Telegram RegisterThe public register of Telegram
Telegram profile photo for AI Learning Resources 🌐

Channel

AI Learning Resources 🌐

@AI_Prompt_Learn

On this record: Topic · Observations · Channels linked by matching posts · Growth · Engagement · Reactions · Posts · Citations · Handles named that no longer answer · Cite this entry

1,352subscribers

-47 since we began measuring on 11 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1001476514527
TypeChannel
Username@AI_Prompt_Learn
CreatedBetween 1 April 2019 and 30 September 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded11 August 2026
Last confirmed live12 November 2026
Measurements held19
Confirmed unchanged1 time, most recently 12 November 2026
On Telegramt.me/AI_Prompt_Learn

Topic

Education — 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 17 September 2026 and assigned it the closest of 31 fixed categories, at 91% 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.

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.

Content that also appears on other registered channels

Posts published here appear in near-verbatim form on 1 other registered channel. This entry also forms a group of 2 channels linked by matching posts. 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.

Matching posts — open both and compare (1 of the pairs behind the counts below)
Posted firstThenOverlapGap
@Edu_updates_college_university/543525 May 2026, 19:05 UTC@AI_Prompt_Learn/1552 · this entry25 May 2026, 19:05 UTC1.00under a minute
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
ChannelMatching postsText overlapTypical gapPublished first
@Edu_updates_college_university5 (5/5 hand-verifiable sample passed)1.00under a minutethis entry (4–1)

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 1 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 17 comparable posts for this entry, running 27 September 2025 to 9 August 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.

  • Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
  • 'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
  • shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
  • Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).

Of the group of 2 channels, the one whose matching posts we hold earliest is @AI_Prompt_Learn — which is this entry. That is a statement about our reading window, not a claim of authorship.

Recorded under the key clone_mutual, 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.

Channels linked by matching posts

This channel is in a group of 2 registered channels linked by matching posts. Links are found by comparing text fingerprints across every channel on the register.

Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.

Growth

1,3521,3991,375.511 August 2026 — 1,399 subscribers11 August 2026 — 1,399 subscribers18 August 2026 — 1,396 subscribers22 August 2026 — 1,394 subscribers25 August 2026 — 1,395 subscribers30 August 2026 — 1,393 subscribers3 September 2026 — 1,391 subscribers8 September 2026 — 1,387 subscribers12 September 2026 — 1,382 subscribers16 September 2026 — 1,379 subscribers1 October 2026 — 1,368 subscribers8 October 2026 — 1,365 subscribers20 October 2026 — 1,362 subscribers23 October 2026 — 1,361 subscribers26 October 2026 — 1,360 subscribers29 October 2026 — 1,358 subscribers5 November 2026 — 1,356 subscribers8 November 2026 — 1,354 subscribers12 November 2026 — 1,352 subscribers11 August 202612 November 2026
19 measurements spanning 93 days, net -47. 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 1,345–1,406 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Nov 2026, 16:471,352-2
8 Nov 2026, 10:461,354-2
5 Nov 2026, 07:571,356-2
29 Oct 2026, 23:311,358-2
26 Oct 2026, 22:451,360-1
23 Oct 2026, 12:301,361-1
20 Oct 2026, 09:591,362-3
8 Oct 2026, 02:211,365-3
1 Oct 2026, 11:221,368-11
16 Sept 2026, 02:211,379-3
12 Sept 2026, 11:181,382-5
8 Sept 2026, 01:221,387-4
3 Sept 2026, 09:061,391-2
30 Aug 2026, 21:281,393-2
25 Aug 2026, 09:421,395+1
22 Aug 2026, 06:591,394-2
18 Aug 2026, 11:381,396-3
11 Aug 2026, 20:301,399no change
11 Aug 2026, 20:171,399first reading

Engagement

20 posts held, back to 27 September 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 1 page of Telegram’s post history, 20 posts per page.

Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 9 August 2026. An engagement rate over an empty window would be a number about nothing.

Reaction mix

4 reactions across 4 posts, in 1 kind.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤4100.0%

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 4 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 4 reactions 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 27 September 2025 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.

Recent posts

9 Aug 2026, 17:22 UTC39 viewsread 11 August 2026

🪪Dear All Professionals, ➖➖➖➖➖ 🔘 *Follow and Support for more and more updates* 🆓 *Journal Hub India* https://whatsapp.com/channel/0029VaiYNPf2UPB7Y308pF3f ✅*Research Cluster* https://whatsapp.com/channel/0029Vaeo4ZsLNSa2ifE5bt30 ✅*Professor's Hub India* https://whatsapp.com/channel/0029Vb7NNIv7YSdB2QqvUZ12

Signed Professor Madhav

25 Jun 2026, 18:06 UTC158 viewsread 11 August 2026

✅Research Cluster https://whatsapp.com/channel/0029Vaeo4ZsLNSa2ifE5bt30 Follow | Forword | ❤️For More

Signed Professor Madhav

22 Jun 2026, 06:54 UTC143 viewsread 11 August 2026
Forwarded from @jrf_net_set_commercePhoto

Starting today SCOPUS Blueprint Welcome to an intensive 7-Day Online Workshop is designed to take you from research design to publication strategy. 📅 Dates: 22–26 & 29–30 June 2026 ⏰ Time: 7:00 PM – 9:00 PM (IST) What You'll Learn ✅ Systematic Literature Reviews (SLR) ✅ Bibliometric Analysis Research Papers ✅ Qualitative & Quantitative Research Writing ✅ Structural Equation Modeling (SEM) Papers ✅ Mixed Methods R…

Signed Professor Madhav

1 Jun 2026, 16:28 UTC196 viewsread 11 August 2026

🪩 Get all research related updates in your WhatsApp Join our most popular whatsapp channel 👇🏻 🪪 Research Cluster https://whatsapp.com/channel/0029Vaeo4ZsLNSa2ifE5bt30

Signed Professor Madhav

25 May 2026, 19:05 UTC246 viewsread 11 August 2026

🛂 Crack NET JRF Commerce Official WhatsApp Channel https://whatsapp.com/channel/0029Vb7mDOaADTOGDVxMIQ0r 🛂 Crack NET JRF Commerce Official Telegram Channel https://t.me/jrf_net_set_commerce 🛂 Crack NET JRF Commerce Official Telegram Group https://t.me/ugc_net_commerce_management

Signed Professor Madhav

21 Mar 2026, 04:23 UTC284 views1 reactionsread 11 August 2026
Forwarded from @NET_JRF_LS

📚 🔝Best and Informative WhatsApp Channels for all kind of Exam preparation, Research, PhD Notifications, NET JRF and SRF, UGC Lectureships and Professor's of Practice. 🚀Join and Follow ━━━━━༻❁༺━━━━━ 🪪 PROFESSORS HUB https://whatsapp.com/channel/0029Vb7NNIv7YSdB2QqvUZ12 ━━━━━༻❁༺━━━━━ 🔝Research Cluster https://whatsapp.com/channel/0029Vaeo4ZsLNSa2ifE5bt30 ━━━━━༻❁༺━━━━━ 🔝Maharashtra SET https://whatsapp.com/channel/0029…

❤1

Signed Professor Madhav

26 Feb 2026, 08:19 UTC412 viewsread 11 August 2026

📢 Teaching Recruitment Updates – All in One Place! ➖➖➖➖➖ Looking for Assistant Professor / Associate Professor / Professor Jobs? 🎓 Stay ahead with real-time faculty recruitment notifications. ◼️Latest Teaching Job Updates ◼️University & College Vacancies ◼️Higher Education Alerts ◼️Instant Notifications Join Now 👇 🔔 Telegram: https://t.me/Aura_Professor_Hub 🪪 PROFESSORS HUB (WhatsApp Channel): https://whatsapp.com…

Signed The Future School

31 Jan 2026, 16:14 UTC158 viewsread 11 August 2026
Forwarded from @NET_JRF_LSPhoto

➖➖➖➖➖ युजीसी नेट #NET #JRF की पुरी तयारी के लिये अभी जॉईन करे. 🇮🇳 In this channel you can get Material about #UGC #NTA #NET #Paper-I #material #Books, #PYQ https://t.me/ugc_net_set_paper_research_apti https://t.me/ugc_net_set_paper_research_apti ➖➖➖➖➖

Signed Professor Madhav

31 Jan 2026, 16:12 UTC169 viewsread 11 August 2026
Forwarded from @NET_JRF_LSPhoto

➖➖➖➖➖ युजीसी नेट #NET #JRF की पुरी तयारी के लिये अभी जॉईन करे. 🇮🇳 In this channel you can get Material about #UGC #NTA #NET #Paper-I #material #Books, #PYQ https://t.me/ugc_net_set_paper_research_apti https://t.me/ugc_net_set_paper_research_apti ➖➖➖➖➖

Signed Professor Madhav

22 Jan 2026, 19:20 UTC415 viewsread 11 August 2026
Photo

IITGN is pleased to share that Designing Learner-Centric MOOCs, an 8-week SWAYAM–NPTEL course co-offered by Prof Sameer Sahasrabudhe (IIT Gandhinagar), Prof Sahana Murthy (IIT Bombay) and Prof Jayakrishnan M (IIT Madras), is commencing its 7th consecutive run on January 19, 2026. ➖➖➖➖➖ Join for Ai Resources https://t.me/AI_Prompt_Learn ➖➖➖➖➖ With over 1100 educators already enrolled, the course has seen strong partic…

Signed Meenaa Sonawane

13 Jan 2026, 08:29 UTC413 viewsread 11 August 2026
Photo

नई दिल्ली विश्व पुस्तक मेला 2026 में सीएसआईआर–निस्पर का पुस्तक स्टॉल विज्ञान और प्रौद्योगिकी से जुड़े विश्वसनीय और लोकप्रिय प्रकाशनों के माध्यम से ज्ञान को समाज के और अधिक निकट लाने का प्रयास है। यह पाठकों, विद्यार्थियों , शिक्षकों और विज्ञान प्रेमियों के लिए वैज्ञानिक सोच को समझने, सवाल करने और संवाद स्थापित करने का एक सार्थक अवसर है। भारत मंडपम, हॉल संख्या 6 में स्टॉल संख्या X-04 पर विज्ञान की दुनिया से जुड़ने के ल…

Signed Meenaa Sonawane

13 Jan 2026, 08:28 UTC361 viewsread 11 August 2026

नई दिल्ली विश्व पुस्तक मेला 2026 में सीएसआईआर–निस्पर का पुस्तक स्टॉल विज्ञान और प्रौद्योगिकी से जुड़े विश्वसनीय और लोकप्रिय प्रकाशनों के माध्यम से ज्ञान को समाज के और अधिक निकट लाने का प्रयास है। यह पाठकों, विद्यार्थियों , शिक्षकों और विज्ञान प्रेमियों के लिए वैज्ञानिक सोच को समझने, सवाल करने और संवाद स्थापित करने का एक सार्थक अवसर है। भारत मंडपम, हॉल संख्या 6 में स्टॉल संख्या X-04 पर विज्ञान की दुनिया से जुड़ने के ल…

Signed Meenaa Sonawane

Showing the 12 most recent of 20 posts we hold for @AI_Prompt_Learn. 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.

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 4 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.

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 November 2026 — this entry's latest reading, not the date you are reading this.

“AI Learning Resources 🌐” (@AI_Prompt_Learn), 1,352 subscribers as measured 12 November 2026. Telegram Register, tgregister.com/channel/AI_Prompt_Learn.

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.