discursive thought is highly underrated
it’s one of the bedrocks of creativity
the key algorithm is what decides to “fund more scarce m.e.a.t resources” to continue disgressions into continuation from inference to inference
it’s poorly understood, and can be finetuned to be higher EV and understand when to continue vs. cutting off the compute loop
this can be understood well with agents as well
the ephemeral items is the sense of EV and the awareness of whether to continue “feeding the loop”
it’s a sad state of progess to not be able to discuss this at various levels of abstraction (m.e.a.t formation, m.e.a.t deployments in venture, scientific research, progress research into development, what some have termed meta-science)
another issue is that crossing inferences is too slow
people cannot read or go through 100+ inferences
there’s sometime embedded experiential knowledge at certain points of inferences
a clear litmus test is take a laymen (non-experts) and bridge multiple persons across the inferences
this takes work and is very much an empirical process
since it’s a skillset of communication and finding shorthand for each specific person based on their backgrounds and conceptual mapping
though it’s certainly possible
the professionalized ecosystem versions of these are VC-startup ecosystem and PHd-professor ecosystem
both are incentivized by their respective status symbols to orient people “learning” and crossing inferential bridges (for VCs power law MOIC outcomes and for professors tenure and published papers)
these more “concrete tangible examples” of discursive experiments
that happen as halting functions
with a “market eval” (either VC funding or professor time/attention and then peer review)
happen within one’s own mind for trails of thought/inferences as well
A Stream of Consciousness