Channel
@tedvsworld
On this record: Growth · Engagement · What this channel posts · Posts · Citations · Cite this entry
3subscribers
+0 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1001833776082 |
|---|---|
| Type | Channel |
| Username | @tedvsworld |
| Created | 30 November 2022 — measured — dated from the channel’s first post |
| First recorded | 13 August 2026 |
| Last confirmed live | 22 August 2026 |
| Measurements held | 2 |
| On Telegram | t.me/tedvsworld |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 13 Aug 2026, 13:33 | 3 | no change |
| 7 Aug 2026, 08:46 | 3 | first reading |
9 posts held, back to 30 November 2022 — 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.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 9 posts for this entry, the most recent from 25 July 2023. An engagement rate over an empty window would be a number about nothing.
Lifetime counters from Telegram’s own channel header, read 13 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.
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🤖 Stability AI releases 2 new open-source LLMs Stability AI has released FreeWilly1 and FreeWilly2, two open-source Large Language Models developed by its own CarperAI lab. Details: Both models excel in reasoning and understanding linguistic subtleties, validated through various benchmarks. The data generation process was inspired by Microsoft's methodology, using high-quality instructions from specific datasets.…
🤖 Stability AI releases 2 new open-source LLMs Stability AI has released FreeWilly1 and FreeWilly2, two open-source Large Language Models developed by its own CarperAI lab. Details: Both models excel in reasoning and understanding linguistic subtleties, validated through various benchmarks. The data generation process was inspired by Microsoft's methodology, using high-quality instructions from specific datasets.…
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🤖 Stability AI releases 2 new open-source LLMs Stability AI has released FreeWilly1 and FreeWilly2, two open-source Large Language Models developed by its own CarperAI lab. Details: Both models excel in reasoning and understanding linguistic subtleties, validated through various benchmarks. The data generation process was inspired by Microsoft's methodology, using high-quality instructions from specific datasets.…
Meta just released CM3leon The new generative AI model that performs both text-to-image and image-to-text generation. Key points: It can generate sequences of text and images conditioned on any given sequence of other image and text content Performance for text-to-image generation uses 5x times less compute power than previous transformer-based methods Generates captions and answers any image-related question I…
🤖 Meta and Microsoft team up and release Llama 2 Meta has open-sourced its large language model, Llama 2, which rivals ChatGPT in chat quality, albeit with less coding proficiency. Meta has implemented safety measures including context distillation and RLHF, following extensive evaluations. Commercial use is permitted barring products with over 700 million monthly users. In a surprising move, Meta has partnered wit…
Channel created
Showing the 9 most recent of 9 posts we hold for @tedvsworld. 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.
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.
Names
Channels on the register whose handles appear in this channel's posts.
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 13 August 2026 — this entry's latest reading, not the date you are reading this.
“tedvsworld” (@tedvsworld), 3 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/tedvsworld.
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.