551–560 of 584 posts
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It’s because their products are really bad. Last time I tried Gemini it repeatedly lied about running internet search when explicitly asked to do it. I know their models benchmark really well, but in real world the performance is abysmal.
Maybe it was just using Google Search, and not finding anything ...
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I don't know how you can read my comment, not respond to my comment saying that today's self-driving cars use LIDAR, and continue to reiterate your point. I don't think I was clear and explicit, it being tedious to write, and I apologize for that. I also apologize for shifting the goalposts as I had not written out my own position, which is not exactly in the "grandparent commenter"'s position (that I had not previou…
Precisely how is the inclusion of LIDAR counter to the bitter lesson?
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I don't know how you can read my comment, not respond to my comment saying that today's self-driving cars use LIDAR, and continue to reiterate your point. I don't think I was clear and explicit, it being tedious to write, and I apologize for that. I also apologize for shifting the goalposts as I had not written out my own position, which is not exactly in the "grandparent commenter"'s position (that I had not previou…
Tesla's entire fleet runs on raw cameras. Including the driverless Robotaxi vehicles - which are basically a 1:1 match to how Waymo operates. Plenty of hecklers were saying "you can't self-drive on cameras", and some still try. But Tesla's self-driving on cameras, and it seems to work fine. While Waymo's self-driving on fat sensor stacks, and it also seems to work fine. Sensors don't seem to be a differentiator of se…
I can't evaluate how true or sensationalist this story is, but this bearish article suggests to me that Tesla robotaxis today isn't yet the success you are painting https://electrek.co/2026/07/03/tesla-robotaxi-miami-service-...
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This is absolutely not true check out Sunday robotics and their robot that folds clothes. Sunday robotics says it does holding of clothes correctly 99% of the time that is real world usage today. They even have three hour video of the robot folding the clothes.
No, the above is absolutely exactly true. Robots folding clothes and tying shoelaces etc is nothing but a tech demo at this point. It's difficult to grok this because if you watch a human folding a t-shirt, you can reliably predict that the same human will fold a different t-shirt just as well, and in fact be perfectly capable of folding a wide variety of other clothes items as well. Not so for robots. With robots, w…
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Seems like production ready is 2-5 years out though. Not a very long time
you mean like the self driving car which elon promised ten years ago. :D Robotic vision AI is far more complex than an LLM
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>But how does LLMs help in making chat bots better, help with this "multi-sensory" data. All three offerings from the linked blog post are either Vision LLMs or Vision/Action LLMs.
Action LLMs work by generating text underneath. Just some higher level software interprets the text generated and do some action. So the immediate inference result is still text. That does not help a lot.
This isn't true.
Obviously there is a lot of variety in architecture, but in the prototypical example there are vision and languages encoders and an action decoder which decodes direction into action steps. Eg, Hugging Face SmolVLA:
> Specifically, the VLM processes sensorimotor states, including images from multiple RGB cameras, and a language instruction describing the task. In turn, the VLM outputs features directly fed to the action expert, which outputs the final 3 continuous actions.[1]
Or NVidia's GR00T N1:
> A diffusion transformer (DiT) processes the robot’s proprioceptive state and action, which are then cross-attended with image and text tokens from the Eagle-2 VLM backbone to output the denoised motor actions.[2]
(Emphasis mine)
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I have a dishwasher and I still usually just hand wash. It takes about 10 seconds to wash a dish. The side benefit is all your dishes are always available. With the dishwasher, up to one full dishwasher load are dirty at any time, which means you need more dishes and more cupboard space than someone without a dishwasher. If the robot is going to clear your dishes and wash them for you right away, what's the dishwashe…
Mostly to save water and energy. I have a hard time believing the robot would be more efficient washing dishes by hand.
I'm not saying people who already have a dishwasher will throw it away. But a robot makes installing a new dishwasher much less tempting.
At my utility prices, it costs about 5¢ to hand-wash one serving (plate, pan, glass, utensils, and a bowl) with running water. That's not nothing, but it's dwarfed by the energy use of using the oven and the supply-chain energy and water use of the food if it includes meat.
People will casually waste 10x that energy without a second thought when they don't need to just because it's convenient, or because they're used to doing things that way.
The dishwasher looks more unfavorable if you're considering installing one in a small apartment or condo. Apart from the cost of the dishwasher, you need space to install it, and more cupboard space to keep more dishes, glasses, etc. For an extra 4¢ per person-meal, having your robot do the dishes buys you the convenience of skipping all that and having all your dishes clean and ready all the time.
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Yeah, look carefully at that demo of tying the garbage bag strings: it's done in a very peculiar style that suggests a very specific, very precise, "algorithm" taught in an imitation learning session, which has no chance to transfer to other tasks, or even other garbage bag strings. As usual with robot tech demos: WYSIWYG.
Did the past decades of AI research teach you absolutely nothing? Every time you see something that "suggests a very specific, very precise, "algorithm" taught in an imitation learning session"? Scale the imitation learning up x10, x100, x1000, and it suddenly generalizes! I'll be honest: I don't see what you see. I don't see anything that would suggest this algorithm is so brittle there's zero transfer to "even othe…
Before I put in the effort to reply in good faith I have to know: do you think we're going to have a conversation or are you going to fulminate and scold me like some kind of all-important authority (which I have to say you clearly are not)?
To clarify, I'm happy to have a curious and respectful exchange.
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No, the above is absolutely exactly true. Robots folding clothes and tying shoelaces etc is nothing but a tech demo at this point. It's difficult to grok this because if you watch a human folding a t-shirt, you can reliably predict that the same human will fold a different t-shirt just as well, and in fact be perfectly capable of folding a wide variety of other clothes items as well. Not so for robots. With robots, w…
You make some very good points about the ACT-2 if it’s nine garment types that’s still very acceptable but the point you bought up about them training on exactly those pieces of garments is a possibility.
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Action LLMs work by generating text underneath. Just some higher level software interprets the text generated and do some action. So the immediate inference result is still text. That does not help a lot.
Depends entirely on VLA arch. Some have dedicated action diffusion heads that work in a standalone non-text action output space. Much like an LLM can either use an external TTS or have audio output heads attached to it directly for native S2S. But your entire premise is wrong regardless of that. Even if VLAs were forever bound to outputting text, you'd have to prove that they're fundamentally incapable of emitting te…
You don't understand what I am saying. The crux of your misunderstanding is here
>emitting text that maps to useful action sequences
If you have a static mapping from text to action, then you are throwing away all the advantage of using an AI. The whole point of AI is that you can get an output from an input without explicit mapping. So If you use explicit mapping anywhere in the chain, then you lose most of the advantage of using the AI.
So if your hardware, physical vocabulary is limited, like move left/right/up/down then what you say could work. But something that have the dexterity of a human form, this vocabulary is nearly infinite. You won't be able to use explicit mapping there.