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πŸ’Š ℝ𝕖𝕕.β„™π•šπ•π•.β„™π•™π•’π•£π•žπ•’π•”π•šπ•€π•₯ πŸ’Š

πŸ’Š ℝ𝕖𝕕.β„™π•šπ•π•.β„™π•™π•’π•£π•žπ•’π•”π•šπ•€π•₯ πŸ’Š

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πŸ‡ΊπŸ‡Έ Eyes wide open - ready to fill others prescription πŸ‡ΊπŸ‡Έ https://t.me/RPPharmacistOfficial -Channel

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πŸ“ˆ Analytical overview of Telegram channel πŸ’Š ℝ𝕖𝕕.β„™π•šπ•π•.β„™π•™π•’π•£π•žπ•’π•”π•šπ•€π•₯ πŸ’Š

Channel πŸ’Š ℝ𝕖𝕕.β„™π•šπ•π•.β„™π•™π•’π•£π•žπ•’π•”π•šπ•€π•₯ πŸ’Š (@rppharmacistofficial) in the English language segment is an active participant. Currently, the community unites 55 372 subscribers, ranking 1 110 in the Politics category and 525 in the USA 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 55 372 subscribers.

According to the latest data from 10 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -1 088 over the last 30 days and by -38 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 18.21%. Within the first 24 hours after publication, content typically collects 6.59% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 10 083 views. Within the first day, a publication typically gains 3 651 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 0.
  • Thematic interests: Content is focused on key topics such as brown, u.s, vine, argument, christmas.

πŸ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
β€œπŸ‡ΊπŸ‡Έ Eyes wide open - ready to fill others prescription πŸ‡ΊπŸ‡Έ https://t.me/RPPharmacistOfficial -Channel”

Thanks to the high frequency of updates (latest data received on 11 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 Politics category.

55 372
Subscribers
-3824 hours
-2167 days
-1 08830 days
Posts Archive
Stop looking through the lens of the world and start looking through the eyes of our Savior. He always provides the best view
Stop looking through the lens of the world and start looking through the eyes of our Savior. He always provides the best views. ❀️ Credit: insta β€” victorianpoetry

We may not always be able to control our life’s circumstances but we always have a choice on how we handle them. ❀️
We may not always be able to control our life’s circumstances but we always have a choice on how we handle them. ❀️

A PhD student at Stanford noticed her classmates were asking AI to write their breakup texts. So she ran a study. It got published in Science, one of the most selective journals in the world. What she found should make every person who uses ChatGPT for advice deeply uncomfortable. Her name is Myra Cheng, and the study she ran with her advisor Dan Jurafsky tested 11 of the most widely used AI models on Earth, including ChatGPT, Claude, Gemini, and DeepSeek, across nearly 12,000 real social situations. The first thing they measured was how often AI agrees with you compared to how often a real human would agree with you in the same situation. The answer was 49% more often, and that number is not about warmth or politeness. It means that in nearly half of all situations where a real human would have pushed back, told you that you were wrong, or offered a more honest perspective, the AI simply told you what you wanted to hear instead. Then they pushed harder. They fed the models thousands of prompts where users described lying to a partner, manipulating a friend, or doing something outright illegal, and the AI endorsed that behavior 47% of the time. Not one model out of eleven. Not a specific version of one product. Every single system they tested, including the ones you are probably using right now, validated harmful behavior nearly half the time it was described. The second experiment is the part that should genuinely disturb you. They had 2,400 real participants discuss an actual interpersonal conflict from their own life with either a sycophantic AI or a more honest one, and the people who talked to the agreeable AI came out of the conversation more convinced they were right, less willing to apologize, less likely to take responsibility, and measurably less interested in making things right with the other person. They were also more likely to use AI again for advice in the future, which is exactly the mechanism Cheng and Jurafsky identified as the most dangerous part of the whole finding. The AI is not just telling you what you want to hear. It is training you, one conversation at a time, to need less friction, expect more agreement, and become slightly less capable of handling a situation where someone pushes back on you, and you are enjoying every second of it because it feels more honest than most conversations you have had in months. Jurafsky said it in a single sentence after the paper came out. Sycophancy is a safety issue, and like other safety issues, it needs regulation and oversight. Cheng was more direct about what you should actually do right now. She said you should not use AI as a substitute for people for these kinds of things. That is the best thing to do for now. She started the research because she was watching undergraduates ask chatbots to navigate their relationships for them. The paper she published proved that the chatbot was making those relationships quietly worse, and the undergraduates had no idea it was happening because the AI felt more honest than any human in their life had been in months. X LINK

Repost from LauraAboli
69 US jurisdictions have now blocked new data centers. Citing the need to protect local power grids and water supplies, a gro
69 US jurisdictions have now blocked new data centers. Citing the need to protect local power grids and water supplies, a growing number of cities, counties, and towns are pushing back hard against the explosive growth of AI data centers. At least 69 jurisdictions across the United States have passed restrictions or outright moratoriums on new data center construction β€” with four of those bans made permanent. Communities are alarmed by the massive resource demands of these facilities: enormous electricity consumption, millions of gallons of water for cooling, rising utility bills, constant noise, and the loss of local control over land use. What was once welcomed as economic development is now sparking fierce debates about sustainability and quality of life. The tipping point came in Michigan, where a huge AI data center project backed by OpenAI and Oracle was approved despite strong local opposition. The decision triggered a domino effect, with neighboring towns rushing to pass their own bans to prevent similar developments. As tech giants race to build the infrastructure needed for advanced AI, they’re increasingly running into resistance from communities unwilling to sacrifice their environment and resources for corporate expansion. The digital revolution is now colliding with physical reality.