The article title makes an unqualified claim about realisation, and so it was what I responded to, but the article itself also makes the same strong claim:
> A closer look reveals that although development of artificial intelligence for specific purposes (ANI) has been impressive, we have not come much closer to developing artificial general intelligence (AGI). The article further argues that this is in principle impossible, and it revives Hubert Dreyfus’ argument that computers are not in the world.
This is not an argument about cost - the article argues that it is "in principle impossible".
Any argument about cost I think is also irrelevant: We know from the existence of the brain and how a brain is produced that it is possible to produce one relatively cheaply via biological processes.
It seems highly unlikely that our ability to produce an artificial brain will not eventually approach the cost of growing one, because the "worst case" scenario is for us to find ethical ways of growing brain matter via biological processes and hook them up to computers, and it would seem unlikely that we will not eventually find cheaper ways of doing so than growing full mammalian bodies with it, and that we can not find any ways of optimising the process.
How the brain grows and develops in humans is not very well understood. We mostly use animal models to understand the nervous system, not humans. As an example of why this is problematic: mouse embryos pretty much turn inside out at day 3, and are the only known mammal to do this. All others, including humans, don't. Why and how are unknown, as are the effects on long term development. Basically, mice are better subjects than zebrafish, but not very good being humans.
The limiting factor is not budget or time, but 'stomach'. How elastic are your ethics?
It's not very well understood, but the process is known to exist and work. To assume it can't even in principle be replicated would be an extraordinary claim. Yet the article suggests artificial intelligence can not exist even in principle.
I mean, from a biochem perspective, it's flabbergasting that intelligence exists at all. The brain is so noisy.
To me, it's not far fetched to say that you can't make it happen again. Though I think it's technically possible.
We're missing something big with intelligence. We know neurons and synapses a little bit. We know a few dozen neurons a little, though it's complexity is crazy big.
But that gap between a normal brain down to a few dozen neurons is just boggling right now. There are just so many questions that need to be studied ethically.
It may not be possible to answer them all in a reasonable time window.
We know it happens again millions of times a year just for human brains. As such the complexity of the brain is irrelevant - what is relevant is the complexity and reliability of the machinery that constructs it.
We know the volume of the machinery that constructs it, which allows us to compute an upper bound on the informational complexity of a system capable of constructing human brains.
To me it is totally unreasonable to suggest we will never be able to at the bare minimum mimic that process and grow whole brains.
To me most of the opposition to the idea of artificial intelligence seems to come down to people assuming we're bound to only try to do this with software on a digital computer. But if that proves fruitless, there's no reason to assume we won't try analog systems, or if all else fails try biochemical systems, all the way down to genetic manipulation and tricking cells into growing into brains for us to hook up to computers.
Counter perspective: The process by which the brain produces intelligence might not be complex at all. Maybe it is just a simple algorithm which, when applied en masse, produces it. See for example the neocortex is made up of billions of cortical columns which are all basically the same architecture.
A few generations of biologists have tried to reason it out. I think it's safe to say that whatever is going on is either very complex or we just do not have the right tool to study it right now.
Something really new, like radios were to communication, or steel hulls to shipping, is needed in bio to get things moving apace. The tools we have are really great, but they are a bit slow it seems.
Also, the neocortex is somewhat stereotypical, but those long range projections that come in/out at every layer are the things that make the brain so hard to understand. Everything is flying everywhere all at once.
Oh yes! Developmental biology is just bonkers tough.
Take all the hard parts of bio normally, and now add in a ton of mitosis, long range movement of cells, hard to detect chemical gradients, cell-to-cell junctions, and pure random chance. All just going bananas fast for 'normal' bio processes.
It is a crazy tough field to get work done in. No wonder no one uses mammals to do anything.
> A closer look reveals that although development of artificial intelligence for specific purposes (ANI) has been impressive, we have not come much closer to developing artificial general intelligence (AGI). The article further argues that this is in principle impossible, and it revives Hubert Dreyfus’ argument that computers are not in the world.
This is not an argument about cost - the article argues that it is "in principle impossible".
Any argument about cost I think is also irrelevant: We know from the existence of the brain and how a brain is produced that it is possible to produce one relatively cheaply via biological processes.
It seems highly unlikely that our ability to produce an artificial brain will not eventually approach the cost of growing one, because the "worst case" scenario is for us to find ethical ways of growing brain matter via biological processes and hook them up to computers, and it would seem unlikely that we will not eventually find cheaper ways of doing so than growing full mammalian bodies with it, and that we can not find any ways of optimising the process.