In the midst of the establishment trying to intimidate communities who don't want the data center monstrosities near their homes, several people across the country are successfully defeating the agenda and, in some cases, banning data centers altogether! Kristen and Tammy join us to discuss exactly how they're doing it and how you can too.

AIRING NOW: https://rumble.com/v7avjfi-how-americans-defeat-data-centers-daily-pulse-ep-267.html

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Do you know the documented history of decades of illegal Israeli government spying on Washington? Well, you're about to! Strap in and get ready.

via The Corbett Report https://ift.tt/uGxFbh4

wmiddelkoop:

RT @RnaudBertrand: So I spent some time studying the new Twitter/X algorithm today since the latest version was published about a week ago on Github (https://t.co/3jzdav3Ywp).

My goal was to answer why so many people have seemingly seen such a dramatic drop in their posts' reach.

The first answer, which is actually somewhat unrelated to the ranking algorithm on Github, is the auto-translate feature, rolled out worldwide on April 7, 2026 (https://t.co/YtGomG9RGz).

Before that date, if you wrote in English about, say, the Trump-Xi Beijing summit, you were competing for attention with maybe 5,000 other English-language accounts writing on geopolitics.

After that date, your post is competing for attention with other posts on the same topic IN EVERY LANGUAGE ON EARTH. For some topics that do command global attention like geopolitics, that's a very brutal multiplier: you used to be one of 5,000, you're suddenly one of 50,000 (something of that order): MUCH more difficult to stand out.

Secondly, the number of followers you have matters far less than it used to: each post now has to earn its audience reader by reader, on the predicted engagement of the post, and how its topic matches what each reader has recently been engaging with.

Here is how the algorithm works, in simple terms: when you, as a reader, open your feed, the algorithm doesn't load "posts from accounts you follow." Instead it runs a 2-stage prediction of what posts you're likely to engage with in that very moment.

The first stage is the retrieval stage. The system narrows billions of posts on X/Twitter that day down to roughly 1,500 candidates by matching the semantic content of each post - what it's about - against what you as a reader have recently engaged with. Some candidate posts come from accounts you follow; others are pulled from across the platform by pure topic similarity to your recent interests.

You can test this retrieval stage easily: start disproportionally engaging with - say - Brad Pitt videos and you'll bit by bit see your timeline flooded with Brad Pitt content, most of it from accounts you've never followed and never heard of.

Then there's the ranking stage. Each of these candidate posts for your feed is fed through a Grok-based model that tries to understand if you'll engage with the post.

It looks at 15 engagement metrics:
1) P(favorite) — the reader likes the post
2) P(reply) — the reader replies to it
3) P(repost) — the reader reposts it
4) P(quote) — the reader quote-tweets it
5) P(click) — the reader clicks a link in it
6) P(profile_click) — the reader taps through to your profile
7) P(video_view) — the reader watches the video
8) P(photo_expand) — the reader expands an image
9) P(share) — the reader shares it (DM, off-platform, etc.)
10) P(dwell) — the reader stops scrolling and lingers on the post
11) P(follow_author) — the reader follows you after seeing it
12) P(not_interested) — the reader marks "not interested"
13) P(block_author) — the reader blocks you
14) P(mute_author) — the reader mutes you
15) P(report) — the reader reports the post

Fifteen predicted actions, each multiplied by a weight, summed: that sum is the score that determines in which priority a post will be seen among other candidates.

Please note that posting something with a video or an image can give your post an advantage as 2 actions are specifically for these: video_view and photo_expand. No video or photo and you don't get a score for these. Also, naturally, having a video maximizes the chance that a user will "dwell" on your post to watch it.

Also note that 4 of these actions carry negative weights (not_interested, block_author, mute_author and report): meaning that if the model expects a post to generate a lot of negativity, it'll get de-boosted quite dramatically.

But note, first and foremost, what's NOT in there: none of the things that, naively, one might think a serious information pla[...]

A man from Dixon, Illinois was arrested at his home by police for alleged “stalking and intimidation” related to a Facebook post and event organizing a community protest against a proposed data center.

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AI video mocking UK “justice” has gone viral.

Some say it reads like a non-fiction documentary.

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Bodies of Evidence
https://www.bitchute.com/video/c6F9QxODL0Jd
https://rumble.com/v7b4bkk-bodies-of-evidence.html
https://odysee.com/@thecrowhouse:2/Bodies-of-Evidence:a
https://vigilante.tv/w/vhvkBEdjpwTznJAoPs3Nok

Outcry from a retired ER nurse about vaccines

"Just retired from a local hospital here. No one believes in the flu shots — my colleagues didn’t either!"

"Efficacy? 10% one year… 18%… 40% at best. It NEVER worked for kids 2-8 years old."

"I survived 20 years in high-volume ER — 300 flu cases a day — NEVER got the flu. Why? Hand washing, Vitamin D, elderberry syrup. Not your shots!"

"My soul was sick from what I saw… mandates, bribes with Target cards, pharmacists pushing it everywhere. I got 7 shots as a kid. My daughter got 10. Her son got 60+. My new grandson? Expected 72!"

"And I watched a perfectly healthy 2-year-old get those shots and become severely autistic! RFK Jr. is right — where are the 40-year-olds in diapers and helmets if this isn’t real? You should be ashamed. We’re done!"

Join us: t.me/CRUEL_HISTORY 🜂