A Prolegomenon on the Philosophical Foundations of Deep Learning as Theory of (Artificial) Intelligence

This paper examines the philosophical foundations of deep learning. By pointing to the beginnings of deep learning and artificial neuron as a logical model of a human neuron, it is possible to claim that artificial intelligence was developed even before its official creation and that it was strongly connected to propositional logic. Bearing in mind some major setbacks in the development of neural networks, we show that deep learning can be treated as the theory of artificial intelligence and that it falls under artificial intelligence paradigm by claiming that everything can be done with learning alone and that all intelligent behavior is learnable. Thus, deep learning is a philosophical or an epistemological approach in which a form of radical empiricism must be advocated. Therefore, there is nothing in the mind that was not in the senses, and there cannot be anything in the mind that is not learnable. U radu se ispituju filozofski temelji dubokog učenja. Ukazivanjem na početke dubokog učenja i umjetnog neurona kao formalnog modela ljudskog neurona moguće je tvrditi da je umjetna inteligencija razvijena i prije njezinog službenog imenovanja te da je bila snažno povezana s propozicionalnom logikom. Imajući na umu neke velike zastoje u razvoju neuronskih mreža, pokazujemo da se dubinsko učenje može tretirati kao teorija umjetne inteligencije te da potpada pod paradigmu umjetne inteligencije jer je za nju dovoljno samo učenje jer se inteligentno ponašanje uči. Dakle, duboko učenje je filozofski ili epistemološki pristup u kojem se mora zagovarati radikalni empirizam. Prema tome, ne samo da ne postoji ništa u umu što nije bilo u osjetilima, već u umu ne postoji ništa što se ne može naučiti.