[marcus_holmes]

But that's the point - we don't build robots that can do a wide range of tasks with ease. We build robots that can do single tasks super-efficiently.

I don't see that changing. Even the industrial arm robots that are adaptable to a range of tasks have to be configured to the task they are to do, because it's more efficient that way.

A car-welding robot is never going to be able to mow the lawn. It just doesn't make financial sense to do that. You could, possibly, have a singe robot chassis that can then be adapted to weld cars, mow the lawn, or do the laundry, I guess that makes sense. But not as a single configuration that could do all of those things. Why would you?

[Jensson]

> But that's the point - we don't build robots that can do a wide range of tasks with ease. We build robots that can do single tasks super-efficiently.

Because we don't have AGI yet. When AGI is here those robots will be priority number one, people already are building humanoid robots but without intelligence to move it there isn't much advantage.

[marcus_holmes]

quoting the ggggp of this comment:

> I think this whole “AGI” thing is so badly defined that we may as well say we already have it. It already passes the Turing test and does well on tons of subjects.

The premise of the argument we're disputing is that waiting for AGI isn't necessary and we could run humanoid robots with LLMs to do... stuff.

[EGreg]

I meant deep neural networks with transformer architecture, and self-attention so they can be trained using GPUs. Doesn't have to be specifically "large language" models necessarily, if that's your hangup.