اینجا چیزهایی را مینویسم که یا آنقدر کوتاهند که مناسب متمم و روزنوشتهها نیستند یا قرار است بعدا دربارهشان بیشتر بنویسم. اسمش را میشود گذاشت "هایلایت"
motamem.org
mrshabanali.com
محمدرضا شعبانعلی
Created
Between 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
Politics & activism — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 20 August 2026 and assigned it the closest of 31 fixed categories, at 99% 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 the other topics.
Growth
61 measurements spanning 93 days, net +1,971. 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 25,189–27,770 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 61
Measured (UTC)
Subscribers
Change
7 Nov 2026, 03:20
27,472
+81
6 Nov 2026, 00:21
27,391
+42
4 Nov 2026, 23:10
27,349
+63
3 Nov 2026, 21:51
27,286
+58
2 Nov 2026, 19:45
27,228
+50
1 Nov 2026, 21:47
27,178
+44
31 Oct 2026, 21:06
27,134
+44
30 Oct 2026, 19:38
27,090
+54
29 Oct 2026, 18:47
27,036
+12
28 Oct 2026, 17:40
27,024
+18
27 Oct 2026, 18:46
27,006
+27
26 Oct 2026, 19:48
26,979
+30
25 Oct 2026, 20:45
26,949
+66
24 Oct 2026, 17:39
26,883
+33
23 Oct 2026, 18:18
26,850
+21
22 Oct 2026, 20:56
26,829
+15
21 Oct 2026, 18:19
26,814
+18
20 Oct 2026, 13:31
26,796
+60
19 Oct 2026, 14:44
26,736
+179
18 Oct 2026, 15:06
26,557
first reading
Engagement
99 posts held, back to 13 December 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 138 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
44.3%
avg views ÷ 27,472 subscribers
Avg views / post
12,200
60 posts measured
Reaction rate
3.44%
reactions ÷ views · ER floor
Posts in window
60
of 99 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
Window
Rolling 30 days · latest post in window 6 November 2026
Posts held
99 (13 December 2025 – 6 November 2026)
Views total
729,560
Reactions total
25,098
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
7 Nov 2026, 04:22 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
274
Videos
21
Links
178
Lifetime counters from Telegram’s own channel header, read 7 November 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.
Video runtime
8m 51s
Average length
2m 57s
Measured directly from 3 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
62,418 reactions across 99 posts, in 4 distinct kinds. The most used accounts for 69.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
43,109
69.1%
👍
15,179
24.3%
✍
2,767
4.43%
🐳
1,363
2.18%
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 99 of the 99 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 62,418 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 99 most recent posts we hold, published 13 December 2025 to 6 November 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
Telegram’s own ‘edited’ marker: 46 of 60 posts held from the last 30 days (76.7%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
یادگیری مادامالعمر
میخواستم در جواب کامنت یکی از بچهها توی وبلاگم، سه نگاه مختلف به اصطلاح "یادگیری مادامالعمر / lifelong learning" رو شرح بدم.
طبق معمول، کامنتم طولانی شد و در قالب یه پست مستقل منتشرش کردم.
نیمهٔ دوم متن شخصیتره و ممکنه جذابیت عمومی نداشته باشه.
اما نیمهٔ اولش که سه نگاه رو توضیح دادم، شاید ارزش خوندن داشته باشه.
حرفی که زدهام اینه که اصطلاح یادگیری مادامالعمر رو میشه سه جور متفاوت ف…
ایشون رو میگم.
تا آخرین دونهٔ چیزی که دستش هست - و در چند سال آینده میتونه تولید کنه - رو از الان نفروشه، سیاستمدارهای دنیا رو با این AI Sovereignty ول نمیکنه.
دربارهٔ AI Sovereignty
اینکه ما بگیم «شرکتهای فعال در AI» یا «شرکتهای حوزهٔ تکنولوژی» واقعاً اصطلاح گمراهکنندهایه. ماهیت، جنس کار و دغدغههای این شرکتها لزوماً با هم یکسان نیست.
فعلاً برندهٔ بزرگ ماجرا Nvidia است که شبیه بیلچهفروشهای عصر کشف طلا در آمریکا میمونه.
هر کسی هر جای دنیا ضرب و تقسیم کنه و دیتاسنتر بخواد، Nvidia خوشحال میشه. بهخاطر همین، جنسن هوانگ، که قطعاً میدونه این موج بلندمدت نیست و با …
دربارهٔ حباب AI
اول یادمون باشه که حباب (bubble) با تبِ توجه (hype) فرق داره.
حباب یه اتفاق بورسی و بازاریه. اما هایپ راجع به اینه که چقدر فکر و ذهن مدیرها، کسبوکارها، مردم و رسانهها با موضوع درگیره.
البته که این دو تا روی هم تأثیر هم دارن. اما از نظر مفهومی، متمایز هستن.
اینکه الان خیلی از مدیرها مدام میگن ما چهجوری AI رو در کسبوکارمون استفاده کنیم و چه کنیم عقب نیفتیم و ...
بسته به تحلیل شما، میتونه ن…
قول میدم دو تا پست کوتاه دیگه بنویسم و این بحث رو ببندم تا یه مدت حرف نزنم.
دیگه سرگرم اخبار و انشاءالله ماشاءالله الحمدلله عبدل (السید) بشید و ماجراهای سیاسی آمریکا
از اونجا که دنیا هم روی خبرهای AI حساسه، بازیهای رسانهای توی این حوزه خیلی راحته.
توی تمام دنیا و توی همین ایران خودمون، دهها هزار آدم و رسانه و کانال نشستهان مدام این خبرها رو بازنشر کنن.
آخآخ این شد.
آخآخ اون شد.
و کمکم زمانی که انتظار عمومی به سطح مطلوب برسه، مثلاً بین ۱۵۰۰ یا ۲۰۰۰ میلیارد، حالا هر عددی که هدفگذاری کردهان، میشه IPO رو انجام داد.
جالبه که OpenAI ظاهراً تا این لحظه تصمیم گرفته بازیگر د…
انتخاب Anthropic و OpenAI چه بوده؟
به نظر میرسه که Anthropic خیلی مصممه که وارد بازی IPO بشه. رسماً هم گفته. چند بار هم دربارهٔ ارزشگذاریش صحبت شده.
و الان ماههاست عمیقاً درگیر IPO Marketing هست:
یه بار میان میگن ما نمیخوایم با ارتش آمریکا همکاری کنیم بهخاطر سلاحهای خودکار (= ما مسئولیتپذیریم). خب. زنگ بزن به ارتش بگو. چرا به ما میگی؟
یه سری میان میگن ما خودمون فکر میکنیم ممکنه باعث انقراض بشر بشیم. …
چند نکته دربارهٔ سقوط ارزش بازار شرکتهای مرتبط با AI
بخش پنجم
در ادامهٔ بخش چهارم (و بخشهای قبلش):
دو استراتژی پیش روی شرکتهای پیشرو غیربورسی در AI
یکی از گزینههای پیش روی شرکتهایی مثل Anthropic و OpenAI اینه که اگر مصمم هستن سراغ IPO برن، بهتدریج برنامههای «بازاریابی و روابط عمومی پیش از IPO» رو شروع کنن:
Pre-IPO Marketing & PR
برنامههای Pre-IPO برای چنین شرکتهایی خیلی پیچیده و چندلایه است. چون اصطلاح…
چون ما توی متمم از ده دوازده سال پیش دربارهٔ پیتر تیل و پالانتیر و کتاب صفر به یک حرف زده بودیم، اسم ناآشنایی براتون نیست.
اما چند تا نکته رو که اونجا نیست اینجا اضافه کنم:
پیتر تیل توی دورهٔ اول ترامپ، (به نظر من) اصلیترین آدم سیلیکونولی در اطراف ترامپ و عملاً پل ارتباطی تمام رفقای خودش با ترامپ بوده.
شاید اگر تیل نبود، ما جنسن هوانگ و ایلان ماسک و زاکربرگ و ... رو دور و بر ترامپ نمیدیدیم.
توی دورهٔ دوم ی…
چند نکته دربارهٔ سقوط ارزش بازار شرکتهای مرتبط با AI
بخش چهارم
در ادامهٔ بخشهای اول، دوم و سوم (همینطور توضیح دوبخشی دربارهٔ رویکرد کشورهای GCC به مشارکت در AI):
بیاید مشخصاً به مشهورترین شرکتهایی فکر کنیم که در حوزهٔ AI هستن و هنوز سهامشون بهشکل عمومی عرضه نشده. یعنی Anthropic و OpenAI.
این شرکتها الان وضعیت پیچیدهای دارن. برای اینکه بتونن سرمایهٔ جدید برای افزایش مقیاس پیدا کنن، یکی از بهترین راههای پ…
ترنس تائو
خیلیا میگن ترنس تائو یکی از بزرگترین ریاضیدانهای زندهٔ دنیاست.
کار ارزشمندی کرده و یه کتاب به زبان ساده دربارهٔ ۶ ابزار اصلی در ریاضی نوشته (اعداد، جبر، هندسه، آنالیز، احتمال و معادلات دینامیکی).
کتاب جمعوجوریه. توی این هفته در اومده و هنوز ندارم و ندیدمش.
اما چون گفتگوها و مصاحبههای ترنس تائو رو خوندهام و گوش دادهام، مطمئنم کتاب جذابیه.
آدمهایی مثل تائو و استروگاتز کار بزرگی میکنن که گاهی اون …
❤498👍79✍16
Showing the 12 most recent of 99 posts we hold for @bamotamem. 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
@bamotamem edited 10 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
26 September 2026
Most recent edit
5 November 2026
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 3 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.
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 7 November 2026 — this
entry's latest reading, not the date you are reading this.
“با متمم | هایلایت | محمدرضا شعبانعلی” (@bamotamem), 27,472 subscribers as measured 7 November 2026. Telegram Register, tgregister.com/channel/bamotamem.
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.