Channel
@ConvlyAi
On this record: Topic · Growth · Engagement · Posts · Cite this entry
1,054subscribers
-17,730 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1004427728967 |
|---|---|
| Type | Channel |
| Username | @ConvlyAi |
| Created | Between 1 June 2026 and 31 July 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 11 October 2026 |
| Measurements held | 30 |
| Confirmed unchanged | 1 time, most recently 11 October 2026 |
| On Telegram | t.me/ConvlyAi |
Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 10 August 2026 and assigned it the closest of 31 fixed categories, at 100% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 11 Oct 2026, 16:57 | 1,054 | -32 |
| 5 Oct 2026, 11:39 | 1,086 | -249 |
| 27 Sept 2026, 03:58 | 1,335 | -2,366 |
| 18 Sept 2026, 05:19 | 3,701 | -1,152 |
| 13 Sept 2026, 16:00 | 4,853 | -1,570 |
| 9 Sept 2026, 12:54 | 6,423 | -1,518 |
| 4 Sept 2026, 04:36 | 7,941 | -860 |
| 1 Sept 2026, 03:56 | 8,801 | -718 |
| 29 Aug 2026, 06:25 | 9,519 | -550 |
| 28 Aug 2026, 05:34 | 10,069 | -186 |
| 27 Aug 2026, 07:28 | 10,255 | -232 |
| 26 Aug 2026, 09:34 | 10,487 | -570 |
| 25 Aug 2026, 11:53 | 11,057 | -482 |
| 24 Aug 2026, 14:16 | 11,539 | -514 |
| 22 Aug 2026, 19:19 | 12,053 | -529 |
| 21 Aug 2026, 08:58 | 12,582 | -227 |
| 20 Aug 2026, 11:37 | 12,809 | -418 |
| 19 Aug 2026, 12:45 | 13,227 | -450 |
| 18 Aug 2026, 11:03 | 13,677 | -220 |
| 17 Aug 2026, 12:28 | 13,897 | first reading |
66 posts held, back to 31 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 41 pages of 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 66 posts for this entry, the most recent from 28 August 2026. An engagement rate over an empty window would be a number about nothing.
Hugging Face Paper Pages: Daily Papers, arXiv Links, and Model Metadata A Hugging Face paper page is at huggingface.co/papers/<arXiv-ID>. Swap arxiv.org/abs/ for huggingface.co/papers/ in any arXiv URL to jump straight to it.huggingface.co/papers… https://convly.ai/hugging-face-paper/?utm_source=convly&utm_medium=social&utm_campaign=autopost
Anthropic AI Agent Hardware Standard Runs Physical Lab Experiments Anthropic has published a hardware standard intended to let AI agents operate physical machines, with early reporting pointing at scientific laboratories as the first serious use case. Here is what the announcement changes for agent developers. https://convly.ai/anthropic-ai-agent-hardware-standard-physical-machines/?utm_source=convly&utm_medium=soc…
Local LLM Models: Complete Guide to Running AI Models on Your Hardware TL;DR:Local LLM models run on your hardware without API calls. Popular options include Llama 3.1 (8B-405B), Mistral 7B, Phi-3, and Gemma 2.Use Ollama for the easiest setup (ollama … https://convly.ai/local-llm-models/?utm_source=convly&utm_medium=social&utm_campaign=autopost
Salesforce and Anthropic Launch Claudeforce AI Sales Plugin Salesforce and Anthropic have announced Claudeforce, a new AI plugin that integrates Claude's language capabilities directly into Salesforce's CRM platform for sales automation. https://convly.ai/salesforce-anthropic-claudeforce-ai-sales-plugin/?utm_source=convly&utm_medium=social&utm_campaign=autopost
LM Studio in Chicago: What the Search Means and How to Run Models Locally There is no "LM Studio Chicago" server, region, or edition. LM Studio is a desktop app for Windows, macOS and Linux; inference runs on your own CPU/GPU, so location is wherever you… https://convly.ai/lm-studio-chicago/?utm_source=convly&utm_medium=social&utm_campaign=autopost
Nvidia Q2 Earnings Pricing Power Tested After 4 Straight Beats BlackRock's Li says Nvidia has earnings pricing power going into its second-quarter report, which Yahoo Finance frames as a test of the resurgent AI trade. Here is what the framing means for anyone buying GPUs or paying for model access. https://convly.ai/nvidia-q2-earnings-pricing-power-test/?utm_source=convly&utm_medium=social&utm_campaign=autopost
Ollama and OpenClaw: How to Run OpenClaw on a Local Model There is no dedicated Ollama integration. You connect OpenClaw to Ollama through Ollama's OpenAI-compatible API at http://localhost:11434/v1, treating it as a generic OpenAI-style … https://convly.ai/ollama-openclaw/?utm_source=convly&utm_medium=social&utm_campaign=autopost
Anthropic AI Security Startup Funding Round Hits $140 Million Bloomberg reports that an AI security startup working with Anthropic and Google has raised $140 million. The report is brief, so we separate what is confirmed from the wider industry context. https://convly.ai/anthropic-ai-security-startup-140-million-round/?utm_source=convly&utm_medium=social&utm_campaign=autopost
Nvidia AI Financing Model Adds Balance Sheet Risk Nvidia's move to provide financing to AI customers has positioned it as a banker to the sector, but the arrangement introduces new credit risks to its balance sheet. https://convly.ai/nvidia-ai-financing-balance-sheet-risk/?utm_source=convly&utm_medium=social&utm_campaign=autopost
Anthropic Chases $2T IPO: How to Invest in Anthropic Anthropic is reportedly targeting a $2 trillion valuation for a potential public offering, though concerns have surfaced about its most advanced AI model. https://convly.ai/how-to-invest-in-anthropic-ipo/?utm_source=convly&utm_medium=social&utm_campaign=autopost
Safetensors: Fast and Safe Model Weight Storage Format TL;DR:Safetensors is a file format for storing machine learning model weights that prevents arbitrary code execution vulnerabilities present in pickle-based formatsIt loads 2-10× f… https://convly.ai/safetensors/?utm_source=convly&utm_medium=social&utm_campaign=autopost
vLLM Omni-Modal Support: Running Multimodal Models with vLLM "vLLM omni" almost always refers to running omni-modal models (text + vision + audio + video) on the vLLM inference server — most commonly Alibaba's Qwen2.5-Omni family.vLLM added … https://convly.ai/vllm-omni/?utm_source=convly&utm_medium=social&utm_campaign=autopost
Showing the 12 most recent of 66 posts we hold for @ConvlyAi. 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.
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 October 2026 — this entry's latest reading, not the date you are reading this.
“Convly | AI News” (@ConvlyAi), 1,054 subscribers as measured 11 October 2026. Telegram Register, tgregister.com/channel/ConvlyAi.
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.