41–50 of 77 posts
“I may not care if my household robot takes all night to tidy up and fold the laundry.” I do. I don’t want robot vacuuming or making noise at night or doing something potentially dangerous unmonitored while people are asleep.
Not folding the laundry, though.
Earlier quoted context omitted.
That would only be a minor marker. A major marker would be whatever the Chinese equivalent(s) of Amazon are (Alibaba? etc.) going that route successfully. From academic / industrial conference presentations it appears Chinese services are banking on automation far more than an entity like Amazon does. That being said, I don't know what exact state the industrial automation technology is there and I can only extrapola…
Not sure about that. Labor costs are lower in China and the CCP is strongly incentivized to keep enough jobs around for humans to maintain their own hold on power.
People think robots in terms of humanoid or number-5 style robots. I think it'll be more capable appliances at first. Like a lawn mowing device that also spots weeds and can spray them. Next iteration has arms to rip weeds out of the garden. Next has attachments so you can direct it to do pruning. Next it can figure out the pruning itself and move the outcome into the woodchipper. And so on and so on. It's not going…
That's available as a tractor-pulled implement for farms. Deere and some others make such things.
I feel this is actually somewhat straightforward. I assume deep water on roadways is not commonly in the training set, because frankly it isn't common in real life, and when it is common people do not drive and do not gather that training data. As a result the proper response has not adequately been beaten into the models. There are probably also challenges of world-sensing, since water can act as a mirror, and maybe other complications. So waymos are bad at handling deep water on roadways. However, deep water on roadways is also not common in the areas where waymos are deployed. As a result, waymo's have a great safety record, and at the same time they make mistakes that are obvious to a human.
A common criticism of AI discourse is that people act as if LLM's "think". I don't want to be a vocabulary purist, but I suspect that's related to the astonishment here -- the Waymo doesn't know what flooding is, it doesn't fear drowning, it doesn't think. So unless it's been repeatedly trained, or a special case has been hard coded by manual effort, it doesn't know that flooded roadways are dangerous.
I have made a lot of assumptions here, and I don't truthfully know what the training data looks like. Feel free to push back if you think my assumptions are wrong. I'd especially be interested if somebody can show that water on roadways _is_ in the training data
Maybe in another 2 decades I could see it possibly starting to change, but even then I wouldn't bet the horse on it until I saw it. Cars only have three degrees of freedom and even that we are barely able to get working well enough to put it into limited practice. And yet one single human finger has atleast 3 degrees of freedom, and is covered in what is the equivalent of a million tiny ultra sensitive tactile sensors.
Roboticist here. All of this, and he didn’t mention compliance or online adaptation to otherwise un-sensable dynamics. Or massively complex miniature mechanisms. Current generation tactile sensors cost a couple thousand $ PER FINGER, and have a real world MTBF of hours. The cost can be solved with economy of scale. The fragility is harder.
I'm picturing humanoid robots having to operate in pairs so they can constantly fix each other.
Earlier quoted context omitted.
Eat? You must be living under a rock. We've been evaporating our sustenance and storing it in the cloud for years. Perhaps nanobots will be able to carry the chemical makeup of a cheeseburger and rebuild a bite directly in our mouths, no cooking necessary!
Remember though, there is no food cloud really, just other people's fridges.
Roboticist here. All of this, and he didn’t mention compliance or online adaptation to otherwise un-sensable dynamics. Or massively complex miniature mechanisms. Current generation tactile sensors cost a couple thousand $ PER FINGER, and have a real world MTBF of hours. The cost can be solved with economy of scale. The fragility is harder.
>> It will be difficult to match this scale of breadth and depth of data for physical tasks. There’s no straightforward equivalent of “just Efficient learning, generalization, and adaptability / on-the-job learning seem like requirements.
Isn’t this the idea of NVIDIA’s Isaac? Model based adaptive learning in virtual environments for robotic systems? Or is this oversold?
> Once they have context, robots will need to reason, plan, and exercise judgement and common sense. LLM-based systems like ChatGPT and Claude are making great strides in these areas
But why would I want to make AI more powerful - and disruptive - than it already is? I don't see this as a benefit but as a disadvantage. Let's also not forget that e. g. Google deliberately ruined its search engine. Now if you search something, by default, you get AI slop results that are often not truthful or only partially truthful. This is a private web. Google wants to control information.
A marker of progress will be when Amazon converts to automated picking. They've been trying hard for almost a decade now. They had an annual competition for years. They have a decent picking robot developed in house.[1] It's not being deployed in quantity yet. Nor does it have anything like a humanoid hand. Just a two-surface gripper. Amazon's production robots are mostly automatic guided vehicles, not manipulators.…
Their robots do movement using sliding scale in 3D spaces (think poles that are left right, up and down, and the "picker" being able to glide and move. They currently have a ceiling slider that goes down and suctions things into a pneumatic tube to then end up in my grocery bag. IMHO it works pretty well - especially considering that delivery is ~$8 for me.
Ultimately we're going to end up with several different types of robots, and not with a human centric vision. The question is if bipedal is a long term dead-end, and merely a short term method to fit into the world we currently have designed.