Channel
@TheInfinityAI
On this record: Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Citations · Cite this entry
400subscribers
-2 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1002941557658 |
|---|---|
| Type | Channel |
| Username | @TheInfinityAI |
| Description | Exploring the world of CS, AI, and ML 🧠. Sharing high-quality resources, tools, and interesting tech breakthroughs daily. Join us to learn and build together! |
| Created | Between 1 August 2025 and 31 October 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 8 August 2026 |
| Last confirmed live | 8 August 2026 |
| Measurements held | 3 |
| On Telegram | t.me/TheInfinityAI |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 8 Aug 2026, 05:48 | 400 | no change |
| 8 Aug 2026, 00:57 | 400 | -2 |
| 7 Aug 2026, 18:26 | 402 | first reading |
20 posts held, back to 15 June 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 1 pageof 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 3 of 11 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 8 August 2026 |
|---|---|
| Posts held | 20 (15 June 2026 – 8 August 2026) |
| Views total | 9,691 |
| Reactions total | 5 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 8 Aug 2026, 05:48 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 8 August 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.
17 reactions across 7 posts, in 4 distinct kinds. The most used accounts for 52.9% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 9 | 52.9% | |
| 🎉 | 3 | 17.6% | |
| 👾 | 3 | 17.6% | |
| 🤣 | 2 | 11.8% |
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 9 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 17reactions 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 15 June 2026 to 8 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.
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @TheInfinityAI. 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 20 most recent posts we hold for this entry, published 15 June 2026 to 8 August 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.
Article 35: Attention Mechanisms and Transformers ⚡️🤖🧠 In 2017, Google published the famous paper "Attention Is All You Need." It introduced the Transformer which replaced RNNs and LSTMs entirely. Transformers can process an entire sentence at the exact same time (parallel processing), making them much faster and more accurate. 1. What is Attention? 👀🔍 When you read a sentence like: "The animal didn't cross the st…
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Article 34: Sequence Modeling – RNN, LSTM, and GRU 🧠📚 Standard Neural Networks assume that all inputs and outputs are independent of each other. But in language, the word "bank" means something different depending on the previous words ("river bank" vs. "money bank"). Sequence models have a memory to remember past information. 1. Recurrent Neural Networks (RNNs) 🔄 An RNN processes a sequence one step at a time. It…
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More more more short plz
🤣2
Neural Networks & Deep Learning 🧠📚 Want to master Deep Learning from the ground up? This PDF contains comprehensive notes covering the complete DeepLearning. Save this PDF and keep it as your Deep Learning handbook! #AI #MachineLearning #DeepLearning #NeuralNetworks #CNN #RNN #LSTM #Python #DataScience #ArtificialIntelligence #AndrewNg #DeepLearningAI #ComputerVision #NLP #LearnAI @TheInfinityAI
Article 33: Computer Vision – Convolutional Neural Networks (CNNs) 📷🧠 Standard Neural Networks are bad at processing images because an image has thousands or millions of pixels. If you flatten an image into a 1D vector, you lose all spatial information (where pixels are relative to each other). CNNs solve this problem by keeping the 2D grid structure intact. ✅ 1. The Core Idea: Spatial Features 🎯 When a human look…
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Electricity is optional 🌚
🎉3
Article 32: Neural Network Foundations – How Machines Learn 🧠 A Neural Network is a mathematical model inspired by the neurons in a human brain. While a simple model like Linear Regression finds a straight line, a Neural Network can find any complex shape in data. 1. The Structure of a Neural Network A network consists of layers of Neurons, Input Layer - receives the raw data (like pixels of an image or numbers in…
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Posted without readable text
Showing the 12 most recent of 20 posts we hold for @TheInfinityAI. 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.
Republishes
Channels on the register whose posts this channel has forwarded.
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.
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 8 August 2026 — this entry's latest reading, not the date you are reading this.
“Infinity CS” (@TheInfinityAI), 400 subscribers as measured 8 August 2026. Telegram Register, tgregister.com/channel/TheInfinityAI.
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.