Installing and unistalling on unix is unsafe for beginners.

Tread the terminal with caution.

I usually dont touch my core environment, but use virtual vms in case i wanna develop some stuff.

Not all AI is ML.

In closed systems, AI can emulate how the brain is forward-looking.

For example in a game like chess or go, there isnt data to be dissected, rather there is sheer force of compuation.

The monte carlo tree algorithim can simulate games based on the specific state of a board. Humans can do that however to a much lower degree and less deep.

I like how you think.

Though we are very far off from understanding consciousness.

I feel like what roger penrose is doing is more what you are describing.

Data science cares about output more than the science behind the humam brain. Though i think neural networks are very interesting.

Limited use in neural network applications at present due to many application's CUDA requirements (though the same could be said of AMD)

This is what i read from a newegg review.

Im interested in this.

Definitely not helpful advise. Anyway it feels like the question caters to fanboys of each enviroment.

Both pytorch and tensorflow are pretty good, though each has their own strengths.

Yeah i might be wrong based on the downvotes.

;)

Lol. Ofcourse.