A Machine for Hypotheses : which Judges from Experience

Hypothesis [formation] and [determination of falsifiability], followed by [evidenced non-falsification of a falsifiable hypothesis], are all language constructs, which all of science depends on. If nothing else, this part of linguistics and the philosophy of language is what science students should be fully oriented with.

A [falsifiable hypothesis] is [a set of predicates, with a missing object]. If the object is found, the hypothesis is falsified. This part is fairly straightforward. ( But a miraculous leap of logic must occur at the point at which all language does not support itself : once the object is found, the linguistic construct about the object must be updated to reflect this. In other words, it is a non-trivial phenomena in language use that we say, "there is a red apple on that table", based on what we see in the world. )

This leads us to notions about the [picture theory of language], and [its tribe, the correspondence theories of truth]. The readings about this sort of thing are fun and wholesome reflections for children and adults of all ages, but they do not concern a machinist. A machinist only needs to know, how to [implement the tribe in a machine]. And this is where computer programmers start to get excited, because it turns out this part is fairly easy.

The machinist only needs to hook up certain inputs, from [imaginary ( software ) worlds], or from [hardware sensors], which modify data within a target buffer, which we can call an "experiential buffer". Then, the machinist only needs to specific what values of the experiential buffer need to exist, which would then force data in what we might call a "judgment buffer" to evaluate to some state. The type and state of judgment may be arbitrarily complex, but where [the simplest example of a judgment buffer is a single datum, whose type is boolean/2-ary-logic, and whose value has only two possible states]. This, being the reified concrete definition of a machine which forms judgments according to experience : any other source code leading to this, ultimately refers to this.

Having to read philosophy today, specifically metaphysics, because [ontological debates] collide with [models of mind] : philosophers like to argue about how ... [our language, and the world, and our recognition of the world] interact.

The reason I didn't specialise in academic philosophy as an undergraduate was, because I find much of this verbiage too unauthoritative to even be worth commenting on. Generally my interest is in machining, to provide [reified models and counter/examples of my understanding of the world].

Revision : 

- WAP/SAP vs TI : the [weak and strong anthropic principles] are related to [transcendental idealism] ( Kant's version - anything beyond that is woowoo ) : they are the somewhat [tautologous observations] that [anything we observe about the universe] is inextricably linked to [our cognitive apparatus] (TI), which relates furthermore to [the fact that our apparatus exists at all] (WAP) and that [the laws of physics actually support any of this] (SAP). These are compatibilist paradigms which try to unify 'realism' ( the notion that things exist outside our cognition of those things ) and 'idealism' ( the notion that things do not exist outside our cognition of those things ).

- Generally, what I like about the mechanistic approach, i.e. software engineering, is that we can play with [the cognitive apparatus under construction] to understand how it works. Whether the machine mind is exactly like the human mind or not, is besides the point.