True and false are referents referring to the ontic realm, so the other referrals I mention in "About mixorders" must refer to truth and false referents. In this way, the other contributors will be able to be identified by artificial intelligence. In my opinion, when we are going to recognize the other references by artificial intelligence, we will be able to create a self-educated computer.
maybe the use of fuzzy logic to support more values, or the Bayesian network to exploit the probabilistic method
the new generation of AI are based on machine learning and deep learning
I mean, if the computer had filled in the algorithms for the referrals I mentioned, it would have been a bit like a human. He would not have been aware but thanks to pragmatism, he could know how to change the algorithm for a pedestrian crossing if it caused an accident. And while doing probability calculations, he could predict the occurrence of an accident by collecting data from the surroundings of the vehicle.
self-educated human ? yes of course, human have teleology and meta-knowledge that enables them to think and search ... Computer machines are artificial without objectif and finality and are a simple executor of basic calculus principles given by humans. In specific meaning they can learn about engineering skills .. not more
What mean learning ? Use, memory, experience, reasoning, conclude, learning, observe, argue. In my opinion computer with this predicates is imposiible.
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