Lots of theoretical models, philosophical, and metaphysical thinking... The scientific method... Actual in-depth studies centered on the system you're trying to understand and duplicate in another form. You know.. Everything but the foolishness employers and VC firms look for in people.
How all the greats did it :
> Einstein
> Von Neumann
> Alan Turing
> etc
If you have a proven coding background, you're off and running in the production lab. The problem with the layers of hype, academic jargon, overly complex white-papers, and hand waving is that it makes people believe this is unapproachable outside the narrow scope of thinking that everyone is currently subscribed to. Scopes change with time and the people who tend to progress and widen these scopes are often those who think outside the narrow box everyone else is set upon. This is what Jobs meant by 'think different'.
Or you can attempt to brute force it with statistical models, PHDs, computing power, and truckloads of data hoping something miraculously emerges.
So, what type of thinking is used to develop strong A.I?
Strong thinking... Something that most and the industry aren't set upon which is why it most always takes an outside to usher in such new paradigms.
As is the history of the Googles of the world ...
Which is why I say you are more likely to hear about strong A.I once someone has developed it in the dark. It isn't going to be a 'thing' until it is a thing for people don't know how to recognize, value, or back undefined things until someone goes out of their way to make it into a reality.
Isn't deep learning the correct approach though? I mean we are trying to emulate biological neural networks which is fundamental to intelligence. Do you think that the artificial neural networks we are using right now are not rigorous enough?
> No. It's a piece of a much larger puzzle and only a partial piece at that. An overfit piece that people are over-applying. This is why things are overly complex and filled with statistics...
I mean we are trying to emulate biological neural networks which is fundamental to intelligence.
> There is far more functional complexity to the underlying biology. This is why studying neurobiology/neuroscience have value as opposed to resorting to ever more complex statistical models that no one understands.
Do you think that the artificial neural networks we are using right now are not rigorous enough?
> Of course not. Out of all the amazing people centered on it, no one can say why/how it works. Is it magic? lol... That should tell you something and trigger a red flag. I can state why it works and already have. It's just not something that's convenient and would necessarily cause one to admit that its not the broad general answer were looking for....
So, for some time, those centered on this paradigm are probably going to build out wildly elaborate NNs. They will require boat loads of data and computational power and achieve great outputs. Coincidentally this fits nicely in the cloud computing model that the big tech titans maintain.
Somewhere down the line, more solid and thought through computational models inspired by actual understanding will come out that will shake the very foundation of said approaches and so will go another page in tech history.
NNs are biological inspired. With all of the fanfare surrounding them, You maybe never stopped to question how inspired.
Drop Paul King/Paul Bush a line a Quora or dig through some of their posts.
It's better to talk w/ a Neuroscientist/Computational Neuroscientist about this stuff IMO.
How all the greats did it : > Einstein > Von Neumann > Alan Turing > etc
If you have a proven coding background, you're off and running in the production lab. The problem with the layers of hype, academic jargon, overly complex white-papers, and hand waving is that it makes people believe this is unapproachable outside the narrow scope of thinking that everyone is currently subscribed to. Scopes change with time and the people who tend to progress and widen these scopes are often those who think outside the narrow box everyone else is set upon. This is what Jobs meant by 'think different'.
to the history of new approaches... i.e : https://en.wikipedia.org/wiki/Feynman_diagram
Or you can attempt to brute force it with statistical models, PHDs, computing power, and truckloads of data hoping something miraculously emerges.
So, what type of thinking is used to develop strong A.I? Strong thinking... Something that most and the industry aren't set upon which is why it most always takes an outside to usher in such new paradigms.
As is the history of the Googles of the world ...
Which is why I say you are more likely to hear about strong A.I once someone has developed it in the dark. It isn't going to be a 'thing' until it is a thing for people don't know how to recognize, value, or back undefined things until someone goes out of their way to make it into a reality.