The economic value in automating high skill and expensive labour that the most profitable corporations rely on is what attracts the most investment and effort.

Once you lose your job you'll find plenty of time to do all those menial tasks you hate wasting time on.

Jokes aside, programming and mathematics are just well ordered environments. Already digital and verifiable. Perfect for a GPU cluster to power through. The real world is big slow and complex in comparison.

The bottleneck is not really the intelligence here.

We can build robots that do the things you want. Arrange a visit to Amazon's robot warehouse tour.

We can't ship them because they break all the time with current technology. It would be a tough sell to have to being in a 100kg robot for servicing every few weeks.

This was cars in the first several decades of automobiles. The tide shifted as soon as you could just drive the car to a neighborhood dealership for servicing. It's fun to imagine the logistics of that for robots but the material science and engineering has to advance a bit.

I've learned that I spend significantly less time folding laundry than many of the people commenting about modern ai powered robotics. It's not meant literally is it? For instance keeping floors and counter-tops clean seems a much bigger time sink for me.

It's because existing models are a brute-force approach to intelligence. With enough data and compute, a stochastic parrot will become very impressive.

But with robotics, there's no pre-made dataset that can be parroted. Notice that these datasets, e.g. how to fold clothes, need to be created by humans. That's as if humans needed to write algorithms like quicksort to teach LLMs how to code.

future is on the way, three to four generation ( one each year ?) will unfold this, primarily quantum computer improving material and battery, humanoids becomes standardised and modular enough to be easily replaceable ( think ibm pc ) ( most components are simple injection moulded advance plastics , mass produced in some corner of china, self detection of wear and tear and self replace that part ), other is optical computers ( 100x lower power x 100x speed = local inference ), problem is, when this will become reality, who will benefits more ? who will hold moat ?

f folding clothes, i wanna just have a robot be my personal chef. the amount of different tasks and capabilities a robot will need to make any meal that I can in my kitchen is huge and i feel like it’s still a while from being solved.

Unless we spend a bunch of money generating data, I can't imagine the machine steps to fold laundry are very big in the general training sets. Someone is going to have to find a hardware system, cheap enough to make it economically feasible then train it. As far as tasks people will pay a lot of money for a robot, this seems low on the list.

Pretty soon. Sunday Robotics had a 3 hour stream of folding clothes with 99% accuracy. You can watch it for yourself. There’s a lot of “hand” companies with very compelling videos just over the last two months. Then there was Figure’s multi day livestream of package manipulation that was very impressive. Physical LLMs are definitely coming. Given enough training data we know LLMs can output coherent data in any space, it’s just a matter of time.

The problem is we're orders of magnitudes better at manipulating bits at scale than we are at manipulating atoms.

I'm not holding my breath for advanced robots in the home within the next ten years.

But, then again, I didn't see LLMs coming either.