It sparked me into an old reflection that suddenly went deeper than previously.

After talking about a Feynman Experiment insight about the moment a wave of particle(s)) behaves like a solid atom when observed, and likening that event to an individual’s existence, the creator of the video asked: “if we all exist because of being observed, then who is observing us?

Here follows the caption of my “stitch” in reply: each one of us is a particle of the entire particle system that makes up “ God/Source/The Universe/All That Is/*insert preferred name here* “ in the process of perceiving itself through each of us perceiving each other.

When we observe one another very objectively, and objectifyingly, we are in essence “collapsing the wave function” and individualizing that which we observe, as well as ourselves through the act of judgement, as when we judge we are in the act of “checking back” with any concept that oneself has rationalized or internalized as an ideal (idea as an object to the mind’s eye). And so, at the moment of judging someone, we are individualizing and losing “sight” (losing empathic perception, and not attentive, pointed observation ).

As entangled particles of being one perceived singular particle of oneness, when we stop judging anyone - as well as therefore, oneself - and directly oneself, THAT is when the self, and the observed duality dissolves into an expansive and fully inclusive embodiment of oneness.

It makes me think of several field developments when it comes to careers, namely “AI Pedagogy”, but not as what I see in terms of a discourse that looks into how AI can help people learn, but the other way around. Perhaps this could then be termed “LLM Pedagogy”.

It is a very paradoxical experience as when I receive GPT replies about concepts and known, renowned theoretical frameworks, it responds with excellence. It gives the impression of having found* correlations on its own, however, when the subject matter and framework isn’t obvious or common, it not only encounters great difficulty but also hits up triggers.

Words that have very strong conceptual associations in theoretical discourses seem to trigger the GPT to completely forget my theoretical framework and its contents and it goes on spewing ideas centered in previous discourse by others. It makes assumptions, and at one point it even reprogrammed itself.

To remediate this issue, I am having to develop an entire system of teaching (training) that can facilitate its understanding.

A breakthrough of these recent days has been to use tech metaphors for my concepts and then explain them in this way. Once the GPT has come to a basic understanding, then I ask it to compose metaphor systems in microbiology, for example, and then others. For now, this pedagogical methodology seems to be working but only time - and the context window - will tell