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I don’t think Snoopy needs puppy training! 🐶💕🛋️🎤 #peanutsclips #snoopy #charlesschulz #charliebrown #petlovers #thepeanutsgang #puppy #training #puppytraining

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jihoon talking about working even harder from now on and his solo album someday… 🥹 🐶 (yonghwa hyung told me) “you did really well, seriously, you did well.” since he kept giving me lots of compliments like that, it made me feel really good. and it also gave me motivation, like i should work even harder from now on.. going forward, i want to work harder, keep practicing, and keep building the identity of the things i like… i don’t want to stop. i want to always work hard and not be lazy. in the end, it all comes back to me, and eventually it becomes one of the many ways i express myself as a singer 🐶 hyung said a lot of good things to me, praised me a lot, and even gave me a ring, so all of that was great but apart from that, i just felt proud somehow 🐶 so someday.. maybe when a solo album comes out, or- treasure is working really hard right now too, and i hope there’s no misunderstanding in what i’m saying. i love treasure. i’m doing treasure activities, but at the same time, there could be a day when i do music activities on my own too, right? you could say i’d be doing both in parallel 🐶 when that day comes, i want to really melt in a lot of identity, something that looks cool to people who know, and also looks cool to people who don’t. from one to a hundred, i want to think deeply about everything. i work with a lot of references honestly, my studio is full of them 🐶 (…) i’m always preparing. of course, i think a lot about the team too, and i think deeply about team activities as well. but i’m also doing a lot on my own, looking for references in the studio, talking with composer hyungs, working on various demos and things like that 🐶 whenever it is, someday… whether it comes out fast or slow.. someday.. if there’s an opportunity to come out properly after being prepared, that’s good too 🐶 either way, i’m going to do it someday. i have to do that before i leave this world. if i ever quit being a singer, i have to quit after doing what i want to do. i can’t quit without doing it. whether it’s fast or slow, i’ll do it eventually 🐶 so because the future is something i look forward to, a person can’t stop. some people might think this is like giving false hope and i get how this situation could look like that, but i don’t think that way. i’m definitely going to do it. and i need something i’m chasing like that so i can work harder, love the things i love even more, move my body, and live happily. i think of it as a goal point, and i’m chasing it hard… it’s fun~ 💬 i’m always rooting for you 🐶 i know very well that you always support me~ i’m so thankful. soso thankful, really. because of that support, when i’m able to release something, i want to put out something more perfect. not something that just looks like it quoted a rock concept and made something out of it, but something that really took that rock concept and those sounds and genuinely did something with them. if i were just going to do it halfway like that, i wouldn’t be loving this so much, grinding this hard, and practicing this much. i want to do it boldly, the way i truly feel.. haha it’s like that~ 🐶 so until that day comes, i’ll avoid things that are bad for my throat, take care of my health, and work hard. starting this year, i’ve been doing vocal training again, since december 2025, i’ve gone back into vocal correction, taking lessons on days without schedules. i need to work on my vocals too. 2026 is a year where i want to sing even better, everyone

행복지수 314%

43,388 views • 8 months ago

KINGSTON IS BREAKING MY HEART‼️‼️‼️‼️‼️‼️‼️ PLEASE SOMEONE SEE HIM & RESCUE HIS SWEET PUPPY SELF🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏 URGENT IN COBB COUNTY, GA‼️‼️🙏🙏🙏🙏🙏🙏🙏 Kingston is up for adoption at: 📍 Cobb County Animal Services - Marietta, Georgia ☎️ (770) 499-4136 READ HIS STORY ⬇️ Today, while I was volunteering at the shelter, one of the officers asked if I could make a video for a puppy because this was already his fourth time at the shelter… I couldn’t believe what I had just heard. 🥺 Then she told me that Kingston is only six months old and has already been adopted and returned three times. Apparently, he first arrived at the shelter as a stray when he was only four months old. A family adopted him and later returned him, saying that he had too much energy. After that, he was adopted once again and brought back because, once again, he had too much energy and they just couldn’t keep up with him. The third time he was adopted, he was returned yet again. This time, they said that he had too much energy and that they were moving. I honestly don’t even know what to say. I couldn’t believe it, and my heart broke for Kingston. 💔😭 I took him on a walk and made this video for him today. I spent a long time with him, and during the entire visit, he was one of the sweetest puppies. He was just so happy to be surrounded by people. At one point, Kingston grabbed a toy and decided that he wanted to bring it with us on our walk… and he did. For the entire walk, he proudly carried his toy everywhere he went. He is only six months old. He is not “too much.” He is a puppy!!! Puppies need patience. They need training. They need time to learn and grow… And despite everything he has been through in his short life, Kingston still greets the world with a wagging tail, a toy in his mouth, and hope that someone out there will finally keep him forever. If you think that person could be you, Kingston is waiting...

Fionaismybitch

27,577 views • 2 months ago

What actually changed my life was learning to do things I hated every single day. Some people read the early chapters of Troubled and say, “I can’t recognize this person. How does the teenage kid I’m reading about become the person I’m speaking to now?” The answer is simple: if you spend eight years in the military, you’re going to change. And it took all eight of those years for me to reshape my personality, my outlook, and my priorities to the point where I could function as a self-sufficient adult. I initially enlisted for four years. One of the most important lessons I learned during that time was that motivation is overrated. It took me a long time to understand this, but motivation is just a feeling. Do I want to do this? Do I not want to do this? Do I feel inspired today? Self-discipline matters more than motivation. Self-discipline means doing what needs to be done regardless of how you feel. It means sticking to healthy routines and making good decisions even when you don’t feel motivated. If you can string together enough productive days over a long enough period of time, your life will begin to improve. What’s happening internally, in terms of motivation or lack of motivation, matters less than people think. The real question is: can you do it anyway? At first, that discipline was imposed from the outside. In basic training, the instructors enforce structure and routine. But over time, that external discipline gradually becomes internal self-discipline. Even after my first four years in the Air Force, from ages seventeen to twenty-one, I knew I still wasn’t ready to leave that rigid structure behind. I understood that I needed more time inside an environment that demanded responsibility and consistency from me. So I reenlisted for another four years. By the time I was twenty-four or twenty-five, I was finally prepared.

Rob Henderson

24,172 views • 4 months ago

Today is my 7th birthday. And I think I've had the best year of my life. I have seen love, compassion, and kindness. I've licked teardrops off of cheeks, and wiggled joyously to the sound of laughter. I've won pretty ribbons and learned the best prize was the smile and the ear rub as she tells me how proud she is of me. I've discovered that when you take away some of the barriers we are a force to be reckoned with. I've learned to have patience with a puppy and I've learned that some humans will always fear me. I've discovered many people will help us chase our dreams and show the world that someone different can be successful. I've also learned some people fear those who are different and don't want to see us succeed. But we can, and do, in spite of them. Deep down, most hearts are good and capable of learning. There will always be some that see those who are different as having less value. They don't stop us though. We don't need approval from those who feel we deserve the same access as the trash bin in the alley. I've learned to worry about those who strive to make everyone feel like they belong. Thank you for helping us achieve our little victories and small miracles this year, and thank you for helping build a world where we can go out and do amazing things, instead of having to rely on someone else. Thank you for helping us be part of a great community and believing that we can achieve so many things. Maybe this year I will earn a championship title. Maybe I'll try something different. But I know I'll keep training my human to be well behaved, confident and capable of doing stuff she didn't think she could. I'm glad you're here for the journey. Video description: clips from Kuno's past year

Team Servicerottie🇨🇦🐕‍🦺🦽

39,305 views • 2 years ago

Quick chat with dylan ツ (Dylan Bristot, GTM @ $NBIS). Also on YouTube (link in first comment) for those who prefer to watch/listen there. Timestamps 00:00 – Dylan's role at Nebius and Nebius Token Factory 01:48 – Dylan's investing philosophy and portfolio approach 05:07 – How working in AI infrastructure influences his investing 08:29 – Training vs. inference and why inference demand could explode 13:22 – Enterprise AI adoption: from POCs to production 18:02 – Open-source vs. closed/frontier models 24:44 – The economics of open vs. closed AI models 29:27 – Where the next AI infrastructure bottlenecks could emerge 31:22 – Dylan's AI Bottlenecks project and approach to stock selection 34:06 – Closing thoughts Key Insights (AI Summary, so you don't have to copy paste and prompt for exactly that ;D) “I seem to like areas where the demand really looks kind of secular, but the supply is genuinely hard to create.” → Implication: The most attractive AI trades may sit in physical bottlenecks where supply cannot quickly respond to demand. “The bottleneck is who has the pricing power and kind of what might get commoditized and where the concentrate might move next.” → Implication: Value capture across the AI stack will keep shifting as individual layers become scarce or commoditized. “Training creates the intelligence and then the inference actually monetizes and distributes.” → Implication: Training and inference are complementary, rather than one ultimately replacing the other. “One user action can become dozens or hundreds of model calls, tools calls, and like verification steps, retries.” → Implication: Agentic AI can drive token consumption far faster than user growth alone would suggest. “The best infra for making any model and the best infra for serving a billion interactions are not necessarily the same.” → Implication: Training and inference could increasingly require different hardware and infrastructure architectures. “The Frontier Labs might be incentivized to run more and more of the inference of these models for internal research instead of providing it to external people.” → Implication: The most capable models and their compute could increasingly be used internally to accelerate frontier research rather than monetized externally. “Enterprise AI adoption is actually much further along than a lot of people kind of think. But probably less mature than the headlines suggest.” → Implication: Enterprise demand is real, but deployment maturity still has significant room to improve. “The POC problem might be solved for a lot of companies, but the production problem isn’t yet.” → Implication: The enterprise bottleneck is shifting from proving AI works to deploying it reliably, securely and economically at scale. “They feel like it’s time for them to actually not only integrate AI, but build some sort of moat out of the AI.” → Implication: Enterprises increasingly want proprietary AI systems built around their own data rather than simply consuming generic models. “The more autonomous the software becomes, the more infra discipline you need underneath it.” → Implication: Agents increase the importance of inference cost, reliability and infrastructure optimization. “Maybe I have fifteen different versions of very different LLMs, fine tuned on fifteen different kinds of tasks that I’m operating across my business, instead of having a one model fits all.” → Implication: Enterprise AI could evolve toward many specialized models rather than one frontier model handling every workload. “I don’t necessarily think it’s open versus closed. That might be the wrong framing.” → Implication: Open and closed models can coexist because they optimize for different customer needs. “Historically the problem was that that control came with a massive operational tax.” → Implication: Better inference infrastructure can make open models materially more competitive by removing the complexity traditionally associated with running them. “I don’t think open needs to beat the best closed model on every single benchmark. It just basically needs to be good enough for the workload of the given customer while offering a much better combination of control, cost, and deployment flexibility.” → Implication: For production AI, workload-specific economics may matter more than having the absolute smartest model. “Maybe actually the bulk of tokens generated in the future might come from open models.” → Implication: Frontier intelligence could remain dominated by closed labs even while open models capture most production inference volume. “I could really imagine frontier intelligence being really concentrated while most of the production inference becomes super fragmented.” → Implication: AI could consolidate at the intelligence layer while fragmenting heavily at the inference layer across models, GPUs, providers and regions. “I don’t think that necessarily means the margins of open source will be much worse than the ones of closed source.” → Implication: Optimization can potentially make open-model inference highly profitable despite lower pricing. “I think now we’re probably in the middle of phase two... everything feeding the accelerator.” → Implication: The AI trade is broadening beyond GPUs toward networking, packaging, data centers, electrical equipment and power. “It’s no longer about the megawatts, about energized megawatts.” → Implication: Available power on paper matters less than how quickly that power can actually be delivered to operating AI infrastructure. “It’s increasingly about utilisation and conversion now and like how efficiently you convert expensive infra into actual useful AI work.” → Implication: Infrastructure efficiency and utilization become increasingly important as the absolute amount of deployed AI infrastructure grows. “The market tends to really notice demand before it notices what demand breaks.” → Implication: Second-order bottlenecks may offer some of the most interesting opportunities in the next phase of the AI buildout. “The interesting question now is which part of the mine breaks next?” → Implication: Finding the next constraint in the AI supply chain may matter more than simply identifying continued AI demand.

Daniel Koss

49,970 views • 29 days ago