Channel
@ilquinta
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
300subscribers
+0 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1001550565694 |
|---|---|
| Type | Channel |
| Username | @ilquinta |
| Created | Between 1 July 2021 and 31 January 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 7 August 2026 |
| Measurements held | 2 |
| Confirmed unchanged | 1 time, most recently 7 August 2026 |
| On Telegram | t.me/ilquinta |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 7 Aug 2026, 07:26 | 300 | no change |
| 6 Aug 2026, 23:48 | 300 | first reading |
20 posts held, back to 29 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 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 4 of 20 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 6 August 2026 |
|---|---|
| Posts held | 20 (29 July 2026 – 6 August 2026) |
| Views total | 2,154 |
| Reactions total | 3 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 6 Aug 2026, 23:48 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.
3 reactions across 3 posts, in 2 distinct kinds. The most used accounts for 66.7% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 2 | 66.7% | |
| 😡 | 1 | 33.3% |
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 3reactions 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 29 July 2026 to 6 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.
Restaurants, pubs and theatres ban Meta’s ‘spy glasses’ over privacy fears | Meta | The Guardian August 6, 2026 Bravi!!! But those plans have hit a snag in the UK, where venues from elite restaurants to popular pub chains have banned the £359 glasses in order to preserve the privacy of customers and staff. Source: Restaurants, pubs and theatres ban Meta’s ‘spy glasses’ over privacy fears | Meta | The Guardian …
Microsoft Tells Engineers ‘Tokenmaxxing Is Not What We Are Optimizing For’ August 5, 2026 “fate qualcosa di utile” Prompt: creami un clone di arkanoid che giri silla mia vecchia console TI99/4A “As we accelerate our use of GitHub Copilot to deliver on our goals, we all need to be aware of how we consume tokens,” Jay Parikh, an executive vice president at Microsoft said in an email… 📢 @ilquinta
Flock Misread License Plates in 71% of Alerts It Sent Roseville Police – Business Insider August 4, 2026 “In condizioni ottimali”. Flock says that in optimal conditions, its cameras accurately read more than 96% of license plate characters. Hundreds of pages of records from the Roseville Police Department show a different picture. In 2023 and 2024, Flock sent 1,427 alerts to Roseville police, flagging vehicles as…
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Raiding the Genome: How the United States Government Is Abusing Its Immigration Powers to Amass DNA for Future Policing | Center on Privacy and Technology | Georgetown Law August 4, 2026 Gli USA ce la mettono tutta per diventare come la Cina Alla base buona parte delle persone che ci finiscono dentro è per ragioni di pantone. Since the first Trump administration changed the rules on DNA collection at DHS, the nu…
‘Own the Narrative’: Leaked Flock Guide Shows How It Teaches Cops to Promote Its Tech August 4, 2026 “If you build it, they will come” (proverbio) Se lo costruisci, sarà usato. All’inizio per terroristi, pedofili, reati contro l’amministrazione, poi squadracce, interruzioni di gravidanza, stalking di contestatori,.. These include the fact that Flock data was regularly making its way to Immigrations and Custom…
DeepSeek V4 Flash 0731 (max) – Intelligence, Performance & Price Analysis August 4, 2026 Sul sito tutte le analisi. Non so quanto siano da prendere alla lettera, o più che altro come indicazione “largo circa” DeepSeek V4 Flash 0731 (Reasoning, Max Effort) is amongst the leading models in intelligence and well priced when comparing to other open weight models of similar size. It’s also notably fast, however… 📢 @…
Prompt Injection as Role Confusion August 4, 2026 Devo ammettere che a questo non avevo pensato. Forse, andando avanti, i testi provenienti dal sistema saranno firmati digitalmente. O qualche altro meccanismo che su due piedi non mi viene in mente… Let’s build an attack. Standard prompt injections hide user-sounding commands in tool data. The LLM mistakes them for real user instructions… 📢 @ilquinta
Context Collapse, Part 3 – AI Worming through Word | En Klype Salt – I virus degli LLM (2) August 4, 2026 Leggi la parte 1 con le considerazioni generali su questo tipo di attacchi An attacker places hidden instructions in a document that is later used as source material in Copilot for Word. Copilot may interpret those instructions as part of the user’s request, causing it to manipulate the document being drafted…
[2403.02817] Here Comes The AI Worm: Unleashing Zero-click Worms that Target GenAI-Powered Applications August 4, 2026 Non so se vi avevo raccontato che nella seconda meta’ degli anni 80 mi occupavo di virus. Conobbi anche Morris, quello del worm. Il mio primo articolo scientifico pubblicato su “Note di Software” del dipartimento di scienze dell’informazione dell’università di milano si intitolava “sistemi autore…
28×2026 Podcast:Central Park – My love in the dark August 3, 2026 Lanfranco Palazzolo (Radio Radicale) intervista @quinta – Tech e Regole Podcast https://castopod.it/@quinta/episodes/28×2026-central-park-my-love-in-the-dark - USA – l’avvocato che bacia - Libri – il “Destructive Scanning” - Il decreto legislativo sul riconoscimento facciale - App della settimana – Curve Pay - Prove del DNA a rischio? - AI-Act – la …
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The ban on robot vacuums won’t make them safer, only worse | The Verge August 3, 2026 “Puro Vangelo” (cit.) No other gadget knows as much about your home as a robot vacuum. They map your space, learn your routines, and many now carry a camera and microphone into every room in your house. As AI gives them a better understanding of what they see, the privacy and security risks… 📢 @ilquinta
Azione, correlazione ? August 3, 2026 Il 17 luglio, 2 settimane fa, per interessi di sicurezza nazionale USA e come finanziamenti militari all’estero, approvato lo stanziamento di 40M al Marocco re. lo stato futuro di Ceuta e Melilla, “città amministrate dalla Spagna ubicate nel territorio del Marocco”. H.R. 8595 – National Security, Department of State, and Related Programs Appropriations… 📢 @ilquinta
Showing the 12 most recent of 20 posts we hold for @ilquinta. 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 — 219,889 of 1,160,990entries 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.
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.
Named by 3 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.
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.
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 7 August 2026 — this entry's latest reading, not the date you are reading this.
“Stefano Quintarelli Weblog” (@ilquinta), 300 subscribers as measured 7 August 2026. Telegram Register, tgregister.com/channel/ilquinta.
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.