In quantum systems, symmetry emerges from asymmetry. The transitioning logic
from one such a quantum state to another remains at the forefront of physics.
The thermodynamical approach is also aligned to this way of reasoning about AGI.
perhaps, we need to continuously be asking ourselves: "What
Addendum: another candidate for this variational model for finding
distributions to replace back-prop (and consequently with the
potential to capture predictive structure which is chaotic attractors.
Though they don't appreciate the need yet.) There's Extropic, which is
proposing using heat noise.
Let's give the symbolists their due:
https://youtu.be/JoFW2uSd3Uo?list=PLMrJAkhIeNNQ0BaKuBKY43k4xMo6NSbBa
The problem isn't that symbolists have nothing to offer, it's just that
they're offering it at the wrong level of abstraction.
Even in the extreme case of LLM's having "proven" that
The problem with AGI is Wolpert's law. A can predict B or B can
predict A but not both. When we try to understand our own brains,
that's the special case of A = B. You can't. It is the same with AGI.
If you want to create an agent smarter than you, it can predict you
but you can't predict it.
