> filling the need for labor in jobs that are too physically stressful or too dull for humans to want to do
That's a disturbing sentence. Most jobs are "dull". Peolpe work not to fill their otherwise empty existence, but in order to earn money. Dullness could be solved by making the tasks less dull, or empowering employees (even if the term has been abused).
The sentence is also dishonest. Businesses want robots to save costs and increase profits, not to make their employees happier.
>It needed to achieve the lifting limits recommended under the U.S. National Institute for Occupational Safety and Health guidelines for human workers, which include repeatedly lifting 23-kg bins and reaching shelves 1.75 meters high. Digit is designed to perform tasks like these for 20 hours a day—something no human can do.
I think that rather underestimates what people can and have done (cue John Henry story).
I worked in an Amazon warehouse for two different stints:
and it was rather like a gym membership which I couldn't skip out on (glances at exercise equipment cluttering living space) and during which I could ponder life choices and consequences while wishing there was a soundtrack/music.
That said, this sort of thing, LLMs/AIs and data centers, and so forth feel like a perfect storm leading up to singularity (as envisioned by some optimistic science fiction authors) or something far worse, cue Marshall Brain's novella "Manna":
The main appeal for human robots in general is that, in theory, they can go wherever humans can go. As soon as a facility has stairs or even a single step up wheeled robots can't work.
Very nice video. Comparing to the channel's latest, I guess the channel itself experienced evolution, with the Algorithm and clicks as its fitness function...
Are these kind of robots even economically viable? I've seen them doing work that would generally pay like $3/h. And human after a week is significantly faster.
>As of late 2026, Amazon’s U.S. warehouse hourly pay generally ranges from about $18 to $22 for most roles.
That said, after a while, one can be surprisingly fast when picking --- on one occasion I walked up to a bin full of non-descript cardboard boxes, grabbed one, spun it in my hands for the six-sided box check and scanned it to verify it was the correct pick, and then was asked to explain how I had gotten that right by a trainer w/ a bunch of trainees--- it seemed like almost five minutes of explanation of minor differences in cardboard texture, box shape, construction and so forth to explain how it was that at first glance, that was the only correct choice.
I've always wondered if LLMs would arrive at a similar conclusion with on-going training as they are used.
> filling the need for labor in jobs that are too physically stressful or too dull for humans to want to do
That's a disturbing sentence. Most jobs are "dull". Peolpe work not to fill their otherwise empty existence, but in order to earn money. Dullness could be solved by making the tasks less dull, or empowering employees (even if the term has been abused).
The sentence is also dishonest. Businesses want robots to save costs and increase profits, not to make their employees happier.
>It needed to achieve the lifting limits recommended under the U.S. National Institute for Occupational Safety and Health guidelines for human workers, which include repeatedly lifting 23-kg bins and reaching shelves 1.75 meters high. Digit is designed to perform tasks like these for 20 hours a day—something no human can do.
I think that rather underestimates what people can and have done (cue John Henry story).
I worked in an Amazon warehouse for two different stints:
https://www.reddit.com/r/EDC/comments/dmnuts/53mamazon_fulfi...
and it was rather like a gym membership which I couldn't skip out on (glances at exercise equipment cluttering living space) and during which I could ponder life choices and consequences while wishing there was a soundtrack/music.
That said, this sort of thing, LLMs/AIs and data centers, and so forth feel like a perfect storm leading up to singularity (as envisioned by some optimistic science fiction authors) or something far worse, cue Marshall Brain's novella "Manna":
https://karmak.org/archive/2003/12/manna/manna1.htm
Very beautifully written.
Does it even need legs? For most of these factory use cases would it not be more efficient/cheaper to have a version that has wheels to get around?
The main appeal for human robots in general is that, in theory, they can go wherever humans can go. As soon as a facility has stairs or even a single step up wheeled robots can't work.
And some kind of bin holding attachment would be far more efficient than using arms and 'fingers'
One needs legs to allow for more intimate appendages that sell.
The market for souped-up vacuum cleaners is already saturated.
Can anyone explain that if we had this more than 10 years ago:
https://www.youtube.com/watch?v=kQ2bqz3HPJE
we are still struggling with making a robot walk?
Very nice video. Comparing to the channel's latest, I guess the channel itself experienced evolution, with the Algorithm and clicks as its fitness function...
I think people can make robots walk, but it's really expensive and not particularly useful if most of what the robot does is walking.
Are these kind of robots even economically viable? I've seen them doing work that would generally pay like $3/h. And human after a week is significantly faster.
>As of late 2026, Amazon’s U.S. warehouse hourly pay generally ranges from about $18 to $22 for most roles.
That said, after a while, one can be surprisingly fast when picking --- on one occasion I walked up to a bin full of non-descript cardboard boxes, grabbed one, spun it in my hands for the six-sided box check and scanned it to verify it was the correct pick, and then was asked to explain how I had gotten that right by a trainer w/ a bunch of trainees--- it seemed like almost five minutes of explanation of minor differences in cardboard texture, box shape, construction and so forth to explain how it was that at first glance, that was the only correct choice.
I've always wondered if LLMs would arrive at a similar conclusion with on-going training as they are used.