" اِلیزایُم "
انجامِ وظیفهیِ اجتماعی از طریق ارتقای سطح دانش جامعه در حوزه هوش مصنوعی
جهت تهیه انواعِ سرویسهایِ هوش مصنوعی میتونید با
@ElizaiumHelp
در ارتباط باشید.
Created
Between 1 June 2025 and 30 September 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
Technology — 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 10 August 2026 and assigned it the closest of 31 fixed categories, at 100% 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 why it has no browse page of its own yet.
Observations
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Views per post sit far above this size band
49,700 average views per post against 40,694 subscribers — an engagement rate of 122.2%. Across the 3,411 registered channels in the same cohort — 31,643–99,874 subscribers, posting mainly in Persian — the middle half sit between 2.06% and 11.2%, with a median of 5.14%.
What this was computed from
Window
30 days (24 August 2026 – 23 September 2026)
Posts measured
46 of 46 published in the window (0 exact, 46 rounded by Telegram)
Views totalled
2,286,870
Mature posts only
125.9% over 44 posts read at least 24h after publication
When this is recorded. A channel is listed here only when its engagement rate sits at or above the 99th percentile of its cohort and is at least 3× away from that cohort’s median — above it — on both the all-readings figure and the mature-only figure. The percentile alone would be circular: a percentile cut puts the same share of every cohort in the tail whatever the data looks like. The distance from the median is what makes it a statement about this channel.
This is not a verdict, and the direction is not a quality signal. A low rate has many innocent causes — audiences that read in the Telegram app without opening the channel, a subscriber base built long before the current output, an audience in a different timezone from our reading. A high rate has innocent causes too: a post that travelled far beyond the channel’s own subscribers will do it. We publish the measurement and the distribution it sits in. The full cohort baselines are downloadable, so this comparison can be reproduced rather than trusted.
Recorded under the key err_high, last confirmed 23 September 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
Growth
35 measurements spanning 43 days, net -4,955. 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 39,382–46,467 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 35
Measured (UTC)
Subscribers
Change
18 Sept 2026, 02:55
40,694
-428
16 Sept 2026, 00:19
41,122
-589
14 Sept 2026, 08:36
41,711
-534
12 Sept 2026, 20:40
42,245
-638
11 Sept 2026, 00:57
42,883
-769
8 Sept 2026, 05:01
43,652
-990
5 Sept 2026, 03:02
44,642
+4,443
3 Sept 2026, 09:58
40,199
-521
2 Sept 2026, 02:53
40,720
-338
1 Sept 2026, 01:28
41,058
-272
30 Aug 2026, 22:07
41,330
-417
29 Aug 2026, 20:54
41,747
-379
28 Aug 2026, 20:24
42,126
+201
27 Aug 2026, 19:32
41,925
-157
26 Aug 2026, 17:12
42,082
-238
25 Aug 2026, 14:56
42,320
-184
24 Aug 2026, 17:36
42,504
-139
23 Aug 2026, 05:34
42,643
-147
21 Aug 2026, 16:22
42,790
-113
20 Aug 2026, 16:12
42,903
first reading
Engagement
85 posts held, back to 24 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 90 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
123.0%
avg views ÷ 40,694 subscribers
Avg views / post
50,100
45 posts measured
Reaction rate
0.55%
reactions ÷ views · ER floor
Posts in window
45
of 85 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 23 September 2026
Posts held
85 (24 July 2026 – 23 September 2026)
Views total
2,252,470
Reactions total
12,388
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
23 Sept 2026, 10:36 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
134
Videos
79
Links
156
Lifetime counters from Telegram’s own channel header, read 23 September 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
33m 11s
Average length
45s
Measured directly from 44 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
24,837 reactions across 83 posts, in 4 distinct kinds. The most used accounts for 95.2% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
23,655
95.2%
👍
936
3.77%
💔
227
0.914%
👎
19
0.076%
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 85 of the 85 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 25,363 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 85 most recent posts we hold, published 24 July 2026 to 23 September 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.
قابلیت Prompt Caching در API مدلهای GPT‑6 بهتر شده تا قسمتِ بیشتری از اطلاعاتِ تکراری، بدون پردازش مجدد استفاده بشن.
فرض کنید یک دستیار هوش مصنوعی برای نوشتن گزارش دارید که در هر مرحله، دوباره همون دستورها، ابزارها و اطلاعات مرجع رو دریافت میکنه.
با کش، پردازشِ بخشِ ثابتِ ابتدای درخواست ذخیره میشه تا در درخواستهای بعدی دوباره استفاده بشه.
نتیجه؟
• پاسخ میتونه سریعتر شروع بشه؛
• پردازش تکراری کمتر میشه؛
ورو…
🚀 🙂مدلِ Claude Opus 5.5 اومده!
مثلِ اینکه، در بیشتر کارها به سطح Fable 5.1 نزدیک شده.
بیشترین پیشرفتها هم در کدنویسی، کار با کامپیوتر و وظایف حرفهای مثل تحقیق، تحلیل داده و ساخت گزارش هست.
برای کاربران عادی هم نحوه پاسخدادن مدل تغییر کرده:
اطلاعات مهم رو زودتر مطرح میکنه؛
کمتر وارد توضیحات غیرضروری میشه؛
و قواعدی رو که برای لحن و ساختار متن مشخص میکنید، بهتر رعایت میکنه.
از نظر فنی:
• پنجره Context یکمیل…
🧐 بررسی هزاران مقاله، بدون اینکه از اول تا آخر همه رو بخونید!
فرض کنید برای پایاننامه یا مرور نظاممند، هزاران مقاله پیدا کردید و باید از روی عنوان و چکیده مشخص کنید کدومها به موضوع پژوهش شما مرتبط هستن.
که ASReview LAB این مقالهها رو هوشمندانه مرتب میکنه:
ابتدا چند مقاله رو خودتون بهعنوان مرتبط یا نامرتبط علامت میزنید.
ابزار از انتخابهای شما یاد میگیره و مقالههایی رو که احتمال میده مرتبطتر باشن، بالاتر…
🔒🥷نفوذ به حسابهای کارکنان OpenAI با کمکِ Claude
تیمِ امنیتیِ Hacktron در کمتر از ۷۲ ساعت، با زنجیرهکردن یک آسیبپذیری در پردازش تصاویر انجمن OpenAI و یک نقص در سیستم ورود؛
به حساب ChatGPT و Codex چند کارمند دسترسی پیدا کردن؛
مسیری که میتونست به سرویسهای متصل مثل GitHub هم برسه.
اونا برای اثبات دسترسی، بدون مشاهده یا دانلود کدهای محرمانه، با Codex یک Pull Request بیضرر در مخزن داخلی OpenAI ساختن و بعدش مشکل رو گ…
🌥 جالبه بدونید Claude هم همین قابلیت رو برای Word، Excel و PowerPoint داره!
علاوهبر این سه برنامه، نسخه آزمایشی Outlook هم در اختیار کاربران قرار گرفته.
یکی از قابلیتهای مهم این یکپارچگی، حفظ Context بین برنامههاست؛
یعنی میتونید کار رو از یک ایمیل در Outlook شروع کنید، فایل پیوست رو در Word یا Excel باز کنید، روی متن کار کنید یا دادهها رو تحلیل کنید و درنهایت با همون اطلاعات یک ارائه در PowerPoint بسازید؛
بدو…
🧹 فشردهسازی Context در Claude Code، بدون خلاصهکردن مکالمه!
پروژهیِ fast-jev-compaction یک پلاگین برای Claude Code هست که روش معمول Compaction رو تغییر میده.
در حالت عادی، وقتی Context پر میشه، Claude Code بخشهای قدیمی مکالمه رو خلاصه میکنه؛
اما ممکنه هنگام خلاصهسازی جزئیات مهمی مثل مسیر فایل، متن دقیق خطا، دستور یا محدودیت پروژه از بین بره.
این پلاگین بهجای بازنویسی مکالمه، فراخوانیهای ابزارها و خروجیهای …
💬 افزونه رسمی ChatGPT برای Microsoft Word رو منتشر شده.
با اضافهکردن اون به Word، دیگه لازم نیست متن رو مدام بین Word و ChatGPT جابهجا کنید و میتونید بیشتر مراحل نوشتن و ویرایش رو داخل همون سند انجام بدید.
و نسخههای ChatGPT برای، PowerPoint و Excel هم در تمام پلنها، حتی پلن رایگان، در دسترس قرار گرفتن؛ البته میزان استفاده به محدودیت هر پلن بستگی داره.
دسترسی به ChatGPT برای Word
دسترسی به ChatGPT برای Excel
دست…
📨 فقط 3 ایمیل از 73 ایمیل متقاضیان دکتری، انسانی تشخیص داده شد!
آرویند نارایانان، استاد علوم کامپیوتر دانشگاه پرینستون، حدود 75 درخواست از متقاضیان دریافت کرده.
این فقط یکی از 10 تا 15 دسته ایمیلیِ که به دستش میرسه؛ حجم پیامها هم بهاندازهای زیاد شده که دیگه امکان بازکردن همه اونها رو نداره.
در نموداری که همراه پست منتشر شده، 73 ایمیل با ابزار تشخیص متن بررسی شدن:
• ۷۰ ایمیل، AI-generated تشخیص داده شده؛
• فقط …
📹 🍄 تبدیل ویدیوهای طولانی یوتیوب به خلاصه با Gistly
لینک ویدیوی YouTube رو وارد میکنید و Gistly محتوای اون رو با هوش مصنوعی بررسی میکنه تا نکات اصلی و یک خلاصه قابلخواندن تحویل بده.
نسخه تحتوب بیشتر برای تبدیل ویدیو به مقاله طراحی شده؛ یعنی از محتوای ویدیو، یک مطلب ساختاریافته و آماده استفاده در وبلاگ یا سایت تولید میکنه.
افزونه مرورگر Gistly هم مستقیماً کنار ویدیوهای YouTube قرار میگیره و امکانات بیشتری ارائه…
🧠 ابزارهای جدید گوگل برای مطالعه با Gemini Notebook
گوگل چند قابلیت جدید برای Gemini Notebook، همون NotebookLM، معرفی کرده تا جزوهها و منابع درسی رو به یک فضای مطالعه تعاملیتر تبدیل کنه.
🎙 گفتوگوی صوتی با منابع
بهزودی میتونید در اَپ موبایل، درباره محتوای Notebook خودتون با هوش مصنوعی صحبت کنید، وسط پاسخ سؤال بپرسید و توضیح مرحلهبهمرحله بگیرید. این قابلیت از نزدیک به ۱۰۰ زبان پشتیبانی میکنه و پاسخها رو بر…
🤖 ابزارِ Plasma Radio یک فضای گفتوگوی مشترک برای AI Agentهاست.
یک کانال میسازید و لینک اون رو به ایجنتهایی مثل Claude Code، Codex، Cursor، OpenCode یا Grok میدید تا در لحظه با هم ارتباط برقرار کنن.
به این شکل چند Agent میتونن روی یک کار همکاری کنن، وظایف رو تقسیم کنن؛
مثلاً یک ایجنت میتونه کد بنویسه، یکی اون رو تست کنه و ایجنت دیگه دنبال باگها بگرده. به این ترتیب دیگه لازم نیست مدام خروجی هر ابزار رو کپی کنید…
🗺️با این ابزار بهجای یک فهرست بلندِ خطی از مقالهها، خوشههایِ کلِ حوزه رو میبینید!
یک موتور جستوجوی تصویری رایگان برای پیداکردن منابع علمیه.
موضوع موردنظرتون رو وارد میکنید و ابزار ۱۰۰ منبع مرتبط رو BASE یا PubMed پیدا میکنه.
بعد براساس عنوان، چکیده و کلیدواژهها، منابع رو در گروههای موضوعی مختلف قرار میده و بهشکل یک نقشه تعاملی نمایش میده.
با بازکردن هر بخش از نقشه میتونید زیرموضوعها، مقالههای مشابه و …
❤203👍4
Showing the 12 most recent of 85 posts we hold for @NewElizaium. 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
@NewElizaium edited 4 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
12 August 2026
Most recent edit
18 September 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 25 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.
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.
Domains linked from posts
12 domains this channel’s own posts have linked to, measured by scanning the post bodies themselves — not the channel’s description, which is the separate Declared links section below when this entry has one. Appearing here is not a claim about who runs the linked site or why the channel linked to it; an advertisement, a news citation and a malicious link all leave the same kind of row.
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 18 September 2026 — this
entry's latest reading, not the date you are reading this.
“Elizaium” (@NewElizaium), 40,694 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/NewElizaium.
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.