That's an argument about complexity. And "organic" simply means based on molecules with a carbon backbone. They're versastile, but that does not give them any known information processing advantage over silicon.
If analog processing were relevant (it most likely isn't) then Artifical Neural Networks could also be implemented on analog silicon circuits.
As for the complexity, well, the systems are getting more complex. Straight lines on log charts. That's what scaling is about. Getting there, to that complexity.
So I'm just not seeing any knockout argument from you. We can't predict the future with certainty. But the factors you present do not appear to be fundamental blockers on the possibility. You're pointing at the lack of an existence proof... which is always the case before a protoype.
It sounds like you're basically abandoning forward-thinking and will only acknowledge AGI when it hits you over the head. A sign of intelligence is also the ability to plan for an unseen future.
Can you clarify what you mean by "no information processing advantage?" Does increased speed or memory capacity provide such an advantage? Or would you also claim that 2024 silicon has no advantage over 1994 silicon despite several orders of magnitude more speed & memory?
Since we're looking towards the future and asking whether there is an advantage of the basic materials (organic vs. inoraganic) I'm talking about the physical limits of those substrates, whether there's anything special about them that allows one to process information in a way that the other can't. I.e. how many bits can be stored in a cubic centimeter of nano-structured silicon compared to a cube of carbon, oxygen, hydrogen and other organic chemistry arranged into (for example) neurons. How many TFlop/s can be fit into such a cube in principle etc. etc.
Or if there are some other physical processes relevant to information processing that make carbon special.
Those fundamental limits have not changed over time, the physics are the same. All that changes are how much use engineering makes of those possibilities.
If analog processing were relevant (it most likely isn't) then Artifical Neural Networks could also be implemented on analog silicon circuits.
As for the complexity, well, the systems are getting more complex. Straight lines on log charts. That's what scaling is about. Getting there, to that complexity.
So I'm just not seeing any knockout argument from you. We can't predict the future with certainty. But the factors you present do not appear to be fundamental blockers on the possibility. You're pointing at the lack of an existence proof... which is always the case before a protoype.
It sounds like you're basically abandoning forward-thinking and will only acknowledge AGI when it hits you over the head. A sign of intelligence is also the ability to plan for an unseen future.