Very slowly and not reliably.
> updating their own algorithms,
Slowly and not reliably.
> sharing their algorithms with other AGIs
Slowly.
> and learning new complex skills.
Very slowly, yes
> To add to that, they are energy efficient, you can keep one running for optimally for 5 to 50$/day depending on location, much less than your average server farm used to train a complex ML model.
To run a reasonably complex ML model does not require $1500/month.
And these AGIs require significant resources and space, much of which has to be provided by other AGIs.
> If we disagree on that assumption, than what's stopping the value of human mental labor from sky-rocketing if it's in such demand ? What's stopping hundreds of millions of people with perfectly average working brains from finding employment ?
They're slow and complex and expensive and training scales terribly. Training a model and running 1000 copies of it is not 1000 times as complex as training a model and running just one copy.