A Sudden Farewell Under the Eaves, and a Temporary "Mother Swallow" The mother swallow had flown away in a hurry, leaving behind a nest of tiny hungry babies. 😢Seeing them wait anxiously with their tender yellow beaks wide open, the man decided to become a temporary “mother swallow.” 💛May these little spirits grow up safely and fly into the blue sky that belongs to them. 🪽🫶🏻 #WarmDaily# #RespectForLife# #HeartwarmingMoments# #ChinaYouth# Source: Chezhiliqicheweixiufuwubu/Douyin

Armed Forces Day: honoring the ultimate defenders of freedom. This week we also recognize a Hollywood icon who walked away from celebrity to fly heavy bombers in World War II. Service is the highest calling. We fight and we win.

【Too Hot to Resist】Episode 1: Three Couples Spark Flying 💥 (25:30mins) After a long time apart, we finally reunited with J&B again! Since our Phuket couples trip, it’s been ages since we last saw them. This time, we arranged for J&B to join us together with David & Elaine — bringing new lovers and old flames together under one roof. It felt both exciting and nostalgic. J&B were once intimately close with us, almost like real lovers. Everyone truly cared for each other. Later, they stepped away from the scene due to busy work schedules. Meanwhile, we’ve grown much closer and more in sync with David & Elaine recently. We were all thrilled to finally gather all six of us together and curious about what kind of sparks would fly 💥 We booked a beautiful two-story house for the night. Everyone chilled, drank, and chatted. Elaine sat on the far left, followed by Sam, B, David, me, and then J. The conversation flowed freely and got increasingly flirty, but the real fun began with deeper connections… This game wasn’t just about warming up — it was about discovering who desired who the most. When three couples start swapping, that special, electric tension appears. The women tended to be more selective and passive at first, subtly showing their level of interest and affection toward each person before choosing who they wanted to connect with first. Who will develop strong feelings for whom tonight? And who will be the first to lose control and give in to their desires? —————————————— 【热情难挡】第一集 三对情侣夫妻换出火花💥（25:30分钟） 暌违已久，终于再次见到 J&B 这对情侣！ 自从Phuket那次情侣之旅后，我们已经很久没见了。这次特别安排了 J&B 与 David、Elaine 一起聚会，新欢与旧爱同聚一堂，感觉既刺激又充满期待。 J&B 曾经和我们亲密如恋人，大家都深爱着彼此。后来因为工作太忙，他们暂时离开了这个圈子。而最近我们和 David & Elaine 越来越合拍，关系也日渐亲密。这次能四人再加上 J&B 六人齐聚，真的非常开心，也十分期待会碰撞出什么样的火花💥 我们包下了一间两层楼的房子，晚上大家一起喝酒聊天。Elaine 坐在最左边，接着是 Sam、B、David、我，然后是 J，氛围轻松又暧昧。我们聊了很多，但最精彩的部分，当然还是之后更深层次的连接…… 这次的游戏不只是热身，更重要的是让大家感受「谁更喜欢自己」。当三对同时交换时，那种奇妙又紧张的感觉特别强烈。女生们相对被动，会先选择自己最想连接的对象，在过程中也自然流露出对对方的喜爱程度，慢慢找到今晚心动的性爱对象。 究竟谁会对谁产生强烈的爱意？ 谁又会最先忍不住呢？

to make a shit ton of money you NEED to adopt an abundant mindset you have to free the liquidity and just let it flow, not treat it as if you need to protect it all cost and take no risks i know it’s especially hard when you’re struggling but you have to trick your mind invest in yourself, spend money, let it cycle through ive given away a good amount of capital to people to help them get started trading and ive noticed most are fearful to make any moves even though they have the skills let it fly

In 2022, OpenAI researchers found something that broke every rule of machine learning. Their tiny model trained for 10,000 epochs. It learned absolutely nothing. Validation accuracy was dead stuck at 50%. Then at epoch 12,000, without warning, it jumped to 99%. This phenomenon is called "Grokking". And in 2026, it might be the most important discovery in AI nobody talks about. Neural networks can train for thousands of cycles without seeming to learn anything useful. Then, in a single epoch, they suddenly achieve near-perfect generalization. What started as a weird training glitch has become a foundational insight into how models truly learn. We’ve always been told: “If validation loss stops improving for a few hundred epochs, stop training.” Early stopping was the golden rule. Grokking says the exact opposite: Keep going. The model might look completely stuck, but real understanding is quietly forming under the hood. During that long, dead plateau, the machine isn't idle. It's doing deep internal work: - Circuits form, dissolve, and reform. - Spurious correlations get pruned away. - Weight patterns crystallize around true underlying rules. - The model shifts from brute-force memorization to genuine comprehension. It’s the machine version of a human “aha!” moment—a long, agonizing buildup followed by sudden clarity. Take modular addition as a real-world example. Researchers fed a small model just 30% of all possible examples. At epoch 500, it hit 100% training accuracy but stayed at 50% validation. It had memorized the test answers, but couldn't solve a new problem. At epoch 10,000, it still sat at 50% validation. It looked utterly hopeless. Then at epoch 12,000, it instantly shot to 99%. It didn't just guess right; it had grokked the actual mathematical rule. This explains the hidden mechanics behind the massive reasoning models we use today. When you see modern reinforcement learning or long-context reasoning models suddenly "click" after looking stuck, you are witnessing grokking at scale. Massive training runs aren’t wasteful, they are deliberately forcing the AI to stop memorizing and start thinking. And we are learning to induce this at inference time. Extended Chain-of-Thought prompts that force a model to think for thousands of tokens, self-consistency loops, and verification passes are all designed to do one thing: teach the model to grok your problem on the fly. The big philosophical takeaway is brutal for our short attention spans. Learning isn’t smooth. It isn’t gradual. It is discontinuous. Models, and humans, can stay “dumb” for ages, right up until they suddenly understand everything.