Telegram RegisterThe public register of Telegram

Channel

Artificial Intelligence | ChatGPT AI | Data Science & Machine Learning

@aichads

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

22,798subscribers

+43 since we began measuring on 6 August 2026

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

Register entry

Telegram ID-1002135881900
TypeChannel
Username@aichads
CreatedBetween 1 November 2023 and 31 May 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live13 August 2026
Measurements held8
Confirmed unchanged1 time, most recently 13 August 2026
On Telegramt.me/aichads

Growth

22,75522,79822,776.56 August 2026 — 22,755 subscribers7 August 2026 — 22,757 subscribers8 August 2026 — 22,763 subscribers8 August 2026 — 22,769 subscribers9 August 2026 — 22,773 subscribers10 August 2026 — 22,787 subscribers11 August 2026 — 22,790 subscribers13 August 2026 — 22,798 subscribers6 August 202613 August 2026
8 measurements spanning 6 days, net +43. 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 22,749–22,804 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
13 Aug 2026, 00:0422,798+8
11 Aug 2026, 21:5522,790+3
10 Aug 2026, 23:3422,787+14
9 Aug 2026, 23:4322,773+4
8 Aug 2026, 21:4322,769+6
8 Aug 2026, 00:0322,763+6
7 Aug 2026, 02:3422,757+2
6 Aug 2026, 14:4822,755first reading

Engagement

20 posts held, back to 7 May 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 17 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
3.94%
avg views ÷ 22,798 subscribers
Avg views / post
899
4 posts measured
Reaction rate
0.36%
reactions ÷ views · ER floor
Posts in window
4
of 20 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 2 of 4 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 4 August 2026
Posts held20 (7 May 20264 August 2026)
Views total3,595
Reactions total6
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken12 Aug 2026, 22:55 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.

Reaction mix

63 reactions across 17 posts, in 4 distinct kinds. The most used accounts for 88.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
5688.9%
🔥46.35%
👍23.17%
👏11.59%

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 17 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 63reactions 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 7 May 2026 to 4 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

4 Aug 2026, 11:14 UTC547 views2 reactionsread 12 August 2026

5 Free Courses to Go From AI Beginner to Practitioner 1️⃣ Harvard CS50: Introduction to AI with Python 🎓 Learn the fundamentals of AI before diving into machine learning. Build AI projects like Tic-Tac-Toe, search algorithms, and logic solvers while mastering core AI concepts. 👉 Click Here: https://cs50.harvard.edu/ai/ 2️⃣ Google Machine Learning Crash Course 📊 Google's official ML course teaches gradient descent,

2

24 Jul 2026, 09:42 UTC≈1,120 views4 reactionsread 12 August 2026

✅ Top Artificial Intelligence Concepts You Should Know 🤖🧠 🔹 1. Natural Language Processing (NLP) Use Case: Chatbots, language translation → Enables machines to understand and generate human language. 🔹 2. Computer Vision Use Case: Face recognition, self-driving cars → Allows machines to "see" and interpret visual data. 🔹 3. Machine Learning (ML) Use Case: Predictive analytics, spam filtering → AI learns patterns f

4

23 Jul 2026, 06:35 UTC848 viewsread 12 August 2026
Photo

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16 Jul 2026, 08:55 UTC≈1,080 viewsread 12 August 2026
Photo

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2 Jul 2026, 17:39 UTC≈1,550 views1 reactionsread 12 August 2026

🎯 Step by step AI and ML roadmap with a YouTube playlist 👇 Step 1 - Python programming: https://youtu.be/eirjjyP2qcQ?si=KuAvg-DuKxMkD7jR Step 2 - Foundation of AI/ML: https://youtu.be/VOpETRQGXy0?si=mfJ86zEFHv2VqGrb Step 3 - Data Science: https://youtu.be/fM4qTMfCoak?si=AhpjlpEmRAQh9k0g Step 4 - Gen AI + LLM foundation: https://youtu.be/pSVk-5WemQ0?si=7tb-RGCSxwrXV5E2 Step 5 - LangChain + LangGraph: https://yout

1

1 Jul 2026, 16:54 UTC≈1,330 views1 reactionsread 12 August 2026
Photo

🐶 ASO Corgi — platform for the App Store developers. Find the keywords your apps and competitors rank for, and track positions across every country in one place. 🔑 Keyword research: by topic, by your app's languages, from App Store suggestions, by competitors, and with AI analysis. • Rankings by country — history, charts, demand score (0–100) • Global search across any App Store storefront • ASO assistant builds you

1

26 Jun 2026, 16:07 UTC≈1,320 views1 reactionsread 12 August 2026

AI agents are no longer just a developer toy. OpenAI published new research on how agents are changing work, and the main takeaway is important: AI is moving from short chat interactions to delegated long-horizon tasks. That sounds abstract, but here is the simple version: Old way: ask AI one question, get one answer. New way: give AI a task, let it work for minutes or hours, review the result. This is the shif

1

19 Jun 2026, 16:19 UTC≈1,320 views5 reactionsread 12 August 2026
Photo

🤖 Anthropic updates Claude Design with brand style sync Anthropic's Claude Design now integrates your design system directly from repositories, design files, or codebases to maintain your brand style across projects. It builds interfaces using your real components and checks compliance before you see the result. The editor is more stable for daily use and adds new layout controls. You can drag, resize, and align el

5

15 Jun 2026, 20:14 UTC≈1,380 views2 reactionsread 12 August 2026

✅ Today's AI News 1️⃣ AI regulation is tightening Reuters reports fresh pressure on xAI, OpenAI, and Anthropic, with lawsuits, access restrictions, and national-security concerns all in focus. 2️⃣ Big tech spending on AI is still huge Microsoft’s AI infrastructure push, Google’s Gemini updates, and broader platform expansion remain major parts of the story. 3️⃣ AI is reshaping business models The Economist highlig

2

10 Jun 2026, 18:41 UTC≈1,580 views5 reactionsread 12 August 2026

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5

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

Citation-graph rank

Citation-graph rank — 907,532 of 1,151,006entries 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.

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

“Artificial Intelligence | ChatGPT AI | Data Science & Machine Learning” (@aichads), 22,798 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/aichads.

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.