Telegram RegisterThe public register of Telegram

Channel

Data&AI Insights

@data_ai_insights

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

277subscribers

+0 since we began measuring on 11 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1002166879417
TypeChannel
Username@data_ai_insights
DescriptionНовости про данные и AI. И не только.
CreatedBetween 1 June 2024 and 30 September 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded11 August 2026
Last confirmed live11 August 2026
Measurements held2
On Telegramt.me/data_ai_insights

Growth

27711 Aug 2026, 00:17 — 277 subscribers11 Aug 2026, 00:30 — 277 subscribers11 Aug 2026, 00:1711 Aug 2026, 00:30
2 measurements taken within a single day. 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 276–278 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
11 Aug 2026, 00:30277no change
11 Aug 2026, 00:17277first reading

Engagement

20 posts held, back to 7 August 2026the 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 · 30 days
9.31%
avg views ÷ 277 subscribers
Avg views / post
25.8
20 posts measured
Reaction rate
12.2%
reactions ÷ views · ER floor
Posts in window
20
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.

What these figures were computed from
WindowRolling 30 days · latest post in window 10 August 2026
Posts held20 (7 August 202610 August 2026)
Views total516
Reactions total63
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken11 Aug 2026, 00:30 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.

What this channel posts

Photos
99
Videos
19
Links
2,220

Lifetime counters from Telegram’s own channel header, read 11 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.

Reaction mix

63 reactions across 20 posts, in 3 distinct kinds. The most used accounts for 61.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥3961.9%
👍2234.9%
😱23.17%

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 20 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 August 2026 to 10 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

10 Aug 2026, 08:30 UTC20 views3 reactionsread 11 August 2026
File

🔗 Evaluating Offshore AI Development Teams: Technical Expertise - Freedium 📖 tgf 🖼Post cover image ✏ Краткое введение 🖼 Статья от 14 июля 2026 года посвящена оценке офшорных команд разработки искусственного интеллекта, прежде всего с точки зрения их технической экспертизы. Автор объясняет, что при выборе офшорного центра разработки ИИ недостаточно ориентироваться только на стоимость: важно проверить опыт, навыки

🔥2👍1

10 Aug 2026, 08:00 UTC21 views3 reactionsread 11 August 2026
File

🔗 6 Data Observability Patterns Spotify and Airbnb Use to Catch Failures Before Finance Does - Freedium 📖 tgf 📌 6 паттернов наблюдаемости данных, которые Spotify и Airbnb используют, чтобы ловить сбои до того, как их заметит финансисты 🖼Post cover image ✏ Краткое введение [Полное описание в прикрепленном файле] #DataQuality #dataengineering #dataops

🔥2👍1

10 Aug 2026, 07:30 UTC23 views3 reactionsread 11 August 2026
File

🔗 Is Data Mesh Dead? Lakehouse vs Data Fabric vs Medallion — A Layer Model - Freedium 📌 Саммари статьи «Is Data Mesh Dead? Lakehouse vs Data Fabric vs Medallion — A Layer Model» 🖼Post cover image ✏ 1. Краткое введение 🖼 [Полное описание в прикрепленном файле] #architecture #datainfrastructure #databricks

🔥2👍1

10 Aug 2026, 07:00 UTC21 views3 reactionsread 11 August 2026
File

🔗 What Genie Ontology Actually Automates, and What It Leaves to You - Freedium 📌 Что автоматизирует Genie Ontology и что оставляет вам ✏ Краткое введение 🖼Post cover image 🖼 Статья посвящена Databricks Genie Ontology и тому, какие именно задачи контекстной инженерии он автоматизирует, а какие остаются команде. Основной тезис: новый контекстный слой забирает две из четырех работ — Write и Select, — но не заменяет

🔥2👍1

10 Aug 2026, 06:30 UTC22 views3 reactionsread 11 August 2026
File

🔗 From Gold Tables to Data Products: Redefining the Medallion Contract - Freedium 📌 From Gold Tables to Data Products: Redefining the Medallion Contract 🖼Post cover image ✏ 1. Краткое введение Статья Santosh Shinde от 14 июля 2026 года развивает тему пересмотра medallion-архитектуры и утверждает, что разрыв между Silver и Gold — это не отсутствующий слой, а отсутствующий контракт. Материал является второй частью

🔥2👍1

10 Aug 2026, 06:00 UTC24 views3 reactionsread 11 August 2026
File

🔗 Observability for the Agentic AI Harness - Freedium ✏ Краткое введение 🖼Post cover image Статья Observability for the Agentic AI Harness от 4 августа 2026 года посвящена тому, как строить наблюдаемость для агентных ИИ-систем корпоративного уровня. Основной тезис: создание самих агентов становится всё более простым, а главной сложностью становится их надёжный запуск в масштабе. Поэтому фокус смещается с отдельной

🔥2👍1

9 Aug 2026, 16:00 UTC28 views3 reactionsread 11 August 2026
File

🔗 Best AI Semantic Layer Tools (2026): Connecting Data Models to LLMs - Freedium 📖 tgf 📌 Лучшие инструменты AI Semantic Layer в 2026 году ✏ Введение 🖼Обложка статьи [Полное описание в прикрепленном файле] #AI #llm #datamodeling

🔥2👍1

9 Aug 2026, 15:30 UTC29 views3 reactionsread 11 August 2026
File

🔗 Anthropic is telling you that Agentic Analytics is not just text-to-SQL - Freedium 📖 tgf 📌 Agentic Analytics — это не text-to-SQL: уроки архитектуры Anthropic с точностью 95% Anthropic опубликовала пост «How Anthropic enables self-service data analytics with Claude» (3 июня 2026), в котором описала, как их агентная аналитическая система достигла 95% точности. Автор разбора, Jose Parreño, подчёркивает ключевой те

👍2🔥1

9 Aug 2026, 15:00 UTC28 views3 reactionsread 11 August 2026
File

🔗 Lightdash — BI, который живёт внутри вашего dbt‑проекта / Хабр 📖 tgf 📌 Lightdash — BI, который живёт внутри вашего dbt-проекта ✏ Суть подхода: метрики как код Аналитик из BIGDATAHOUSE на своих проектах использует связку dbt (де-факто стандарт трансформации данных) и Superset в качестве BI. Со временем бизнес-логика неизбежно размывается: одна её часть живёт в dbt, другая — в настройках BI, и отслеживать расхожд

🔥2👍1

9 Aug 2026, 07:30 UTC29 views4 reactionsread 11 August 2026
File

🔗 An AI Designed 16 Viruses That Have Never Existed in Nature. Here Is the Full Story. - Freedium 📌 ИИ создал 16 вирусов, никогда не существовавших в природе: полный разбор 🖼Обложка статьи ✏ Краткое введение [Полное описание в прикрепленном файле] #AI #биология #медицина

😱2👍1🔥1

9 Aug 2026, 07:00 UTC27 views3 reactionsread 11 August 2026
File

🔗 Orchard: The Missing Layer for AI Agents - Freedium 📖 tgf 📌 Orchard: недостающий слой для AI-агентов 🖼Обложка поста ✏ Введение 4 августа 2026 года Microsoft Research выпустила Orchard — открытый фреймворк для обучения AI-агентов, который отличается от типичных новостей года о «больших моделях, длинных контекстных окнах и быстром инференсе». Вместо улучшения самих моделей Orchard решает проблему, которую почти

🔥2👍1

9 Aug 2026, 06:30 UTC28 views3 reactionsread 11 August 2026
File

🔗 I Hardly Open Excel Anymore - Freedium 📖 tgf 📌 I Hardly Open Excel Anymore — как автоматизировать обработку данных и отчёты с помощью Pandas ✏ Введение Автор статьи — инженер в области интегральных схем — рассказывает, как заменил рутинную работу в Excel на автоматизацию через Python и библиотеку Pandas. Раньше он уже описывал, как использует pandoc для генерации документов и PowerPoint-презентаций; теперь речь

🔥2👍1

Showing the 12 most recent of 20 posts we hold for @data_ai_insights. 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 — 999,335 of 1,345,403entries 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.

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.

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

“Data&AI Insights” (@data_ai_insights), 277 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/data_ai_insights.

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.