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Channel

AI & Machine Learning & Deep Learning

@AIMLDeepThaught

On this record: Topic · Growth · Engagement · Reactions · Stars · Posts · Citations · Cite this entry

13,626subscribers

+171 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1002424966075
TypeChannel
Username@AIMLDeepThaught
CreatedBetween 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live12 October 2026
Measurements held36
Confirmed unchanged1 time, most recently 12 October 2026
On Telegramt.me/AIMLDeepThaught

Topic

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 11 September 2026 and assigned it the closest of 31 fixed categories, at 82% 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.

Growth

13,45213,62613,5397 August 2026 — 13,455 subscribers7 August 2026 — 13,455 subscribers9 August 2026 — 13,452 subscribers9 August 2026 — 13,454 subscribers10 August 2026 — 13,458 subscribers11 August 2026 — 13,463 subscribers12 August 2026 — 13,456 subscribers14 August 2026 — 13,459 subscribers15 August 2026 — 13,463 subscribers16 August 2026 — 13,466 subscribers17 August 2026 — 13,464 subscribers18 August 2026 — 13,463 subscribers19 August 2026 — 13,457 subscribers20 August 2026 — 13,464 subscribers22 August 2026 — 13,468 subscribers24 August 2026 — 13,472 subscribers25 August 2026 — 13,463 subscribers26 August 2026 — 13,458 subscribers27 August 2026 — 13,461 subscribers29 August 2026 — 13,465 subscribers30 August 2026 — 13,475 subscribers31 August 2026 — 13,487 subscribers1 September 2026 — 13,498 subscribers2 September 2026 — 13,502 subscribers3 September 2026 — 13,509 subscribers4 September 2026 — 13,511 subscribers8 September 2026 — 13,526 subscribers11 September 2026 — 13,523 subscribers13 September 2026 — 13,531 subscribers14 September 2026 — 13,535 subscribers16 September 2026 — 13,536 subscribers18 September 2026 — 13,546 subscribers25 September 2026 — 13,573 subscribers3 October 2026 — 13,598 subscribers8 October 2026 — 13,619 subscribers12 October 2026 — 13,626 subscribers7 August 202612 October 2026
36 measurements spanning 66 days, net +171. 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 13,426–13,652 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 36
Measured (UTC)SubscribersChange
12 Oct 2026, 18:3813,626+7
8 Oct 2026, 08:1513,619+21
3 Oct 2026, 18:1813,598+25
25 Sept 2026, 01:4113,573+27
18 Sept 2026, 17:4113,546+10
16 Sept 2026, 08:1913,536+1
14 Sept 2026, 14:4113,535+4
13 Sept 2026, 04:4013,531+8
11 Sept 2026, 04:1713,523-3
8 Sept 2026, 04:0013,526+15
4 Sept 2026, 23:0113,511+2
3 Sept 2026, 08:1313,509+7
2 Sept 2026, 01:5313,502+4
1 Sept 2026, 03:4913,498+11
31 Aug 2026, 02:5513,487+12
30 Aug 2026, 04:4713,475+10
29 Aug 2026, 05:5313,465+4
27 Aug 2026, 07:5313,461+3
26 Aug 2026, 05:5613,458-5
25 Aug 2026, 05:1613,463first reading

Engagement

31 posts held, back to 15 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 48 pages 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 31 posts for this entry, the most recent from 1 September 2026. An engagement rate over an empty window would be a number about nothing.

Reaction mix

223 reactions across 31 posts, in 4 distinct kinds. The most used accounts for 58.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍13158.7%
❤9040.4%
👎10.448%
👏10.448%

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 31 of the 31 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 223 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 31 most recent posts we hold, published 15 July 2026 to 1 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.

Telegram Stars

Stars received
1
across the posts below
Posts paid on
1
of 31 we hold a reading for · 3%
Most on one post
1
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @AIMLDeepThaught. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.

Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.

This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.

Counted over the 31 most recent posts we hold for this entry, published 15 July 2026 to 1 September 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.

Recent posts

1 Sept 2026, 13:58 UTC708 views3 reactionsread 2 September 2026

🚀 AI Engineer vs AI Forward Deployed Engineer (AI FDE) Confusion I keep seeing an interesting question: “Is AI FDE replacing AI Engineering?” My answer: 👉 Absolutely not. In fact, I believe AI Engineering is one of the strongest technical foundations for becoming an AI FDE. I wouldn't teach FDE as an alternative to AI Engineering. I would teach it as the next layer on top of AI Engineering. Let’s understand this thr…

❤2👍1

1 Sept 2026, 13:58 UTC757 views3 reactionsread 2 September 2026

“Does this system create measurable business value?” 🧠 THAT'S THE DIFFERENCE AI Engineer BUILD AI LLMs RAG Agents MCP Tool Calling Embeddings Vector DBs Evaluation Inference ⬇️ Production AI Engineer RUN AI Docker Cloud CI/CD LLMOps Observability Security Guardrails Scalability Cost Optimization ⬇️ AI FDE MAKE AI WORK IN THE REAL WORLD Enterprise Integration Solution Architecture Customer Discovery Business Understan…

❤2👍1

30 Aug 2026, 07:51 UTC≈1,330 views8 reactionsread 2 September 2026
File

Prompt_Engineering_for_Generative_AI_Future_Proof_Inputs_for_Reliable

👍7❤1

30 Aug 2026, 07:49 UTC≈1,330 views7 reactionsread 2 September 2026
Photo

Prompt_Engineering_for_Generative_AI_Future_Proof_Inputs_for_Reliable

👍6❤1

24 Aug 2026, 09:37 UTC≈2,430 views12 reactionsread 2 September 2026
File

💰 Building a Financial RAG Agent with DeepSeek, BGE & FAISS

👍7❤5

24 Aug 2026, 09:36 UTC≈2,260 views5 reactionsread 2 September 2026
Photo

💰 Building a Financial RAG Agent with DeepSeek, BGE & FAISS

👍5

18 Aug 2026, 13:05 UTC≈3,150 views12 reactionsread 2 September 2026

🚀 12 Powerful Methods to Detect & Handle Outliers in Data Science Outliers are not always “bad data.” They can represent errors, rare events, fraud, failures, or valuable business insights. As a Data Scientist, the key is to understand the data before deciding to remove an outlier. Here are 12 important techniques: 1️⃣ IQR Method — Great for skewed/non-normal data 2️⃣ Z-Score — Useful for approximately normal dis…

❤9👍3

18 Aug 2026, 13:04 UTC≈2,360 views7 reactionsread 2 September 2026
Photo

🚀 12 Powerful Methods to Detect & Handle Outliers in Data Science

👍5❤2

12 Aug 2026, 09:05 UTC≈3,370 views8 reactions1 Starread 2 September 2026

🚀 AI-Powered Drug Discovery: From Target Identification to Better Patient Outcomes The pharmaceutical industry is entering a new era where Artificial Intelligence (AI) is transforming the entire drug discovery and development pipeline. This infographic highlights 5 major stages where AI is creating impact: 🔬 1. Target Identification AI analyzes genomics, multi-omics, biomedical literature, and biological pathways to …

❤6👍2

Showing the 12 most recent of 31 posts we hold for @AIMLDeepThaught. 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.

Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.

Mentions

Named by 1 registered channel — 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 12 October 2026 — this entry's latest reading, not the date you are reading this.

“AI & Machine Learning & Deep Learning” (@AIMLDeepThaught), 13,626 subscribers as measured 12 October 2026. Telegram Register, tgregister.com/channel/AIMLDeepThaught.

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.