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Hair Dynamics Broken When Moving Your Model Try This Fix! #BlenderHairFix #HairDynamics #BlenderTipsAndTricks #BlenderSimulation #HairCacheProblem #BlenderShorts #BlenderWorkflowTips #3DAssetReuse #BlenderHairSimulation #BlenderAnimationHack

3 条评论

Rombout versluijs 的头像
Rombout versluijs1 年前

Clever tip

Phil@TheMFTs 的头像
Phil@TheMFTs1 年前

Dope! Kinda makes me wanna grow digital feathers now 😂

黑洞 的头像
黑洞1 年前

牛逼啊

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34 Auditing Tips to crush it in 2026 - Think in bets - Constraint behaviour - If it's hard for you it's hard for everyone - Seek truth - Understand it first, then break it - Building is harder than breaking - Tools are substitutes for thinking - A fully understood Low is better than an untested fix - If it's not tested, it's broken - AI is a brainstorming tool - Work with Progressive Escalation - Understand the meaning of being average - Formally verify stateless libraries to extract constraints - There are no easy paths, you have to get better - Understand when to clamp and when not to - Rewrite it your way and compare notes - Peak experiences are like a wave. - Most Contest winners have a brutal track record - There's no rush in writing a report and POC - it's always a very serious deal or just don't bother - Start with the end in mind - Read the code until you can't anymore, then try something else - You don't understand the intensity of reviewing code, until you've seen it - If you're done before the end of the engagement, you're probably wrong - Understand your edge and use it to your advantage - There is no overnight success, only the world catching up to you - The path to mastery is simple, do the thing with 100% of intention, review the results, learn - Model people that inspire you - Forge your own path - Read about common bugs - Create your own category defining bugs - Resting is work - Be careful about your own biases - The only constant is you

Recon

15,364 次观看 • 8 个月前

McKinsey surveyed 2,000 companies in 2025. 51% said AI backfired on them. Top reason? Inaccuracy. From what I can tell, most of these systems weren't broken. They were unreliable. And unreliable is wayyyy worse because you can't predict when it fails. So I got Ash Tilawat (the Mr. Miyagi of teaching AI) from Gauntlet AI to walk me through the solution. Here's his 2026 framework for evaluating if your AI is trustworthy, reliable, and production-ready: 1. build your golden set Identify 30–50 core requests your AI must handle correctly. The stuff that, if broken, makes the whole system useless. And sit with the person whose job this AI is doing/automating/replacing/helping with. 2. test the weird stuff Your golden set covers common requests. But in production, users don't only ask common requests. So build a matrix of categories (topic x complexity) and fill the gaps. Every gap is a corner where failures can hide behind. 3. build a replay harness Record the exact state of every interaction so you can test prompt changes without burning API calls. Think of it like game film... you don't put players back on the field just to review the play. 4. create your rubric Use an LLM to grade outputs on accuracy, completeness, and tone. But calibrate it first -> run 50–100 examples through human and LLM scoring, find disagreements, fix the rubric, repeat until they match. 5. run experiments New model? Prompt rewrite? Run your eval suite against both versions. Ship if the golden set passes, no regressions, and the cost is acceptable. The teams still running production AI on vibes will be f***** in 2026. But the teams building eval libraries are compounding an advantage that gets harder to catch every month. Competitors can copy your product. They can't copy your test cases. h/t Austen Allred for helping put this together. Full playbook + vid below 👇

Alex Lieberman

71,920 次观看 • 6 个月前

🚨🇺🇸 ELON'S CONFESSION PROVES WASHINGTON IS DESIGNED TO DESTROY ITS REFORMERS This is the message we send to anyone who tries to clean up Washington: Try to help us, and we’ll destroy you and everything you’ve built... When Elon says he wouldn't do DOGE again knowing people would burn his cars in response, he's not being weak; he's acknowledging that our political system has evolved into an organism that attacks its own antibodies. Consider what Elon accomplished before touching government: revolutionized electric vehicles against every established automaker, landed rockets backwards on floating platforms when NASA said it was impossible, created a satellite constellation providing internet to war zones and disaster areas, pioneered neural interfaces that help paralyzed people walk. Each achievement required defeating entrenched interests who said he'd fail. But those were merely corporate competitors and skeptics. Washington is a different beast. Washington doesn't just resist change; it destroys change agents. The burning cars tell the real story. When you try to cut government spending, you're not debating policy; you're threatening thousands of interconnected interests that survive on waste. Every inefficiency has a constituency. Every redundant program has defenders. Every dollar saved is someone's dollar lost, and they'll make you pay personally for threatening their revenue stream. They don't argue your proposals; they attack your existence. This is why government never shrinks, only grows. The system selects for people willing to play along, not those who might fix it. Anyone competent enough to reform government is successful enough to have something to lose, and the system ensures they lose it. Elon has billions of dollars and still concluded the personal destruction wasn't worth the attempt. What chance does anyone else have? The tragedy isn't that Elon regrets trying to help. It's that his regret is rational. When fixing waste makes you more enemies than friends, when efficiency threatens more interests than inefficiency, when the reward for public service is public destruction, the system isn't broken. It's performing exactly as designed: protecting itself from anyone who might actually change it. Source: Katie Miller Elon Musk

Mario Nawfal

448,511 次观看 • 8 个月前

You can’t make anyone else change; all you can do is create the conditions where change is more likely to happen. I remember speaking with an administrator and hearing him complain that his staff wasn’t moving forward. Instead of commiserating with him at that moment, I said, “Maybe it’s you?” It caught him off guard, but there was a point. Too often, myself included, when we try to lead people to new ideas, and they don’t immediately embrace them, we blame them instead of looking at where we may be deficient. Sometimes, the new “approach” is sharing the ideas over again, only louder. That approach rarely works. In this week’s newsletter, I shared 3 things that have helped me rethink how to help create better conditions for others to embrace change. 1. Truly listen to their thoughts and viewpoints, and be open to the idea that your way might not be the best. 2. Recognize that you also had resistance to new ideas, including things that you might consistently do and believe today. Be open with your own story of resistance and what made you change. 3. Start by focusing on the areas in which others are excelling, as opposed to your perception of their deficits. People who feel valued are more likely to move forward. People who feel you are trying to “fix” them will fight you non-stop. You can only control your own actions. What do others see in you that will make them want to move forward, by your side? People are more likely to take steps forward on a path if they see footprints from others already on the ground. Read the entire newsletter here:

George Couros

15,735 次观看 • 2 年前

this video is the CLEAREST explanation of how claude skills + AI agents work and how to use them most people set up an AI agent and wonder why it keeps disappointing them. the context window is everything context is what the model assembles before it takes any action. think of it like everything the agent needs to read before it does anything. the quality of what goes in determines the quality of what comes out. the models are genuinely really good right now. claude and gpt are exceptional. the variable is almost always the context you give them. 1. agent.md files are mostly unnecessary every single line you put in an agent.md file gets added to every single conversation you have with your agent. a 1000 line file is around 7000 tokens burning on every run. the model already knows to use react. it can read your codebase. save the agent.md for proprietary information specific to your company that the model genuinely cannot know on its own. 2. skills are the actual unlock a skill.md file works differently. what loads into context is only the name and description, around 50 tokens. the full instructions only appear when the agent recognizes it needs that skill. so instead of 7000 tokens on every run you have 50. and the agent stays sharp because the context window stays lean. the closer you get to filling the context window the worse the agent performs, same way you perform worse when someone dumps 10 things on you at once. 3. here is how to actually build a skill the right way most people identify a workflow and immediately try to write the skill. what you want to do instead is run the workflow by hand with the agent first. walk it through every single step. tell it what to check, what good looks like, what bad looks like. correct it in real time. once you have had a full successful run from start to finish, tell the agent to review everything it just did and write the skill itself. it writes a better skill than you will because it has the full context of what actually worked in practice not in theory. 4. recursively building skills is how you go from frustrated to reliable when the skill breaks, and it will break, ask the agent exactly why it failed. it will tell you specifically what went wrong. fix it together in that same conversation. then tell it to update the skill file so that failure mode never happens again. ross mike did this five times with his youtube report generator. it now pulls from eight different data sources and runs flawlessly every single time without him touching it. 5. sub agents are something you earn not something you set up on day one start with one agent. build one workflow. turn it into one skill. once that works add another. ross mike has five sub agents now covering marketing, business, personal and more. it took months to get there and every single one exists because a workflow proved it deserved to exist. the people who set up 15 sub agents on day one and wonder why nothing works skipped all the steps that make the thing actually run. 6. your workflow is the thing the model cannot get anywhere else the model has been trained on everything. it knows more than you about most things. what it does not have is your specific process, your taste, your way of doing things. that is what skills capture. that is what makes your agent actually useful versus a generic one. downloading someone else's skill means downloading their context onto your setup and it will not work the way you want it to because it was never built around how you work. this is the clearest explanation of how agents actually work i have heard. Micky runs this stuff every single day and the results show it. full episode is now live on The Startup Ideas Podcast (SIP) 🧃 where you get your pods people charge for this sorta stuff i give away the sauce for free i just want you to win watch

GREG ISENBERG

193,592 次观看 • 4 个月前

REPLAY FILES BROKEN (FIXED + STEP BY STEP GUIDE) Hey! Currently there's a bug with replay files that prevents replays from before the latest Rocket League patch to load/work. As a creator, this severely impacts my workflow, and waiting for a patch could take a while. So to make sure I, and everyone else out there can continue to work, I've tried to find a solution. Initially I messed around with installing older Rocket League versions through the steam console, and trying to get the Injector from Bakkesmod to downgrade to the matching Rocket League version, however this proved to be tedious and honestly fruitless. So instead I turned to the modding community where I was quickly directed towards Martin, who ended up fixing the replay issue and building a handy tool. WHAT YOU'LL NEED: RocketRP: Microsoft. NET 9.0 Runtime: HOW TO: Step 1: Download (if your antivirus flags it, allow list it. Running unknown files is ALWAYS at your own risk, however I run the setup as well and the sourcecode is available to check for when you're in doubt). Step 2: Download the .NET 9.0 console framework for windows, or your respective platform. Step 3: Install the .NET 9.0 console framework through the downloaded .exe Step 4: Unzip/Extract the "RocketRP .cli .zip" file Step 5: Right click the extracted folder and select "Open in Terminal". If that option doesn't appear you need to click more options, and / or open with, and manually select Powershell or your preferred terminal of choice. Step 6: leave the terminal window open and go to: %USERPROFILE%\Documents\My Games\Rocket League\TAGame\Demos Step 7: Select the replays you want and place these in a new folder somewhere easily accessible. Make sure to back them up just in case* Step 8: Right click the replay you want to fix, and then select "copy as path" Step 9: In notepad or similar, copy this command: .\RocketRP.CLI.exe -r " " -m Repack --backup --legacy-fix true Make sure to replace the " " with the link you copied from the replay in step 8. For a breakdown of the command, check the video or use the help command in the terminal. Step 10: In the terminal, paste the command we created in step 9, then press enter. This should create a backup file of your replay, and it should create a new replay file that has the patch applied. NOTE: Right now, doing full folders isn't working, therefore you'll have to do this 1 replay at a time, untill I post a fix in the comments. Step 11: Put the newly generated replay in the demos folder (step 6) and load back into Rocket League. Your replay should now work as intended! Please note if you get any errors, you mostlikely didn't install the .NET 9.0 console correctly, or you have to check your command for typos. Huge thanks to Martin for helping me out with this, here's his paypal if you want to show him some appreciation: And if you're feeling EXTRA generous, here's my youtube. Consider subscribing if this helped you out!: If you have any questions, leave them below and I'll try to answer them the best I can!

GGM1 Yota

14,018 次观看 • 1 年前

Alright, this one’s worth your attention if you’re building or deploying agents. Future AGI just open-sourced their entire platform and i don’t mean a trimmed-down version. this is the full stack: UI, backend, simulation engine, evals, optimization loop, observability, guardrails, gateway, docs. all in one repo. Apache 2.0. I’ve been putting it through its paces on production agents, and what stands out isn’t just the breadth it’s the architecture. Most of the current “agent reliability” stack is fragmented. tracing lives in one tool, evals in another, guardrails somewhere else. you end up manually connecting dots, and the agent itself doesn’t really improve you just keep patching prompts and hoping for the best. This flips that model. It’s built as a closed feedback loop: simulate failures → evaluate in real time → detect production issues → learn from them → generate fixes → validate against real traffic → check regressions → redeploy → monitor again And when something new breaks, the loop just runs again. no manual glue. The simulation piece is especially strong. instead of static test cases, it generates adversarial, multi-turn conversations based on how your agent actually behaves basically hunting for the exact scenarios where your system fails confidently. ran a few thousand simulations on our side… caught things we definitely would’ve missed. Evals run fast (sub-50ms) across modalities. not LLM-as-judge trained classifiers. guardrails are built-in, not layered on top. observability gives you step-level visibility into reasoning, cost, latency, quality. But the real shift is the optimization loop. Most tools tell you *what* broke. this system actually fixes it, validates the fix, and ensures nothing else regresses. That’s the missing layer. It’s clearly built with production in mind not a research demo. and the fact that it’s self-hostable makes it even more relevant if you’re running serious workloads. If you’ve been duct-taping together infra around your agents, this is probably the closest thing to a unified system i’ve seen so far. Worth checking out. If you're serious about deploying reliable AI agents, this is worth a look: 👉 You can also try it instantly (no setup) via their cloud version:

Aakash Verma

22,910 次观看 • 3 个月前

A SLAVE TO YOU. 2001 was her peak. It is easy and safe to say “Glad it was not me” and “I would have done it differently”. I see. Fame and Fortune is like dancing with a very large poisons snake and they always win. I have had, in a parallel former life, the chance to work with the very famous on their way up. The first thing I say is: “What goes up, will go down. Your career, your money (maybe) and your brain (most definitely) and just about every friendship”. This will happen to every single complex and all too human, human, some just do a good just a good job hiding it. No one is prepared for wealth and fame. Oh we all talk a big game, but no one is prepared. And the wealth and fame are a guarantee that when you fall, you fall hard. Oh you have the money to protect your fall but because of it your mind falls further than one could think is possible. You are so alone. Your parents, your grand parents, your siblings, your kids they all become part of what I call “The Elvis Syndrome”. To everything your constellation of folks around you say “Yes Elvis, that’s a real good idea”, to everything. See they assume, even if they don’t say it, that you must be a “genius” because they didn’t do what you did and they don’t have the money and fame. They assign genius to you and lesser to themselves. They dare not speak up. They prefer “Yes Elvis, have another fried peanut butter and bacon sandwich. You are not getting fat”. Long ago your burning starlight chased away any true friends, because even if they were strong to say truth, you believed your own public persona like everyone around you. You can not listen, you are the genius they have some job someplace. You also have just two options to anyone around you: 1) Your “crew” 2) People you pay And ironically they merge in to one and the same. All see your public persona and all see you as a means to get paid. Oh you go to “parties” with other rich and famous people but they are one of the above ultimately. Hierarchy forms around you and they naturally form a protection barrier. You have tantrums as fame rips you apart and you desperately try to become your public persona. Each layer you build to protect your all too human center moves you into more and more isolation. Shielded from real and needed pressures of life you are in your beautiful and well stocked velvet prison. You are now just a vehicle for moving money efficiently and surrounded by people that live off this largess. At the peak you may have advisors and they may seem to help. But they dare not tell you what they see even if they could see it. And most can’t see it because no one is prepared for it so they don’t have any better insight. This spans the enter ensemble of people that are now your satellites from gurus to lawyers, from plastic surgery doctors and fitness trainers. So what now? What if your dreams to “make it big”? Abundance does not fix a broken soul. And we all have this. Trauma is a great fuel, it will absolutely get you to orbit and you will shine, but trauma in orbit is the breaks that break you and when gravity wins, and it always does, you have no idea how to navigate going down. Trauma is what I have seen build everyone from Elvis to Steve Jobs. Trauma unresolved took them out. I am not saying your dreams are invalid and should not be your goal, I am saying that you don’t get a pass. No one does. And with fame and fortune it is nearly impossible to address it, because your ego can’t fit in a zip code. As you prepare for you fortune, and if you are reading this, you will have one, prepare your mind. Deal with the dark places that drive you. Make peace with the past, the people that did you wrong and mostly with yourself. But in this bargain you will remove some fuel for your rocket. It is the bargain. But it is the better path. We all will dance with the snake. But hopefully will know it. And you may have fame. Just don’t become a: “Slave to you”.

Brian Roemmele

115,188 次观看 • 7 个月前

Jocko Willink says the answer to tasks piling up is a small notebook, two consolidations a day, and 15 minutes of list review scheduled like an appointment. "First, first of all, definitely write the things down in one place." "It sounds like, since you're moving all the time or you're going to meetings, carry just a nice little notebook with you and write the things down as you get tasked with them." "Then on top of that, you have to have a master list of some kind, either paper or digital." "So if you get tasked something in a meeting in your little notebook, you come back, you put it in the right place in the master task list." "And then like twice a day to consolidate the information that's in the little notebook you have into the big master list." "Before you go to bed at night, you organize those things by priority on the master list. You put the most important thing at the top and that's what you're going to attack the next day." "That's part one on how you get these things organized. Now the part two is you got to schedule this stuff. And actually, I always say this when people have trouble with tasks, put them on the calendar." "Jamie does that for me. When Jamie's got something for me to do, she just doesn't email me and say, hey, you need to do this. She puts it on the calendar. So I look at my calendar, boom, there it is." "Put these things on your calendar. And that includes scheduling time on your calendar so that you can have time to consolidate your list and do a review of your lists." There is no "try harder" anywhere in his answer. The notebook catches it, the list ranks it, the calendar gives it a time, and the fifteen-minute review keeps the whole thing honest, so his head never has to hold any of it. That is the real fix for the kind of overload where none of the tasks are hard but they never stop coming: everything gets a place and a time, and whatever is still floating in your head is the thing taxing you. - Jocko Willink (Jocko Willink) on the Jocko Podcast (Jocko Willink)

Jay McHale

209,386 次观看 • 21 天前

Jensen Huang just reverse-engineered why Elon Musk operates at a speed no one on the planet can match. Three traits. The first is deletion. Huang: “He has the ability to question everything to the point where everything’s down to its minimal amount.” Most engineers solve problems by adding. Musk solves them by subtracting. Every part. Every process. Every assumption that survived because no one had the nerve to kill it. He picks it up. Asks if it’s load-bearing. If the answer is anything less than absolutely, it is gone. Not simplified. Not optimized. Removed. What survives is the skeleton. The bare physics of the problem. Nothing between intent and execution. Huang said it plainly. As minimalist as you could possibly imagine. And he does it at system scale. Not at a product level. Not at a department level. Across entire companies. Entire industries. Entire supply chains. He strips a rocket the same way he strips a meeting. Down to the load-bearing walls and nothing else. The second is presence. Huang: “He is present at the point of action. If there’s a problem, he’ll just go there and show me the problem.” Not a Slack message. Not a report filtered through four layers of people who weren’t there when it broke. He walks to the failure. Stands over it. Puts his hands on it. Most executives have never seen the actual problem their company is trying to solve. They have seen slides about it. Read summaries of it. Formed opinions about it in rooms that are nowhere near it. Musk stands over the broken hardware and does not leave until it works. That collapses the distance that buries most organizations. The gap between something breaking and the person with authority to fix it actually understanding what broke. In most companies, that gap is weeks. For Musk, it is hours. The third is the one that bends everyone around him. Huang: “When you act personally with so much urgency, it causes everybody else to act with urgency.” Every supplier has a hundred customers. Every vendor has a dozen priorities. Every manufacturer has a backlog stretching months into the future. Musk makes himself the top of every single one of those lists. Not by demanding it. By demonstrating it. When the CEO shows up at your facility at midnight. When he is moving faster than your own internal team. When his timeline makes yours look like a suggestion. You do not put him in the queue. You rearrange the queue around him. Huang watched this up close. Huang: “He does that by demonstrating.” Not by asking. Not by negotiating. Not by leveraging a contract clause. By moving so fast that everyone else’s normal pace feels like standing still. Three traits. Strip everything down. Show up at the failure. Move so fast the world rearranges around you. That is not a management philosophy. That is why one man runs six companies while entire boards cannot keep one moving.

Dustin

780,048 次观看 • 4 个月前