5 measurements spanning 7 days, net +27. 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 7,472–7,507 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
13 Aug 2026, 07:55
7,503
+12
10 Aug 2026, 12:21
7,491
+12
7 Aug 2026, 04:40
7,479
+3
6 Aug 2026, 20:00
7,476
no change
6 Aug 2026, 19:54
7,476
first reading
Engagement
25 posts held, back to 22 July 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 12 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
21.0%
avg views ÷ 7,503 subscribers
Avg views / post
1,570
25 posts measured
Reaction rate
1.09%
reactions ÷ views · ER floor
Posts in window
25
of 25 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 24 of 25 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 11 August 2026
Posts held
25 (22 July 2026 – 11 August 2026)
Views total
39,297
Reactions total
406
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
12 Aug 2026, 17:23 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
48s
Average length
48s
Measured directly from 1 video 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
406 reactions across 24 posts, in 9 distinct kinds. The most used accounts for 59.9% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
243
59.9%
❤
125
30.8%
😢
24
5.91%
🔥
6
1.48%
😁
4
0.985%
👏
1
0.246%
🙏
1
0.246%
🤩
1
0.246%
🤷♂
1
0.246%
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 24 of the 25 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 406reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 25 most recent posts we hold, published 22 July 2026 to 11 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.
تفاوت یک AI Engineer معمولی با یک مهندس با حقوق $200K+
این قسمت: Tool Call
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روی سیستم خودش هم همهچیز خوب به نظر م…
گزارش جدید Stripe از تأثیر AI روی کسبوکارها
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جالبتر اینکه چهار سال پیش، یک founder در top 10% حدود ۳۴ برابر یک founder معمولی درآمد داشت؛ اما الان این فاصله به حدود ۶۱ برابر رسیده.
یعنی AI ورود به بازار رو خیلی راحتتر کرده، ولی لزوماً موفق …
نمایشی از عملکرد پروژه CoretxKG
تو این پست در مورد ویژگی های این پروژه گفتم ولی به صورت خلاصه اگه میخوای بدونی:
پروژه CortexKG اجازه میده شما با هر مدل LLM با هر Provider که خواستین صحبت کنین و این وسط گراف دانشی از خودتون، شخصیتتون، کاری که میکنین و یا هر اطلاعات دیگه داشته باشین و تو سیستم های دیگه از این دانش استفاده کنین.
پروژه به صورت اوپن سورس در گیتهاب:
گیتهاب
با استار ⭐️ گیتهاب از این پروژه حمایت کنین ❤️
Anthropic داره Auto Mode رو بهعنوان سیستم پیشفرض permission در Claude Code معرفی میکنه
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مشکل سیستم قبلی این بود که کاربرها تقریباً به 97٪ permission promptها اجازه میدادن و بعد از چند ده درخواست، دقت انسان در تشخیص commandهای خطرناک به حدود 5٪ می…
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اخیرا این پروژه کار کردم و به صورت اوپن سوریس تو گیتهاب گذاشتم.
در واقع CortexKG مکالمات شما رو به یه Knowledge Graph تبدیل میکنه یعنی مفاهیم تاریخچهی چت، موجودیت ها، افراد، پروژهها و ارتباط بین اونارو استخراج میکنه و بهصورت یک گراف دانش ذخیره میکنه.
این دانش ساخته شده قابل انتقال هست و تو سیستم های دیگه با LLM های مختلف لوکال مثل Ollama و انحصاری مث…
بهتازگی OpenAI نتایج مدل منتشرنشدهی خودش به اسم Astra رو منتشر کرده؛ مدلی که تونسته ۱۰ مسئله باز ریاضی رو حل کنه
مسائلی که بعضی از اونها بیشتر از ۱۰ سال (و حتی چند دهه) بدون جواب مونده بودن.
نکته جالب اینه که Astra فقط جواب نداده بلکه اثباتهای ریاضی رو هم تولید کرده و بعد اونها رو به زبان Lean 4 تبدیل کرده. Lean یه زبان برای Formal Verification هست که اثباتهای ریاضی رو بهصورت ماشینی بررسی میکنه و مطمئن میشه …
چرا حتی با temperature=0 هم LLM همیشه جواب ثابت نمیده؟
اگه نمیدونی temperature چیه اینجا گفتم
خیلیها فکر میکنن با temperature=0 خروجی مدل کاملاً deterministic میشه، ولی همیشه اینطور نیست.
یکی از دلیلهای اصلی، Floating Point Rounding هست. توی ترنسفورمرها میلیاردها عملیات Matrix Multiplication و Attention انجام میشه و به خاطر محدودیت دقت اعداد اعشاری، ترتیب اجرای محاسبات میتونه اختلافهای خیلی کوچیکی ایجاد کنه…
یکی یه پست گذاشته بود، با تمسخر و خنده میگفت: «فاز اون برنامهنویسایی که میگن کدهای AI باید Review بشن رو نمیفهمم، نیازی به برنامه نویسی و مهندسی کامپیوتر نیست و الکی به اینا پول ندین😅»
به نظرم ظهور AI با اینکه کلی فرصت فوقالعاده ایجاد کرده، یه مشکل جدی هم به وجود آورده؛ اینکه الان بعضیها تو هر حوزهای خودشون رو متخصص میدونن. بدون اینکه از مهندسی، معماری، محدودیتها یا حتی اصول اون حوزه شناختی داشته باشن، با اط…
یکی از مهمترین بخشهای هر شبکه عصبی، Activation Function هست. اگه بین لایهها فقط عملیات خطی (Linear) انجام بشه، حتی اگه هزار تا لایه هم باشه، کل شبکه معادل یه لایه ساده میشه و چیزی یاد نمیگیره.
اینجاست که Activation Functionهایی مثل ReLU، Sigmoid و Tanh وارد میشن. با اضافه کردن Non-linearity باعث میشن مدل بتونه الگوهای پیچیده، مرزهای غیرخطی و روابط بین دادهها رو یاد بگیره
مثلاً توی پردازش زبان، کلمهای مثل "flie…
خیلیا فکر میکنن ساختن AI Agent فقط به Prompt Engineering مربوطه، ولی در عمل چهار لایه مهم وجود داره:
Prompt Engineering:
نوشتن Prompt مناسب، تعیین Role، دادن Example و مشخص کردن Format خروجی مثل JSON.
Context Engineering:
مدیریت اطلاعاتی که به مدل میرسه؛ مثل RAG، Memory، تاریخچه چت و خروجی Toolها. چون Context Window محدوده، باید فقط اطلاعات مهم وارد مدل بشه.
Harness Engineering:
کدی که دور مدل نوشته میشه؛ مدیریت …
👍15❤5
Showing the 12 most recent of 25 posts we hold for @silicon_brain. 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
@silicon_brain edited 1 post 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
8 August 2026
Most recent edit
8 August 2026
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.
The shares total 177%, above 100: this poll accepts more than one answer per voter. No per-option vote count is published, so the number of voters who chose each option is not derivable and is not 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 25 most recent posts we hold, published 22 July 2026 to 11 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.
Citation-graph rank
Citation-graph rank — 671,658 of 1,169,250entries 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 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 13 August 2026 — this
entry's latest reading, not the date you are reading this.
“Silicon Brain | جامعه هوش مصنوعی” (@silicon_brain), 7,503 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/silicon_brain.
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.