فیلولرن” (@Philolearn), 1,470 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/Philolearn.
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.
