141–150 of 183 posts
I just wrote a reply to a comment talking about the AI tells this writing has, but it got flagged so my comment disappeared when I hit post. I'll rephrase out of spite: My first thought upon reading this was that an LLM had been instructed to add a pithy meme joke to each paragraph. They don't make sense in context, and while some terminally online people do speak in memes, those people aren't quoting doge in 2025. T…
Earlier quoted context omitted.
I think you vastly underestimate how difficult the task you are proposing would be without depth or pressure indication, even for a super intelligence like humans. Simple concept, pick up a glass and pour its content into a vertical hole the approximate size of your mouth. Think of all the failure modes that can be triggered in the trivial example you do multiple times a day, to do the same from a single camera feed…
The point is how much non-vision sensors vs pure vision, helps humans to be humans. Don't you think this point was proven by LLMs already that generalizability doesn't come from multi-modality but by scaling a single modality itself? And jepa is for sure designed to do a better job at that than an LLM. So no doubt about raw scaling + RL boost will kick-in highly predictable & specific robotic movements.
Could you expand on what you mean by this?
I didn't understand a single word about this post and what was supposed to be solved and had to stop reading. Was this actually written by a human being? If so, the author(s) suffer from severe language communication problems. Doesn't seem to be grounded at least with reality and my personal experience with robotics. But here's my real world take: Robotics is going to be partially solved when ROS/ROS2 becomes effecti…
But besides that, you‘re totally right. It’s too „loose“ since to realize that idea the process would have to be way different (and properly explained)
I just wrote a reply to a comment talking about the AI tells this writing has, but it got flagged so my comment disappeared when I hit post. I'll rephrase out of spite: My first thought upon reading this was that an LLM had been instructed to add a pithy meme joke to each paragraph. They don't make sense in context, and while some terminally online people do speak in memes, those people aren't quoting doge in 2025. T…
I'm using eigenrobot's (X user) prompt for ChatGPT and the style is very recognizable. Everything lowercase, tone, zoomer abbreviations, esotheric style of jokes.
I didn't understand a single word about this post and what was supposed to be solved and had to stop reading. Was this actually written by a human being? If so, the author(s) suffer from severe language communication problems. Doesn't seem to be grounded at least with reality and my personal experience with robotics. But here's my real world take: Robotics is going to be partially solved when ROS/ROS2 becomes effecti…
If I had to guess, it seems likely that there will be a serious cultural disconnect as 20-something deep learning researchers increasingly move into robotics, not unlike the cultural disconnect that happened in natural language processing in the 2010s and early 20s. Probably lots of interesting developments, and also lots of youngsters excitedly reinventing things that were solved decades ago.
Earlier quoted context omitted.
> Pure vision will never be enough because it does not contain information about the physical feedback like pressure and touch, or the strength required to perform a task. I'm not sure that's necessarily true for a lot of tasks. A good way to measure this in your head is this: "If you were given remote control of two robot arms, and just one camera to look through, how many different tasks do you think you could comp…
> It therefore follows that robots should be able to learn with just RGB images too! I don't see how that follows. Humans have trained by experimenting with actually manipulating things, not just by vision. It's not clear at all that someone who had gained intuition about the world exclusively by looking at it would have any success with mechanical arms.
1. First create a model that can evaluate how well a task is going; the YT approach can be used here.
2. Then build a real-world robot, and train it by letting it do tasks, and use the first model to supervise it; here the robot can learn to rely on extra senses such as touch/pressure.
Pure vision will never be enough because it does not contain information about the physical feedback like pressure and touch, or the strength required to perform a task. For example, so that you don't crush a human when doing massage (but still need to press hard), or apply the right amount of force (and finesse?) to skin a fish fillet without cutting the skin itself. Practically in the near term, it's hard to sample…
> Pure vision will never be enough because it does not contain information about the physical feedback like pressure and touch, or the strength required to perform a task. I'm not sure that's necessarily true for a lot of tasks. A good way to measure this in your head is this: "If you were given remote control of two robot arms, and just one camera to look through, how many different tasks do you think you could comp…
There are an infinite number of scenes that can be matched to one 2d picture. And what is a scene really? The last time I checked, RGB was not a good way of input in Computer Vision and rather relied on increasing levels of gradients via CNNs to build a compositional scene. None of that is paticularly translatable to how a LM works with text.
Earlier quoted context omitted.
Spoiler: not solved
Indeed, the robotics edge-case problem space complexity balloons far faster than most assume. Physics informed training is a real methodology (simple introduction to the subject: https://www.youtube.com/@Eigensteve/videos ). However, the slop article is 80% nonsense. =3
Earlier quoted context omitted.
I think you vastly underestimate how difficult the task you are proposing would be without depth or pressure indication, even for a super intelligence like humans. Simple concept, pick up a glass and pour its content into a vertical hole the approximate size of your mouth. Think of all the failure modes that can be triggered in the trivial example you do multiple times a day, to do the same from a single camera feed…
A routine gesture I've done everyday for almost all my life: getting a glass out of the shelves and into my left hand. It seems like a no brainer, I open the cabinet with my left hand, take the glass with my right hand, throw the glass from my right hand to the left hand while closing the cabinet with my shoulder. Put the glass under the faucet with left hand, open the faucet with the right hand. I have done this 3 s…
If you were to just do the exact same robotic "throw" action with a glass of unexpected weight you'd maybe not throw hard enough and miss, or throw too hard and possibly break it.
Pure vision will never be enough because it does not contain information about the physical feedback like pressure and touch, or the strength required to perform a task. For example, so that you don't crush a human when doing massage (but still need to press hard), or apply the right amount of force (and finesse?) to skin a fish fillet without cutting the skin itself. Practically in the near term, it's hard to sample…
> Pure vision will never be enough because it does not contain information about the physical feedback like pressure and touch, or the strength required to perform a task. I'm not sure that's necessarily true for a lot of tasks. A good way to measure this in your head is this: "If you were given remote control of two robot arms, and just one camera to look through, how many different tasks do you think you could comp…