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Three people kicked in OnlyFans star Amouranth's bedroom door, put a pistol to her head and beat her. All while demanding $20 million in Bitcoin. She lied and told them she didn't know where it was and led them straight to her husband. The same husband that she has constantly complained about on stream. She even called the police on him at one point. This happened on March 2nd, 2025, in Houston Texas. The robbers came in through the back fence, smashed open the garage door, and inside they even tripped over a pile of kids toys. Kaitlyn "Amouranth" heard the noise and called her husband, he said it was most likely the dogs. She locked her bedroom door and kept him on the phone. That's when they confronted her, shot gunshots in the door and kicked it in, then turned on the lights. One of them had a gun to her head while another took her phone and demanded she opened Coinbase. She didn't even have the app. She told them she didn't have it then they started beating her with the pistol. After the third hit Kaitlyn lied and told them she remembered where it was. She ran barefoot in socks and pajamas to her husband in his mancave. Nick the husband was on the toilet and heard everything on speaker phone. He pulled up in briefs, put on a bulletproof vest and opened his gun safe. When the gunmen came in he told Kaitlyn to get down and she dropped to the floor. Nick then shot one of the gunmen. Then they ran away. Nick almost didn't call 911, because fans would swat their house all of the time. The only thing the robbers got away with was her MacBook, which had Find My turned on. The guy that Nick had shot was in the hospital, but it was too late. Four days later a trooper pulled over their getaway car because the driver didn't use his turn signal. He confessed on the spot. All four robbers were then charged with aggravated robbery and kidnapping. The internet thought this was all fake, so Kaitlyn posted the footage. In October 2022, she had cried on stream and told millions Nick controlled her money, threatened her, and to pretend to be single. After the robbery she called him a hero on camera. On May 11, 2025, they argued on stream for 10 hours. Nick accused her of cheating and she cried. When things heated up the cops came knocking on the door. In February of 2026, they were vacationing in Peru and had another fight in their hotel, police detained them both this time. The man who saved her from 3 gunmen is the same man she would keep calling the police on.

OK let’s try this: ———————- Pretend you’re 5 and the algorithm is a smart robot that picks which toys (posts) to show you in your toy box (For You feed). The robot doesn’t just count how many times people already played with a toy (likes, reports, etc.). Instead, it looks at you and guesses: • “How likely is this kid to like this toy?” • “How likely is this kid to report this toy as yucky?” • “How long might this kid play with it?” Those guesses are little numbers between 0 and 1 (probabilities). The “weights” are like special multipliers the robot puts on those guesses: • A like-guess might get multiplied by a small number (like 0.5). • A report-guess might get multiplied by a big negative number (like –234). Then the robot adds all those multiplied guesses together to give the toy a final “yay or nay” score and sorts the toys by that score. Why the numbers look so big and why people get confused Reports almost never happen, so the robot’s “will you report this?” guess is usually a tiny number (like 0.0001). To make that tiny guess still matter a little bit in the final score, they give it a big multiplier. People sometimes look at the big number and think “1 report = 468 likes!” 
That’s wrong. It’s not counting real reports or real likes. It’s only multiplying the guesses the robot made about you. If the robot thinks you’re the kind of person who almost never reports anything, even a big weight on “report” barely moves the score. The whole thing is personalized to how you usually behave. The people who wrote the code even put big comments in the GitHub repo so no one (and no other robots) gets confused about this again. That’s the whole idea in kid words: the weights turn the robot’s personal guesses about you into a ranking, not a simple “count the hearts and flags.”

该策略将1690枚比特币卖出，用于回购STRC代币，其美元储备增至46.5亿美元，比特币持仓降至840,447枚。 这波操作有点像用老式存钱罐换新玩具——比特币变代币，储备钱多了，但手里的硬币少了，真有意思。 The strategy sold 1,690 Bitcoin to repurchase STRC shares, raising its US dollar reserves to $4.65 billion while reducing Bitcoin holdings to 840,447 BTC. It’s like swapping old coins for new toys: selling Bitcoin to buy STRC, more cash in the bank, but fewer coins left in your pocket—kind of clever. $bitcoin via Cointelegraph Direct ·

It may say 3+ but this one’s for the adults. 😅 And yes, this case did fit on the M3 iPad Air 🎉 Check it out now: #belkin# #toystory5# #ts5# #lilypad# #ipadcase#

Seedance 2.0 on higgsfield Prompt: A photorealistic smartphone selfie vlog that looks exactly like a real mobile phone recording. A young woman (image = her face and hair) visits a cozy thrift store on a sunny afternoon, filming everything herself with a handheld smartphone in selfie mode. The video features natural hand shake, realistic autofocus, slight exposure changes, authentic smartphone stabilization, and true-to-life colors. Smiling at the camera, she says, "Today's thrift store challenge—I'm only buying the first cute thing I find!" She walks through colorful racks of vintage clothes, shelves of accessories, plush toys, and home décor until she spots a random adorable oversized hat. Laughing, she immediately tries it on in front of a mirror, making funny poses and bursting into genuine laughter at how silly she looks. She decides to buy it, walks out of the store holding a small shopping bag, proudly shows her surprise find to the camera, smiles brightly, waves, and says, "See you in the next vlog. Bye!" before reaching toward the phone to stop the recording. The video should feel completely real with natural human movement, consistent facial features, realistic hand interactions, authentic thrift store lighting, no beauty filters, no CGI, no AI-plastic appearance, no subtitles, no logos, no watermark, and no background music—only real store ambience, footsteps, quiet conversations, clothing rustling, and natural environmental sounds.

What a great time at #SDCC#. Thank you to everyone who joined in Hall H for our panel (and kept themselves hydrated 😉) and to all the incredible folks who shared their stories and experiences about the toys that shaped big pieces of our childhood. Cannot wait for everyone to see #MatchboxTheMovie# on @AppleTV October 9th!