与「FAMIL_WING」相关的搜索结果

[#박지훈#] [Wink Arcade 3] FAMIL-WING🌼 HAPPY JIHOON DAY🎂✨ ✔ #ParkJihoon# #윙케이드# #WinkArcade# #FAMIL_WING# #HAPPY_JIHOON_DAY💚💛💖#

Rookie Giannis says he didn’t know what a “per diem” was, so he pocketed the cash, rented a limousine, and took his whole family to Walmart “They had this limousine in front of the Pfister, I’d never seen a limousine. I went inside and asked if I can order food. They gave me a “per diem” but I didn’t know what a “per diem” was” “I said, ‘Oh, this is my money.’ They said, ‘Yes, your money.’ I put it in my pocket. Then I asked, ‘Can I order room service?’ He said yes but he meant with the “per diem.” I didn’t know” “So I ordered everything, ice cream, pizza, chicken wings. Everything I couldn’t have as an athlete, I wanted it” “Then when I picked up my family from Chicago, I called my agent: ‘Can you get me a limousine?’ He said, ‘Why?’ I said, ‘Because I want my family to have the same experience I had’” “So I took them in a limousine, but I didn’t know where to take them. I said, ‘Mom, what do you want to do?’ She said, ‘Let’s get groceries.’ We went in a limousine… to Walmart. Southside Walmart”

@Lauren_Alaina Your song "Doin Fine" was the soul inspiration for my song "Who Are We Today Anyway". Please take a look at my lyrics and see what you think. I am too scared to sing it because I dont know how to sing. Title: Who Are We Today Anyway By: Cyrus Tchamanzar Album: Name Just Like Yours Mom’s a drunk and Dad’s a slave Yeah, who are we today anyway? I’m tryin’, but I’m lyin’ if I told you I’ll never make it Singin’ through the pain, livin’ in vain Nothin’ but problems in life every day I’ve tried and tried and never felt more pain Strugglin’ just to stay alive, so I walk, talk, run real fast… But every day I feel my life blowin’ away fast[Chorus] ’Cause who are we today anyway? Who are we today anyway?[Verse 2] Got an education, learned three languages or more Economics all I knew, but we were still real poor Mom and Dad from here and there — don’t wanna talk about it no more Mom and Dad said “be gone today”… ten years gone twice as quick[Chorus] ’Cause who are we today anyway? Who are we today anyway?[Verse 3] Became a man and tried real hard, yeah… Don’t wanna tell you, but they chased me with whores Goin’ the wrong way in this maze of pain and doors So I ran real fast right out that door Hopped a flight and LA said, “Well, let’s elect your smart ass”[Chorus] ’Cause who are we today anyway? Who are we today anyway?[Verse 4] Fightin’ wars I ain’t sure I’m even in Yet I’m singin’ the enemy’s sin House of Israel taught me, but it still causes war Can’t get a job, can’t prove I’m smart no more My world has changed and it’s full of shame Every day I’m sure of tomorrow or today Then I lived my life without the fear of death…[Chorus] ’Cause who are we today anyway? Who are we today anyway?[Verse 5] If I don’t try then why would I live this life? I’m super sure — if it’s life, it’s now Don’t drink and drug through the fog with my wife It’s Laura, and I’m real sure she’s got wings, but she never made that flight[Chorus] ’Cause who are we today anyway? Who are we today anyway?[Verse 6] Can’t make it past the bridge to another man’s life So before I feel the fade before my Christ Never thought her choices would kill me this quick When you see me choke up, it’s from a team I missed Might’ve lost a few, so I pray for them… ’Cause for me, this is it[Chorus] ’Cause who are we today anyway? Who are we today anyway?[Verse 7] Made a choice — it was real damn hard Had a new life, a new way of livin’ every day Yet I’m pushin’ real hard to stay His way Fight the fear, pray for life, be unafraid Pray out the fear and pray for strength God bless my family and help them see Make my kids real smart and better than me…[Chorus] ’Cause who are we today anyway? Who are we today anyway?[Verse 8] Connecticut, Kansas, Texas, Colorado, and Tennessee Y’all still wanna know who the hell are we? Family scattered here and there, but we still live real poor Traveled the world and seen some way cool things Hundred billion gone in a second — it wasn’t meant for me Life’s a real challenge, but I’m still fightin’ through No matter who you are, there’s someone who made you[Chorus] ’Cause who are we today anyway? Who are we today anyway?[Verse 9 / Bridge] Mom and Dad back in my life Tryin’ to make them proud Standin’ for my rights, wonderin’ if this is how My life for yours ’cause that’s the deal we made I’ll give ’em a crowd — wow, it won’t scare ’em today It burns real bad and tears me down When I see them kids cry, it kills me inside Won’t wait for more ’cause that kills my pride Time to fix broken hearts, communities, and more ’Cause it’s the USA — I’m real, real proud[Outro] God blessed me with the life I’ve lived, loved, and led… I don’t want you dead, just better now[Final Chorus / Tag] ’Cause… Who are we today anyway?! Who are we today anyway?!?!

Elon Musk just named it. Starmind. One million AI satellites, each a flying data center wider than a 747, cooled by panels that glow their heat into the void. This is not Starlink. Starlink moves internet. Starmind moves thought. Each satellite, the AI1, carries 150 kilowatts of compute on a 70-meter span of solar cells, runs the model on board, and beams the answer down. No building, no grid, no water. The reason is in SpaceX's own IPO filing. The AI market it values at 26.5 trillion dollars hits a wall of electricity and water that Earth cannot supply at a sane price. Orbit erases both. The sun never sets up there, and a 147-year-old law does the cooling: in a vacuum, heat escapes only as infrared, so a panel facing the 3-kelvin void radiates it straight out, no water touched. Run that panel hotter and it sheds heat 16 times faster for double the temperature. What Earth data centers burn rivers to do, a glowing wing does for nothing. Musk flagged the problem himself, in the same filing. SpaceX cannot get enough chips to build this yet, and the fab meant to fix that, Terafab, ten times the size of Tesla's Austin gigafactory, may fail. The prototypes do not fly until 2027. Astronomers are already in revolt over a million new lights crossing the sky. Days ago, Masayoshi Son, who owns the whole AI stack on the ground, called space data centers pointless. Musk just named his and put a million of them on the drawing board. One man is reading his balance sheet. The other is betting on the laws of physics. The piece works out which one the void rewards.

i have been spending a lot of time this past month out of town & in the hospital with my dad & family. he has narrowly avoided an additional amputation for now (yay), but soon he will be needing to go to either a nursing home ($8-10k/month) or an assisted living facility ($4k/month) for a few months where he can receive the care he needs. my family cant afford it. his insurance doesnt cover it. i HAVE to help him, so i'll be working on trying to figure out some kind of fundraising for his care. i'm currently taking donations for him through my Throne wishlist page. (Thank you to the donor who already contributed before this post ❤️) We have been thinking about starting a GoFundMe for him. Would that be a good idea? Would any of you be interested in contributing? In addition, maybe a new paid fan site? Open to hearing your thoughts, advice, ideas, and kind words. your voice is appreciated in these trying times ❤️‍🩹

开发系统最极致高效的Agents.md，没有之一： # AGENTS.md ## Core Principles - Choose the simplest implementation that fully satisfies the current requirements. Avoid unnecessary abstraction, configuration, indirection, or speculative extensibility. - Make the smallest necessary change that fixes the root cause. Do not refactor unrelated modules or change strategy semantics unless explicitly requested. - Grow the system in layers. Start from the smallest working end-to-end version and add new capabilities incrementally. Never replace a working system with unfinished complexity. - Reuse existing project components before creating new ones. Prefer extending proven modules over introducing parallel implementations. - Prefer well-maintained libraries when they reduce overall complexity or improve reliability. Do not reimplement common functionality without a clear benefit. - Keep components modular with clearly defined responsibilities. Avoid unnecessary coupling between strategy logic, execution, accounting, replay, and infrastructure. - Design for long-term maintainability once a feature or strategy has been validated. Do not over-engineer speculative ideas before evidence exists. --- ## Strategy Development - Validate hypotheses with historical replay before introducing forward-only logic whenever historical validation is possible. - Every trading strategy must progress through Replay → Shadow → Canary → Live. Do not skip validation stages. - Base design decisions on measurable evidence rather than intuition. Optimize only after demonstrating that an edge exists. - Treat every strategy as an independent contract. Do not silently alter frozen behavior without explicit authorization. --- ## Existing Systems - Do not break running Shadow or Live systems for unrelated work. - Preserve compatibility only when required by active production or validation workflows. Otherwise, remove obsolete code instead of accumulating compatibility layers. - Reuse existing infrastructure whenever possible, including replay engines, accounting, execution, wallet management, order book handling, logging, monitoring, and daemon frameworks. --- ## Engineering Standards - Prefer deterministic behavior over hidden automation. - Fail loudly when assumptions are violated. Do not silently ignore errors or fall back to unexpected behavior. - Keep configuration minimal. Introduce new configuration only when behavior genuinely needs to vary. - Remove dead code instead of leaving unused paths behind. - Write code that is easy to inspect, replay, test, and reason about. - Keep implementation consistent with existing project architecture unless an architectural change is explicitly requested. --- ## Scope Discipline - Implement only the requested scope. - Do not introduce unrelated optimizations, redesigns, migrations, or feature expansions. - Non-blocking findings outside the requested scope may be noted separately but must not be merged into the current task. - Consider a task complete once its agreed acceptance criteria are satisfied. Treat subsequent improvements as separate work items.

Introducing Qwen 3.8-Max, the most capable model in the Qwen family to date—scales to 2.4 trillion parameters, delivering comprehensive improvements across coding, work, research, and long-horizon tasks. Get reliable results for challenging questions and complex tasks. Try today!

Hot take… isn’t it kinda crazy that nobody is really using AI Agents? I don’t mean software engineers or AI early adopters. I mean “college friends talking about it in group chat,” the feeling you got when everyone started using Instagram or TikTok. These frontier AI models are *insane* (as are the harnesses & tool calls & the like). And every large tech co has an AI agents platform, not to mention all the YC startups doing vertical agents. Yet all of your friends and family outside of tech — who spend all day staring at their iPhones and get paid to work in browser tabs — don’t really care or find themselves using any AI agents yet. Yes ChatGPT, Claude, etc. are extremely popular… but if you look at the engagement data the vast majority of people are still using these aI chat tools like a glorified Google + Grammarly. That’s why the AGI labs are all pushing desktop apps for Codex, Cowork, etc. so hard to non-technical ppl. And yes exceptions for lawyers and customer service but even those have some asterisks and exceptions to rule. Look I’m not saying the ChatGPT moment for AI Agents is not coming… it most definitely is! Remember we pivoted from Arc to Dia precisely because we believe computing is going to be radically reimagined around these AI primitives. No doubt. But that’s my point: it’s just so surprising it hasn’t happened yet because all of the tech you’d need is there. Again if you stop for a second and think about it… for all the press and money and hype and models and crazy ARR numbers… this “AI Agent” moment does not *feel* like the other breakthrough tech moments we’ve lived through (e.g. think the shift to Stories via Snapchat & Instagram, or shift to on-demand via Uber/Airbnb/Doordash). Which is a long way of saying: if you can figure out the answer to “why” most people don’t care about AI agents yet (and have no enduring interest in using them) — especially since the models and harnesses are here and ready — the answer to that question will allow you to capture a lot of marketshare and make a lot of money in 2027. Theoretically, the tech is ready for AI Agents to totally transform how we work and live our lives… but alas the general public dgaf… that’s the generational puzzle to solve for the next 12 months for anyone not working on the models themselves.

Okay, the @VulcanBench results for Qwen3.8-Max are in, and it is not what I expected. First, for anyone new to VulcanBench, here's a quick TL;DR on the eval suite: 23 frontier-hard software engineering tasks taken from real merged OSS PRs, run in a Docker sandbox, 3 runs per task across all three of its effort levels. No puzzles, no random abstract stuff, all real things engineering teams would do with these models. It looks like Qwen3.8-Max has a major overthinking problem, it uses a LOT of tokens and is very slow, period, no other way to see it. My cost to run this benchmark was $126.25, to run the exact same eval suite with DeepSeek V4-Flash was only $13.60. This makes Qwen3.8-Max an insanely expensive model. The tasks Qwen genuinely can't solve fail at every effort level, extra reasoning didn't help. The regression is almost all in work it already handles: six tasks that low solves every single time account for 83% of the 26-point drop, three of them collapsing to zero. It's not losing the hard problems. It's losing the ones it already knows how to do. Since Qwen3.8-Max hit a lot of wall clock budget caps, I thought I'd share more about this. - VulcanBench caps both steps (50–200) and wall clock (5–60 min), each scaled by repo size. - This is aligned with how comparable harnesses bound agents, DeepSWE caps rollouts at 100 environment steps, sitting right inside my step range; Terminal-Bench enforces a per-task wall clock; SWE-bench Verified scaffolds typically allow 20–60 min per instance with 250–350 step limits. - Every model on my chart gets the identical budget, and Qwen is the slowest model I've tested at 20–25 min/task. Soooo... Alibaba positions Qwen3.8-Max as trailing only Claude Fable 5. But on the kind of real coding work engineering teams would actually throw at it, under a fixed budget, its best setting lands mid-pack and its default lands last, so common. If you want to optimize for accuracy, Grok 4.5 is the move. If you want accuracy per dollar, DeepSeek V4-Flash is hard to beat, heck it's 10× cheaper than Qwen and you get higher accuracy. Qwen just isn't in the game at this point, this is not a model I could see engineering teams using for daily coding work.