No: people poking at the brain in research contain people who do lots
of experiments, and build concrete models, and attempt to test these models.
Sure, most of the models and experiments are junk: but they are putting their money where their mouth is.
Look up COGENT: an attempt to build software that aids humans in building cogitive models. These models are then tested against human behavior. Sure, it isn't "we have AI", but it is actually producing data. What is better is that it produces hypothesis which can be falsified.
That is just one branch of serious research into the field. Dozens if not 100s of approaches are being done to try to figure out how human intelligence works. The trick is to be serious about it, you have to produce experiments, publish your findings in a way that others can build on them, and test your predictions.
I don't see predictions when I'm reading your posts on the other website: I see musings at the level of philosophy/literature rather than at the level of science. Your posts using quotes from the Illiad does not bolster your position...
So some questions... Can you produce:
A post that demonstrates why you believe that "we have the computational power today"?
I can see an example where you spend 11 million dollars building a model where each dendrite has 64 bits of state, neurons are 10 to 100 times less connected than in the human brain, and you can model on the order of 0.001% of the neurons in the human brain. And this completely ignores the "what interconnects with what" problem!
A post that demonstrates why you think that a weak model of a neuron is good enough? Anything other than hopeful thinking?
In short: I don't see why you are worth paying serious attention to, when there are 100s or 1000s of PhD students, grad students, and researchers poking away at the problem, producing both reproducible and testable results, and building models that are grounded in tested reality rather than philosophy?
Sure, most of the models that the PhD students are working on won't work. That is expected
. When you are trying to worm your way into solving a new problem, you don't know
before hand which approach will work.
So you try multiple approaches. You study things from many many angles, and when one approach starts producing interesting results, you toss more resources at it.
The popularizers of science? They aren't the scientists. Ray is just an author -- he's a philosopher, not a scientist. He's an ad-man, not an engineer. He isn't important, other than possibly convincing people that "AI is neat, maybe I should research it or support those who do".
In short: start building models. If you aren't building models and testing things out, you are just philosophizing. And if you need 11 million dollars to test your hypothesis, then you had better get cracking and either making money (go go self-funded research!) or
gain credibility via simpler accomplishments (academic or otherwise) so others will donate.
There are paths you can follow if you are serious about wanting to do research and spend all of your time on it. Go apply for a PhD program.
Your job will be to work on producing original research. Find a supervisor that will take you on, and you'll even be paid a living wage while you are doing it usually. Then you become a post-doc in which you do even further research -- your job description is basically "produce papers and get them published", each one of which should contain as much testable, hard models as possible. All the while you will be kept in room & board by funding.
If you produce sufficient papers, you can try to become a professor -- the tenure track is all about producing papers, the other parts of the job are secondary. Every paper is another bit of research you have had to push out -- and you will be able to talk to other people whose job is also research, and they'll probably love to hear your ideas. You will attempt to get funding so you can hire peons to do the research work you want, and your peons will love to have your concrete, testable ideas in order so that they to can produce papers.
Ie: there is an existing
infrastructure so you can dedicate your life to this problem. It just requires that you produce testable, interesting results, write them up so that others can understand them.
And there are 1000s of people doing that right now in the AI field. Why not join them?