I think you missed the main point, replicated economically. Given unlimited budget, I think simulating the human brain might be possible if one could use a powerful enough computer for evey neuron.
> 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.
The limiting factor is not budget or time, but 'stomach'. How elastic are your ethics?
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.
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.
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.
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.
If I were a betting person, I would wager that the connectome is enough to get something like intelligence, but that without the biochemistry the entire system is unstable in some way. The chemistry that we see in the brain is far more complicated than what would be required to minimally sustain the cells. There's a reason all of this chemistry is going on, and unfortunately I think we're going to find that intelligence just cannot exist as we know it without the chemistry. If that's true, then we're talking hundreds of years before we have computers powerful enough to model the chemistry at the requisite level.
The "learning" problem is solved. We've developed numerous algorithms to take a neural network and have it learn a task. We've solved specific problems, including image recognition, and text synthesis. Companies have figured out how to make sensory equipment including cameras, microphones, touch sensors...
Just because no one has managed to put together all the pieces doesn't mean it will never happen. People for thousands of years did not think it was possible to build a flying machine, until someone did.