> For AGI, do you really think there are detailed proposals out there today that can achieve AGI but are only missing the computational power?
Yes, I really do. It's neural networks, nothing more. All that is required is more power. Despite its lower power the brain is much more computationally powerful than even the largest supercomputers.
Although it is not necessary, imo, to have a much more efficient computing substrate to achieve GAI, there is work in this direction. Look into optical reservoir computing. Or more generally thermodynamic computing. https://arxiv.org/abs/1911.01968
Machine learning is progressing rapidly mostly because the computational power is increasing rapidly. Read this for an understanding of how important computational power is to progress in machine learning: http://www.incompleteideas.net/IncIdeas/BitterLesson.html
Time and time again computational power trumps complicated technique. It is fairly obvious to many now, after the continued scaling of the GPT-x series models, that genuine intelligence is an emergent property of the kind of systems we are building. It is an emergent property of systems that are driven to predict their environment - no more secret sauce to discover.
I think a major objection people have to the idea that machines are already a little intelligent is that they cannot understand how intelligence can emerge from pure computation. They imagine that there must be some magic between the operation of neurons in their mind and their experience of the world. Qualia where does it come from, how can it be just neurons, just inanimate physical matter? Combine this philosophical objection with the emotional response to the threatening nature of AGI and you have a milieu that refuses to see what is directly in front of its nose.
There are plenty of philosophical positions that allow you to understand how consciousness might emerge naturally from computation. Consciousness is emergent... Panspermia, consciousness is found in everything. To imagine consciousness in the movement of 1s and 0s within a machine is not too hard, to see the consciousness inside the "chinese room" is not really so difficult.
But none of this is relevant to the original argument I was making which is: trying to tell the future is very hard. Because it is simply a fact that before most great breakthroughs there is a common opinion that such a thing is, if not impossible, then in some distant future.
I think there are very very good reasons to think that a general intelligence of genuine utility is not more than 10 years away. I think people will look back at GPT-3 as the first proto form of the general intelligences that will exist in the future.