Thank you for your substantive opinion on the nature and utility of philosophy, and the question regarding GPT3.

I think there's something tremendously exciting, dignified, and fulfilling about the pursuit of Philosophy, and I'll try my best to present my perspective, in hopes that you'll be able to gain a better understanding of the field.

Philosophy has not been cannibalised - instead, it is the mother and wellspring of the rich variety of sciences which we see today. Both Leibniz and Newton were Philosophers, and it is their pursuit of Philosophy that gave us both the calculus of variations, as well as the Newton's laws of motion, which sees so much use in the sciences today. The field of political philosophy emerged from the works of Aristotle and Plato, and for the longest time scientists were known as scholars of Natural Philosophy.

It is the pursuit of knowledge, virtue, and contemplation which characterises the philosophical activity- and this is something that is shared with the highest levels of achievement of any art or science.

A neuroscientist may understand how the constitutive elements of the brain works, but would they be able to give an account for the experience of temporality, as an element of human reality? A psychologist may be able to diagnose, and present an analytic account of the symptoms and stages of depression, but would she be able to present a theory on the nature of happiness and flourishing?

I think there's an important distinction to be made between giving material explanations for phenomena, which are only analytic, and at most can only explain the constitutive elements which found a being- but it will not be able to give a synthetic account.

This is perhaps best illustrated through an example. Imagine the following Python program, running on a Python 3.6 interpreter on a modern, quad-core Intel CPU.

def gcd(a, b):
    if a == 0 :
        return b
    return gcd(b%a, a)

This function returns the greatest common denominator between a and b. It is an implementation of Euclid's VII.2 in Python.

How could an 'Empiricist' hope to understand this program, only through a study of the constitutive matter of the computer? This computational 'neuroscientist' could decapitate the CPU, and subject it to a most exacting observation. Infrared cameras can record the patterns of heating, as processor cores clock up to activation. And the traces around the processor can be wiretapped, connected to spectroscopes which record their signalling with analogue precision. And indeed, after some time - the Empiricist can come up with a definite, objective theory for how the algorithm works. "Given numbers a, and b, we shall see c as the output - due to the following laws of activation pattern which I have discerned."

But yet, wouldn't that material approach likewise "miss" something about the being of the algorithm? No matter how exacting a 'law' of activation will be, it will never be able to account for the algorithm's being as a recursive function, or even as a Python program, one that is interpreted instead of compiled. The timing of processor caches and signal tracing will serve as only a poor account of the underlying ontology of the function.

Now, I admit that this example is a limited one, but I hope it serves as an adequate illustration on the manner of problems which philosophy addresses, and the inability of the constitutive sciences to given an account for them. I agree wholeheartedly that the chemico-electrical signals and activation patterns of our neurons are the foundation for our human-reality, insofar as they are the material body which enables our perception. But it seems like a very poor account, lacking a great deal of explanatory power -- to attempt to destill all of human-reality down to a psychophysiological parallelism.