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AI & Deep Learning

AI & Deep Learning

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All about Deep Learning, LLMs #deeplearning #deep_learning #AI #ML Follow for quality content amid all the noise in #AI.

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πŸ“ˆ Analytical overview of Telegram channel AI & Deep Learning

Channel AI & Deep Learning (@deeplearning005) in the English language segment is an active participant. Currently, the community unites 10 574 subscribers, ranking 11 565 in the Technologies & Applications category and 38 093 in the India region.

πŸ“Š Audience metrics and dynamics

Since its creation on Π½Π΅Π²Ρ–Π΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 10 574 subscribers.

According to the latest data from 27 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 266 over the last 30 days and by 2 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 13.41%. Within the first 24 hours after publication, content typically collects 2.62% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 1 417 views. Within the first day, a publication typically gains 277 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 6.
  • Thematic interests: Content is focused on key topics such as developer, openai.

πŸ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
β€œAll about Deep Learning, LLMs #deeplearning #deep_learning #AI #ML Follow for quality content amid all the noise in #AI.”

Thanks to the high frequency of updates (latest data received on 28 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.

10 574
Subscribers
+224 hours
+827 days
+26630 days
Posts Archive
https://auto-rt.github.io In this paper, we propose AutoRT, a system that leverages existing foundation models to scale up th
https://auto-rt.github.io In this paper, we propose AutoRT, a system that leverages existing foundation models to scale up the deployment of operational robots in completely unseen scenarios with minimal human supervision. AutoRT leverages vision-language models (VLMs) for scene understanding and grounding, and further uses large language models (LLMs) for proposing diverse and novel instructions to be performed by a fleet of robots

GitHub - black-forest-labs/flux: Official inference repo for FLUX.1 models https://github.com/black-forest-labs/flux

Final rankings (as of July 17, 2024): 1️⃣ OpenAI (1,287) 2️⃣ Anthropic (1,271) 3️⃣ Google (1,267) 4️⃣ DeepSeek (1,222) 5️⃣ Meta (1,207) 6️⃣ Mistral (1,157)

A very nice video, must watch if you are into Machine Learning Algorithms. ====== The moment we stopped understanding AI [AlexNet] https://www.youtube.com/watch?v=UZDiGooFs54

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