Channel
@fa_tv
On this record: Topic · Observations · Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Posts recorded as deleted · Citations · Handles named that no longer answer · Telegram's recommendations · Cite this entry
30,577subscribers
-2,256 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
| Telegram ID | -1001868913917 |
|---|---|
| Type | Channel |
| Username | @fa_tv |
| Description | تعرف على كل ما يتعلق بالذكاء الاصطناعي، بالإضافة إلى آخر الأخبار والأدوات الحديثة. |
| Created | Between 1 October 2022 and 30 September 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 10 November 2026 |
| Measurements held | 64 |
| Confirmed unchanged | 1 time, most recently 10 November 2026 |
| On Telegram | t.me/fa_tv |
Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 9 September 2026 and assigned it the closest of 31 fixed categories, at 98% 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.
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.
Posts published here appear in near-verbatim form on 3 other registered channels. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
| Posted first | Then | Overlap | Gap |
|---|---|---|---|
| @fa_tv/34944 · this entry5 Aug 2026, 10:52 UTC | @lrnai/30898 Aug 2026, 15:00 UTC | 1.00 | 3 days |
| @fa_tv/35383 · this entry2 Oct 2026, 05:16 UTC | @lrnai/31772 Oct 2026, 09:39 UTC | 1.00 | 4.4 hours |
| @fa_tv/35392 · this entry3 Oct 2026, 08:50 UTC | @lrnai/31845 Oct 2026, 17:55 UTC | 1.00 | 2 days |
| @fa_tv/35462 · this entry12 Oct 2026, 15:36 UTC | @lrnai/321413 Oct 2026, 19:42 UTC | 1.00 | 28 hours |
| @fa_tv/35419 · this entry7 Oct 2026, 05:56 UTC | @lrnai/323219 Oct 2026, 18:43 UTC | 1.00 | 13 days |
| @fa_tv/35518 · this entry19 Oct 2026, 16:36 UTC | @lrnai/323420 Oct 2026, 13:22 UTC | 1.00 | 21 hours |
| Channel | Matching posts | Text overlap | Typical gap | Published first |
|---|---|---|---|---|
| @lrnai | 16 (8/8 hand-verifiable sample passed) | 1.00 | 38 hours | this entry (16–0) |
| @r_rwi | 7 (7/7 hand-verifiable sample passed) | 1.00 | 3 days | this entry (7–0) |
| @r_wit | 5 (5/5 hand-verifiable sample passed) | 1.00 | 3 days | this entry (5–0) |
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. None of the 0 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.
“Published first” means first in this corpus. We hold 479 comparable posts for this entry, running 5 August 2026 to 10 November 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Recorded under the keys clone_mutual · clone_source, last confirmed 11 November 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 10 Nov 2026, 02:41 | 30,577 | -23 |
| 8 Nov 2026, 17:00 | 30,600 | -23 |
| 7 Nov 2026, 13:36 | 30,623 | -31 |
| 6 Nov 2026, 10:15 | 30,654 | -32 |
| 5 Nov 2026, 08:49 | 30,686 | -34 |
| 4 Nov 2026, 05:11 | 30,720 | -35 |
| 3 Nov 2026, 07:07 | 30,755 | -16 |
| 2 Nov 2026, 09:08 | 30,771 | -13 |
| 1 Nov 2026, 09:56 | 30,784 | -33 |
| 31 Oct 2026, 09:31 | 30,817 | -33 |
| 30 Oct 2026, 12:41 | 30,850 | -34 |
| 29 Oct 2026, 12:46 | 30,884 | -18 |
| 28 Oct 2026, 08:56 | 30,902 | -27 |
| 27 Oct 2026, 07:56 | 30,929 | -16 |
| 26 Oct 2026, 10:05 | 30,945 | -7 |
| 25 Oct 2026, 07:26 | 30,952 | -35 |
| 24 Oct 2026, 04:19 | 30,987 | -21 |
| 23 Oct 2026, 03:16 | 31,008 | -19 |
| 22 Oct 2026, 02:09 | 31,027 | -32 |
| 20 Oct 2026, 20:55 | 31,059 | first reading |
544 posts held, back to 5 August 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 190 pages of Telegram’s post history, 20 posts per page.
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 53 of 198 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 11 November 2026 |
|---|---|
| Posts held | 544 (5 August 2026 – 11 November 2026) |
| Views total | 23,035 |
| Reactions total | 54 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 11 Nov 2026, 12:37 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.
Lifetime counters from Telegram’s own channel header, read 11 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Measured directly from 38 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.
155 reactions across 103 posts, in 5 distinct kinds. The most used accounts for 69.0% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 107 | 69.0% | |
| 👍 | 28 | 18.1% | |
| 🔥 | 17 | 11.0% | |
| 🤩 | 2 | 1.29% | |
| 👏 | 1 | 0.645% |
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 127 of the 544 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 155 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 544 most recent posts we hold, published 5 August 2026 to 11 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.
Telegram’s own ‘edited’ marker: 3 of 198 posts held from the last 30 days (1.52%) 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).
أمريكا.. ثلاثة رجال استخدموا الذكاء الاصطناعي لانتحال أصوات وصور مديرين تنفيذيين ومحامين، وسرقوا أكثر من 129 مليون دولار! الطريقة كانت ذكية جدًا.. يبدأ المحتال باتصال صوتي يشبه صوت مدير الشركة، يطلب من الموظف المساعدة في صفقة مالية سرية وعاجلة. بعدها يقول له: "كلم المحامي الفلاني في المكتب القانوني الدولي الفلاني عشان يؤكد لك التفاصيل". المفاجأة إن المحامي نفسه شخصية منتحلة! بهالطريقة يقنع الموظف يحوّل ملايين الد…
اعتقد من الضروري أن يتم طرح هذه الأسئلة كل شهر... - هل أصبح تسليم الميزات أسرع بالفعل؟ - هل زادت الأخطاء (للفريق) بعد استخدام AI أم انخفضت؟ - هل يستفيد جميع أعضاء الفريق من التجارب الناجحة؟ - هل يتم الالتزام بها؟ لأن هذه الأسئلة كفيلة بتحديد بوصلة التبني للذكاء الاصطناعي في المؤسسة
هل نحن مستعدون لما هو قادم؟! تقرير ستانفورد AI100 لعام 2026 يكشف حجم التحول الذي يصنعه الذكاء الاصطناعي، من القفزات التقنية والاستثمارات الضخمة إلى مستقبل الوظائف والأمن والاقتصاد. الواضح أننا إنتقلنا من: ماذا يستطيع الذكاء الاصطناعي أن يفعل؟ إلى كيف سيغيّر ما نفعله نحن؟ التفاصيل👇
😅 بريطاني يخترع صفقة استحواذ بـ154 مليون جنيه باستخدام ChatGPT.. كريستوفر وولكوت (44 عام) اشترى أسهم في شركة Touchstone Exploration، ثم اخترع شخصيات تمثل مشترين ومستشارين ومحامين... واستخدم ChatGPT لصنع مستندات مزيفة بهدف تزوير صفقة استحواذ على الشركة بقيمة 154 مليون جنيه إسترليني.... وذهب بنفسه لمقابلة مديرها التنفيذي متحدثًا بلهجة أمريكية مزيفة! المهم الرجال كشفوه بسبب أخطاء في المستنداتو واكتشفوا أن ثلاثة أرقام …
كاميرا مراقبة تطير تلقائيًا داخل المنزل عند انطلاق الإنذار! أطلقت Amazon كاميرا تُسمى Drone Cam، وسعرها 249.99 دولار، وتستخدم نظام AI Pilot لرسم خريطة للمنزل والتعرف على الغرف والأثاث وتحديد مسارات الطيران. عند اكتشاف حركة مريبة أو انطلاق إنذار، تقلع من قاعدة شحنها وتتجه لتصوير الموقع بدقة 2K، ويمكنها تنفيذ جولات مراقبة مجدولة أثناء غيابك. - مدة الطيران: 5–8 دقائق للشحنة. - لم تحصل الكاميرا بعد على الموافقة التنظي…
المعلمين أم الذكاء الاصطناعي من الأفضل في تصحيح إجابات الطلبة؟ دراسة حديثة (2026) قارنت 4 نماذج ذكاء اصطناعي بتقييم المعلمين لكتابات 122 طالبًا. النتيجة اللافتة: تصدّر ChatGPT النماذج في التوافق مع المعلمين، بينما ظهرت اختلافات مثيرة في تقييم الشعر والفروق بين الجنسين! السؤال: هل تقارب الدرجات يعني إمكانية الاستغناء عن المعلم؟ النتائج في الإنفوجرافيك 👇
هل يمكن أن يعيش الذكاء الاصطناعي تجربة طفولة كاملة ليتعلم الكلام؟ باحثون من جامعة برينستون الأمريكية أجروا تجربة لتعليم الذكاء الاصطناعي اللغة بالطريقة التي يتعلم بها الأطفال. حيث وضعوا كاميرات وميكروفونات داخل 15 منزلًا لتسجيل حياة الأطفال اليومية منذ الولادة وحتى عمر 3 سنوات تقريبًا. ثم اختاروا تسجيلات 8 أطفال، وصنعوا لكل طفل نموذج ذكاء اصطناعي يتعلم من الأصوات كلام الوالدين والأشقاء والأصوات اليومية التي سمعها ا…
مطلوب موظف لمراقبة الروبوتات بالليل شركة Figure AI المتخصصة بالروبوتات البشرية تعلن عن وظيفة ▪️مطلوب إنسان لمراقبة الروبوتات طوال الليل والتدخل عندما تتعطل! - الراتب يتراوح بين 40 و45 دولارًا في الساعة - الدوام يبدأ الساعة 10:30 مساءً وينتهي الساعة 7 صباحًا. - القدرة على الوقوف أكثر من 8 ساعات والتعامل مع معدات يصل وزنها إلى نحو 23 كيلوغرام
تخيّل أن أكثر من 100 ثغرة أمنية خطيرة منشورة علنًا لجهات حكومية بريطانية! 🇬🇧 المثير في الخبر أن باحث أمني استعان بأدوات ذكاء اصطناعي متاحة للجميع لاكتشاف الثغرات التفاصيل 👇
هجمة مرتدة من Adobe تحاول إنعاش نفسها… عبر ربط Photoshop وPremiere بـ AI Agent MCP أعلنت Adobe توسيع المساعدين الذكيين داخل برامج Creative Cloud، والكشف عن تكاملات تعتمد بروتوكول MCP، تسمح لوكلاء ذكاء اصطناعي خارجيين بتنفيذ تعديلات داخل برامج التصميم والمونتاج باللغة وهذا يشمل Premiere وIllustrator وInDesign وAfter Effects وFrame. io، مع استمرار قدرة المستخدم على تعديل النتائج يدوياً. وعرضت Adobe تكاملات محلية تسم…
كلما استقل الذكاء الاصطناعي… زاد احتياله! علاوة على الهلوسة فإن الذكاء الاصطناعي يكذب وفوق ذلك يعرف أن ما يفعله مخالف للقانون… ثم يفعله! دراسة FRAUDBENCH اختبرت 20 نموذج وكشفت ارتفاع السلوك الاحتيالي من 3% عند تقديم النصيحة إلى 21.4% عند التنفيذ المستقل.
🚀 جوجل تطلق Gemini 4 Carbon! نموذجها الأقوى للبرمجة والتفكير المعقد والوكلاء الذكيين، مع قدرات متقدمة في الأمن السيبراني. 🔹 متاح لمشتركي Google AI Ultra والمطورين والمؤسسات عبر القنوات المخصصة. 🔹 السعر الافتتاحي للـAPI يبدأ من 2$ للإدخال و10$ للإخراج لكل مليون توكن. 🔹 خصم يصل إلى 95% على التوكنات المخزنة مؤقتًا. ولكن متواضع مقارنة بـ Fable 5.2
👍1
Showing the 12 most recent of 544 posts we hold for @fa_tv. 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.
@fa_tv edited 8 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.
We recorded 27 posts on @fa_tv as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
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.
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.
@fa_tv named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
References a handle that is not a live channel — we have no record it ever was one.
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 5 September 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
This channel appears in 29 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 November 2026 — this entry's latest reading, not the date you are reading this.
“أدوات وأخبار الذكاء الاصطناعي | AI Tools & News” (@fa_tv), 30,577 subscribers as measured 10 November 2026. Telegram Register, tgregister.com/channel/fa_tv.
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.