A general-purpose robotic handyman for consumers is many many decades away (at least). And if such a thing did exist it would have massive massive implications for the labor market--both on its own and because of the implications for all the other things that AI could do were such a robot possible.

Computer vision in a very constrained environment is much much different and often isn't even suitable for many "simple" tasks that aren't constrained quite enough.

What if there was some sort of LLM like breakthrough? I could see someone doing a technique where they track all movements of a person going throug their day with a fine grained bodysuit. They could then use that as tokens for generative input that could give a humanoid robot intuition about how to move around and perform tasks that would match an LLM's ability to respond to arbitrary questions.

You'd walk face first right into Moravec's Paradox [1] which observes that higher order intelligence is far easier than basic locomotion & cognition. Probably because the former has only been evolving for millions of years in humans while the latter has been evolving in all animals for hundreds of millions of years.

We can't produce an electromechanical device that is capable of the kind of fine motor control 99% of animals are capable of, let alone doing it on an industrial scale. We're not even at the "promising proof of concept" stage and what use is more advanced software when we're not even close with the hardware.

[1] https://en.wikipedia.org/wiki/Moravec%27s_paradox

I suspect this is related to a serious upcoming bottleneck in AI. A skilled human can do all manner of physical handyman-style tasks, and I can imagine AI tackling a lot of the cognitive parts: reading the manual, figuring out what generally needs to be done, reading industry standards, etc. But a human has also trained themselves about how a screwdriver and a saw actually behave, how to get all the pieces to stay together while doing a job, and a bunch of other physical things work, and can real the manual, etc with this context. AI doesn’t have access to the physical part, at least for the time being.

This runs right into a lot of cognitive science research and debates. Which have not really resolved a lot of things related to AI historically and have been pretty much on the sidelines as GPU-driven machine learning has done some impressive things (and a lot of parlor tricks).

One of the ideas around cognition is that a lot of what we regard as intelligence in the physical domain, including intelligence below human levels, involves creating physical models about how the world works, which AIs are literally not able to do at all. You can instruct them in various ways, e.g. Boston Dynamics, but they have no way to internalize and actually understand novel physical world situations.

Some very smart people suspect that ML is a very powerful technique but that "better ML" only gets you so far.