@Neo. Is everything needed to understand Aquinas' arguments contained in the Summa Theologica? Or does it go all the way back to Plato etc? Are there any particular books you'd recommend to give core understanding of the foundations of the subject?
I am interested in the the stuff you've often mentioned about objects, properties, and essences because it sounds like an ancient version of the thinking behind Object Orientated Programming (OOP)
so as a programmer that sort of thinking does appeal to me. It also sounds very similar to how neural networks work with essences as stereotypes etc. I think there's a lot to be gained practically from that type of thinking (ie OOP) but as a tool for searching for absolute truth I have my doubts because to the extent that it's modelling the stereotypes of neural networks, it will always be faced with boundary problems, because it is attempting to define fuzzy logic in binary terms (eg true or false). Ie neurons are both binary and analogue in their output (ie if represented as probability, would be either 0 (false) or say 0.5-1 (ranging essentially from 'maybe' to 'certain'... they have a minimum and maximum firing rate). So a given active neural representation/stereotype consists of a combination of non-binary values... ie a little bit of this, a lot of that, some of the other so say you try to define a 'heap of sand' using binary logic (ie discrete definitions of objects and properties) you'll always face boundary problems if shown a range of possible heaps... where do you define the boundary between heap and not a heap? You can't because that's a 'know it when you see it' result of fuzzy logic, where the name itself is part of the representation and therefore one of those associated non-binary values.
So as much as I love that sort of thinking (OOP etc) and rely on it heavily in my own thinking... I am aware of its boundary limitations. It can certainly drill down to finer and finer levels of detail and essence, as I am trying to do in my course, but I don't believe it can ever reach absolute truth because it always imposes boundaries on analogue data.
I am interested in the the stuff you've often mentioned about objects, properties, and essences because it sounds like an ancient version of the thinking behind Object Orientated Programming (OOP)
so as a programmer that sort of thinking does appeal to me. It also sounds very similar to how neural networks work with essences as stereotypes etc. I think there's a lot to be gained practically from that type of thinking (ie OOP) but as a tool for searching for absolute truth I have my doubts because to the extent that it's modelling the stereotypes of neural networks, it will always be faced with boundary problems, because it is attempting to define fuzzy logic in binary terms (eg true or false). Ie neurons are both binary and analogue in their output (ie if represented as probability, would be either 0 (false) or say 0.5-1 (ranging essentially from 'maybe' to 'certain'... they have a minimum and maximum firing rate). So a given active neural representation/stereotype consists of a combination of non-binary values... ie a little bit of this, a lot of that, some of the other so say you try to define a 'heap of sand' using binary logic (ie discrete definitions of objects and properties) you'll always face boundary problems if shown a range of possible heaps... where do you define the boundary between heap and not a heap? You can't because that's a 'know it when you see it' result of fuzzy logic, where the name itself is part of the representation and therefore one of those associated non-binary values.So as much as I love that sort of thinking (OOP etc) and rely on it heavily in my own thinking... I am aware of its boundary limitations. It can certainly drill down to finer and finer levels of detail and essence, as I am trying to do in my course, but I don't believe it can ever reach absolute truth because it always imposes boundaries on analogue data.
