DangcingAI

DangcingAI has added four new features: 1. watermark removal 2. subtitle removal 3. video restoration 4. AI video upscaling. It uses our latest self-trained model. Whether the results are good or not, you'll know once you try it. The platform remains in free beta testing. If you encounter any issues or have suggestions, feel free to leave a comment and share your feedback.

@stevencheng very kawayi

A 3D-printed AI-like puppy that tracks every sip, detects refills, and transforms a simple habit into a smart hydration companion.

@Bitcoin188 对啊，剪映啥的还要给钱 。我估计就是ffmpeg上面套了层皮

@DangcingAI 用ffmpeg来简单的剪辑视频很快啊

我已经习惯了用ffmpeg来简单的剪辑视频，而不是用capcut/剪映这类

@stevencheng Most machines on the market are still 3-axis.

It is called 5-axis cnc because the machine controls five directions of motion: X, Y, Z for position, plus two rotary axes for orientation. The additional rotation allows the cutting tool to approach a part from different angles, enabling complex 3D machining.

@stevencheng Technology should be advancing humanity, not fueling wars.

No roads. No bridges. No problem. Drones are rewriting disaster relief — flying over floods to deliver food and supplies to communities cut off from the world. 🚁

@Bitcoin188 受不了这种帖子，太无脑了。

卧槽！兄弟们，听我给你讲个真实故事…… 去年我一哥们儿，普通上班族，每天加班到吐血，月薪勉强够房租。有一天他刷抖音刷到崩溃，心想：这平台天天流量爆炸，老子为啥不能分一杯羹？ 他没钱没设备，更不会剪辑。结果呢？ 他就随便挑了几部热门电视剧，用AI一键切片，剪出高燃名场面、搞笑片段、虐心高光……直接原汁原味扔到抖音上！ 第一条视频发出去，当天就几千播放。 第二条破万，第三条直接10w+！ 现在呢？ 他每个月光躺着收广告分成和直播带货，就稳稳月入七八千……有时候爆款还上万！ 兄弟们，白嫖党福音啊！ 别再手动剪视频剪到吐了！ 用AI做切片，找几部电视剧，发到抖音就行了，月入几千真的轻轻松松！ 我哥们儿现在天天睡到自然醒，笑称自己“AI躺赚”。 你还在996吗？ 还在为流量发愁吗？ 评论区留言 赶紧行动，晚了流量红利就没了！ 🚀 你怎么看呢？

@Eng_china5 远看像个电钻

Only in China. The 91.5-meter "Stairway to Heaven," with over 300 steps attached to a vertical cliff, turns fear into adventure and offers breathtaking views that few places on Earth can match.

@kfk_ai @grok 这段结论的出处

马斯克在最近那场三小时访谈里，给 AI 时代画了三条线 一，学历加速贬值，大学可能只剩社交价值，他自己招人从不看文凭，只看能不能解决真问题 二，机器人外科医生三年内超越人类顶尖医生，AI、芯片、机电灵巧度三条指数曲线相乘，学医不再是稳妥出路 三，2030 年 AI 智力总和超过全人类，货币逐渐失去意义，财富的新单位是能源和算力，为退休存钱这件事本身会过时 他也说了代价：未来三到七年，是一段非常难熬的动荡期

@mingxian232 200u

非常想知道粉丝在5千-1万之间的博主 一个月的收益有多少美元？ 能到500U吗🙏

@CyberRobooo Way too inefficient.

Another humanoid robot at the construction site (POC) For large-scale construction areas with high tolerance for error, Unitree G1 humanoid handle broad-area tasks (via teleoperation), while skilled workers attend to the finishing details...

@stevencheng physical ai is really changing fast

Ant Group's Robbyant just shipped 6 models in 4 days — and the real product isn't any single model. It's a vertical supply chain for embodied AI. What a statement of ambition! The stack: - LingBot-Vision + Depth 2.0 solve precise spatial perception (depth error halved on glass and mirrors). - World 2.0 + Video tackle long-horizon world modeling (hour-long 720p/60fps real-time generation). - VLA 2.0 + VA 2.0 are a double bet on the robot brain. The most elegant design choice: perception models serve as training-time teachers, not runtime modules. Geometric understanding gets distilled directly into policy weights — enabling a 130ms closed loop on a single RTX 4090. Industry context: Physical Intelligence is all-in on VLA. NVIDIA runs both tracks but leans platform licensing. Robbyant open-sourced both routes as a full stack in one week — and benchmarked against π0.5 on its own GM-100 suite, on Astribot S1, a body π knows well (fridge sorting: 77.1/60.0 vs 65.3/46.7, in-domain). The finale, VA 2.0, is their public bet on embodied-native AI: pretrained from scratch, strictly causal, 150Hz on one GPU, generalizes from 20 demos. Everyone else is shipping models. Ant is shipping a supply chain — from Orbbec's sensor edge all the way to the on-device brain.

@stevencheng amazing

These breathtaking automated production lines are pushing efficiency to the extreme.

@stevencheng simple is effective

Color sorters are among the earliest commercial robotic vision systems. Even today, many industrial systems still rely on line-scan CMOS/CCD sensors paired with FPGA processing. The reason is simple: extreme latency requirements. Materials often move at 3–8 m/s, leaving only 5–20 ms for sensing, decision-making, and actuation. FPGA provides deterministic real-time computation, but it does not "understand" the image. Meanwhile, mainstream GPU-based AI solutions still struggle to match this level of low-latency industrial performance.

@feng638061 nb, 一天回复400多，坚持

失业在家后 我成为了x的工作者 看见别人半个月收益3万人民币 我感觉大家都可以 这是鼓励的段子 加油！！！！！！！！！！！！！!

@fchn161037 这麽np !

@DangcingAI 中国队进入8强了

@LuBtc888 我还活着，用的海外卡和手机号

我很不理解， 为什么Claude封了那么多中国人的号， 可还是有很多中国用户至今没被封， 这些人究竟都是何方神圣？

@0xTraderYi 只能说在国外重新起号不容易的。

范爷，老了啊 总觉得没有以前那种艳压群芳的惊艳感了 冰冰也不差钱吧！一把年纪为啥还这么拼参加走秀

@stevencheng after all these years, you finally understand pick-and-place machines. Is it time to get back together with your ex? 😂

Years ago, my girlfriend worked in Yamaha's pick-and-place machine business. Even after we broke up, I still didn't really understand what a "pick-and-place machine" was. Only recently, after discovering LumenPnP, an open-source pick-and-place machine, did I finally understand this fascinating piece of technology. LumenPnP enables reliable and accurate assembly of electronic components onto circuit boards — bringing industrial SMT technology closer to the open-source hardware community. The GitHub repo for this open-source pick-and-place machine is in the comments.

@CXLH22 看了你的回复，我知道为啥你的总流量低了。

我要自由，要雪山、我要山野辽阔，我自自由，心无杂念，远离世俗

@CXLH22 一个男人，居然坐副驾。。。