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In a world of PPO everything for reinforcement learning, I've been tinkering with SAC for training a quadruped gait. This gait is trained purely on CPU (training on one of the Dell GB10s) on a single environment. Training any particular run is obviously slower than PPO on an RTX...

26,758 Aufrufe • vor 6 Monaten •via X (Twitter)

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Would you want to be a teacher on your staff as a principal? I have often asked teachers, would you want to be a learner in your own classroom, but the question above for administrators could be even more critical. If we do not support those closest to students every day in an effective manner, it is much harder for things to improve in schools. If we want learning to look different in classrooms, then leadership must also evolve. This doesn’t mean that everything done in the past has been wrong. Some things that mattered 50 years ago will matter now, both in learning and leadership. But replicating everything that was done in the past, whether it was effective or not, isn’t a great strategy for moving schools forward. I was blessed to learn from some amazing principals in my career, but I also learned about things that I hated as a teacher and swore that I would do my best not to replicate those strategies. I wrote this in my upcoming book co-authored with Allyson Apsey (Allyson Apsey) titled, “What Makes a Great Principal”: “If we do things in our schools and classrooms that were done hundreds of years ago that still work today, we should continue to do them. On the other hand, if we do new stuff just because it is new, but it doesn’t work, we shouldn’t be doing it. Whatever works for our community is where our focus should be, no matter when it originated.” What worked in the past? What would you change? What would you have wanted as a teacher, and how can you make that happen? Simply replicating the strategies of the past, whether good or bad, will not necessarily lead education to a better future. Innovation is crucial to leadership as much as it is to teaching and learning.

George Couros

22,738 Aufrufe • vor 2 Jahren

One question that's been on my mind for years now is: could we use regular multimodal LLMs not necessarily trained for robotics to do the high level robotics intelligence part that VLAs and WAMs attempt to do? The latest explosion of powerful opensource multi-modal LLMs has, IMO, begun to make this possible due both to intelligence and speed. This is GLM 5.3 Flash, which has vision understanding, but isn't meant to be a VLA/VLM/WAM/robotics model at all, controlling an XGO mini wheeled robot quadruped with an arm & gripper. GLM 5.3F simply has access to the robot's high level SDK for controlling movement, arm joints, open/close gripper...etc. It analyzes the frames from the camera and makes adjustments all on its own to solve the task. Nothing was trained here, nothing fine-tuned for this task. Z AI did not make this model for robots and tbh I think they're surprised this works when I talk to them about it! This also works quite well with DSV4F + a vision capable model like Qwen 3.8 27B. I havent tried JUST Qwen 3.8 27B, but I'm sure it works too. I like the "logic" to be a model that's as fast as possible (but still intelligent). There's also an experimental vision version of DSV4F, I'm confident that'll work too and might even be better bc the full loop might be the fastest of all with this model. An obvious question you might wonder is: well why not use VLA or VLM? The hard part about robotics isn't object detection, that's long solved. This also isn't a solution for gait/locomotion...yet, but I actually don't think this is far away either and I've done some experimentation with LLMs in this space in the past and it does show promise. It might actually already be here for quadrupeds, since you dont need super fast IMU readings to maintain balance. I've also tried many of the larger, more generalist, VLAs that you should be able to use with popular robots and tbh there are just so many edge cases that make things hard and not work. You gotta get the camera, lighting, task, everything *just right* or the demo fails. This is for the actual hard part in robotics right now: intelligence, logic, and planning for all the ways the real world just simply isn't perfect. I've trained VLAs. They're super finicky and you're always running into sim2real issues, especially around the camera. You also have to build the whole training pipeline in a simulator, and, if everything does work, you still just have a robot that does this 1 single thing after weeks of work. If you use teleop, this overcomes the "2real" problem, but now you need to painstakingly collect teleop data, and it's only good at that specific task and that particular robot. There is a growing set of egocentric training data for "general purpose" VLAs and world action models (for humanoid form factors), but I'm really starting to wonder: Why? I think we might just sidestep this whole area of research entirely. I didn't need any training data or special environment to work with this quadruped and arm to do the task I was after. This particular quadruped and arm doesn't even exist in the wild yet really, it's a demo build from a company launching it on kickstarter, so it's not like this robot's data exists in the LLM to any real extent. I think this is cool as heck that this works and I am interested to see just how far I can push it. Also this marks the first time that I've finally got a generalist solution to a task I've been trying to solve ever since I became a dad of twins: pick up toys off the ground. This is a big day!

Harrison Kinsley

41,898 Aufrufe • vor 1 Tag

Kevin O’Connell tells Vikings QBs he doesn't care if they throw interceptions in training camp “There are so many things in society, not even just football nowadays, where we want to decide in a moment this guy can or can’t, this guy’s a success or failure. And it’s just not in alignment with the reality of the position or our game.” “Everything should be driven by process, and part of process is failure. Every year in training camp I give my yearly State of the Union on the first practice: ‘Just as a heads up, I’m not going to be commenting on you guys taking your stats every single day. So-and-so went 6-of-11 with two interceptions, and then we chart it for the whole training camp and decide who won or lost this position or quarterback battle.’” “I challenge the quarterbacks all the time: we’re against Brian Flores every day. This is going to be a 10-out-of-10 stress for all of us. There are going to be good days and there are going to be bad days, but I want you to be aggressive with your decision-making.” “How will we know on third-and-eight in Week 12 that you can try to fit a ball in there to Justin Jefferson on a backside in-cut? How will we know if you don’t try to do it now?” “So when you do it now, and you take the proper footwork and try to throw it into a tight window and the ball gets tipped and intercepted, let’s go back and look at it first. I’ve got no problem with the decision. What was your footwork like? Were you in your base, balance, body position? Were you playing on the timing of the play? Did you make the protection call you needed?” “If you did all those things and it was just a blade of grass different from being the best completion you had all day, now you know.” “I can finish up a practice and go to the podium and have people say, ‘So-and-so really struggled today, didn’t you think?’ And I’m like, there’s not enough time in the day for me to explain all the reasons why you’re wrong. We’re going to go in the quarterback room, we’re going to watch it, and we’re going to be better tomorrow.”

Josh Chambers

355,484 Aufrufe • vor 9 Tagen

Q: It must be complicated, when I listen to you, to have a private life, somebody to understand your passion and to share this moment. Lewis: "It really is, especially I would say more so today than ever before, which is the way the world is, you know. I look at the other drivers and I wonder how they're doing it. You know, some are having kids and some married, some, you know, most of them girlfriends. I did that when I was in my 20s, but I took a decision to really to maximize my time that I have here because it's not as long as you think and it's limited, you know. And I don't want to look back and be like, ah, if I just gave a little bit more here, I didn't sacrifice my time because I was committed elsewhere." "So I really focused in these last, you know, particularly these last 10 years, like get everything I can out of my performance. Then when I retire, then I can do whatever I want. You know, I can dedicate my time to whatever else it is and not have to worry." "But in this competition time, focus on health, well-being, my mental health, my driving technique, being as good an engineer as I can be, and also being the best teammate that I can potentially be for the guys that I get to work with. That's my sole focus. You know, I want to win." "I've been fortunate enough to win with great teams in the past. Particularly, obviously, with Mercedes and with McLaren, which was incredible. And my dream is to win a championship with Ferrari." "And that's something that hasn't been done for a while. But they have absolutely every ingredient that's needed to win. It's just like getting all the pieces of the puzzle in the right place. And that's what I'm trying to work on in the background with Fred and the whole team." [📹 VIGNERON GAETAN]

sim

86,907 Aufrufe • vor 1 Jahr

#SOLAR and #MOONBYUL speaking about #MAMAMOO's comeback 🐰 Next year... the article got released first, it's about Mamamoo's comeback. Rather than saying clearly that there will be (a comeback), but right now, we are in the situation where there are things that needs to be coordinated. So I think it's difficult for us to say anything about it now. 🐹 Because we don't know what will happen in the future 🐰 That's right, I think that's is why we are being careful about how we are saying things now. Whenever moomoos asked us this question, the reason why we can simply say it out is because we are at the stage where we are still coordinating. 🐹 Nothing's confirmed. 🐹 We would love it if we can do it (comeback) Because we are Mamamoo, it'll be good if we can do it 🐰🐹 But since we are in different companies 🐰 There are many things needed, the coordination etc. 🐹 If we were to comeback as Mamamoo, we would like to do it properly, just like putting all our energies into it 🐰 I want to do it properly from the start till the end 🐹 And go meet lots of fans 🐰 That's right, but since there are still coordinations that needs to be done, so I seek for your understanding 🐹 The companies are speaking with each other now as well 🐹 I had the thought of wanting to address this to all of you 🐰 Many people are asking this everywhere rather than just passing it on with a short remark, but since this is an important thing, so I think it's difficult for us to just say anything now. 🐰 As we're on this topic now, we do not have any firm answers I hope all of you can understand. 🐹 If things are confirmed, I think we will say it together like 'all of you have waited for a long time right!'. Rather than making all of you wait blindly, that's the reason why we can speaking on this carefully.

ㅌㅂ/TV

104,367 Aufrufe • vor 9 Monaten

This soldiering training is the most impressive and immersive I've ever tried. It is 10x better than a YouTube tutorial video. It really allowed me to see the procedure from all the points of view, and even get super close to get the details. It is a collaboration between @gracia_vr and Imperial College London: they recorded a soldering session with Gaussian Splatting Videos (4DGS), so that you can enjoy it from your VR headset. You can see the action happening in front of you; you can pause and re-watch what you need, change the point of view, get closer, get more distant. And the quality with which it has been shot is impressive: I enjoyed this experience with my DELL Pro Max Tower T2 with NVIDIA Pro RTX 6000, and I could really see all the small details of the PCB that was being soldered! I was really impressed by it. But I also noticed some drawbacks. First of all, some scenes have artifacts that make seeing the details of the PCB hard. I think when it comes to training involving small details, the capture and reproduction of the splat should be flawless. Then, as much as I loved it as a passive experience, I would have liked to have also some sort of practice session in VR. The power of VR is to let you learn by doing in full safety, and this kind of training does not exploit it. But maybe the best way to enjoy it would be in MR, where you have this training video close to a real workbench where you do the actual soldering while following the tutorial. Gaussian Splat can really revolutionize training: this kind of recording is much better than any flatscreen experience, and more accurate than any 3D CGI recostruction. I suggest you give it a go at this experience in the Gracia app (it's free). Then let me know your impressions! #VirtualReality #training #DellProPrecision #GaussianSplat #technology [Disclaimer: I'm a DELL Pro Precision Ambassador, and this is why I mentioned the model of my PC. I have been given a PC to do cool tests and share my results on social media. No monetary compensation or sales affiliation is part of the collaboration]

TonyVT SkarredGhost

38,264 Aufrufe • vor 24 Tagen

Alan Watts on why meditation has no purpose: Alan Watts begins by explaining the first basic reason for meditation. It interrupts our constant internal monologue: "Now, obviously, if I talk all the time, I don't hear what anyone else has to say. And so in exactly the same way, if I think all the time, that is to say, if I talk to myself all the time, I don't have anything to think about except thoughts. And therefore, I'm living entirely in the world of symbols and am never in relationship with reality." But then Watts pivots to a deeper, more counterintuitive point: meditation, properly understood, has no purpose at all. He compares it to music and dancing: "When we make music, we don't do it in order to reach a certain point, such as the end of the composition. If that were the purpose of music, to get to the end of the piece then obviously the fastest players would be the best." The same applies to dance: "When we dance, we are not aiming to arrive at a particular place on the floor, as we would be if we were taking a journey. When we dance, the journey itself is the point. When we play music, the playing itself is the point." This is where Watts delivers his core insight about meditation: "Meditation is the discovery that the point of life is always arrived at in the immediate moment. And therefore, if you meditate for an ulterior motive, that is to say, to improve your mind, to improve your character, to be more efficient in life, you've got your eye on the future and you are not meditating." Watts argues the future is an illusion we chase at our own expense: "Because the future is a concept. It doesn't exist. As the proverb says, 'tomorrow never comes.' There is no such thing as tomorrow. There never will be. Because time is always now." He pushes back against how religion has framed contemplative practice: "Meditation is supposed to be fun. It's not something you do as a grim duty. The trouble with religion as we know it is that it is so mixed up with grim duties. We do it because it's good for you; it's a kind of self-punishment." Watts closes with what he calls the real essence of the practice: "It's a kind of digging the present. It's a kind of grooving with the eternal now and brings us into a state of peace where we can understand that the point of life. The place where it's at is simply here and now."

Mateus — eu/acc 🇪🇺

13,102 Aufrufe • vor 4 Monaten

ELON MUSK: We believe the AI5 chip will be roughly comparable performance to an NVIDIA Blackwell, and at much less than 10% of the cost Transcription: I'm super hardcore on chips right now as you may be able to tell. I have chips on the brain. I dream about chips, Literally! Because in order to have a functional robot, you have to have a great AI chip. And it needs to be an inexpensive chip and it needs to be very power efficient So we think we believe the AI5 chip will be probably about a third of the power of say something like a Blackwell, an NVIDIA Blackwell, which is a great chip, for roughly comparable performance. And much less than 10% of the cost. This is a chip that is very much optimized for the Tesla AI software stack. So it's not meant to be a general purpose chip, it's meant to be an amazing chip for the Tesla AI software And I mean a couple of things that I think make... like how is Tesla able to achieve such an improvement? I think it is because we are specialized. We're not trying to... you know, NVIDIA has to serve the superset of all past and future customers. So all of their requirements, all of the software that they've written has to work, which is a very difficult problem. Whereas we just need to make it work for our software. And so we're able to simplify the chip dramatically And then we also, I think we're unique in this, but like we have an integer-based system. And integer operations are fundamentally more efficient than floating point operations. So we can do floating point, but the vast majority of our inference is done in integer. Which is, if you're familiar with sort of logic gates, the simplicity of integer... it's integer is much more power efficient, much more silicon efficient, but you have to, you actually have to train for integer inference, which everyone else is training for floating point. That's kind of like a niche technical detail, but it's actually very important. So, yeah, this is going to be a great chip So this chip will be made in basically in four places: TSMC Taiwan, Samsung Korea, TSMC Arizona, and TSMC Texas. And we already know what improvements to make for AI6. So I'm hopeful that we can within less than a year of AI5 starting production, we can actually transition in the same fab to AI6 and double all of the performance metrics

X Freeze

305,109 Aufrufe • vor 10 Monaten

Naval Ravikant: "The only true test of intelligence is if you get what you want out of life" "There are two parts to that. One is getting what you want, so you know how to get it. The second is wanting the right things, knowing what to want in the first place. I could want to be a 6'8" basketball player and I'm not going to get that. That's wanting something you can't get. But there's also wanting something that's a booby prize, prizes that are just not worth having, or that create their own problems." Naval explains how people end up in places they never meant to be: "If you're not careful, you can end up in a place in life not only that you don't want to be, but one you didn't even mean to get to. Usually people end up there because they're going on autopilot with societal expectations. Or out of guilt. Or out of mimetic desire, our desires are picked up from other people. Go to law school, go to med school, go to business school. Or it might be what your parents expect. Guilt is just society's voice speaking in your head so you'll be a good little monkey." He shares a problem most people have: "We run on these four-year cycles. You join a startup, you vest over four years. College is four years. High school is four years. You go to law school, that's a 5-year cycle. You become a lawyer, that's a 40-year cycle. These are very long cycles. But the amount of time we spend deciding what to do and who to do it with? Very short. We spend one month deciding on a job where we're going to be for 10 years." Naval's rule: "If you're making a four-year decision, spend a year thinking it through. Really thinking it through. 25% of the time." He explains the Secretary Theorem: "It turns out the optimal time to search is about a third. By a third of the way through, you've seen enough to know what the bar is. Then anybody who meets or exceeds that bar is good enough. But here's the key: it's not time-based. It's iteration-based. You need to take opportunities quickly and bail out quickly. If you look at failed relationships, the biggest regret is usually staying after you knew it was over." Naval reframes the 10,000 hour rule: "Malcolm Gladwell popularized 10,000 hours to mastery. I'd say it's actually 10,000 iterations to mastery. Iteration is not repetition. Repetition is doing the same thing over and over. Iteration is modifying it with learning and doing another version. That's error correction. If you get 10,000 error corrections in anything, you will be an expert." On pessimism vs. optimism: "You want to be skeptical about specific things, every specific opportunity is probably a fail. But you want to be optimistic in the general. Something in here is going to work out. If something fails, it was a learning experience. It was an iteration. As long as you learned something, it's a win. You don't want to jump into the first thing. But once you find the match, you have to be willing to go all in. Move your chips to the center of the table." He concludes: "Most people are stuck in this gray bit. 'I'm half in, but I don't really know.' That doesn't work. It's a barbell strategy, black or white. Explore quickly, cut losses fast. Then when you find the right thing, compound into it."

Jaynit

74,450 Aufrufe • vor 5 Monaten