Thanks for the submission. I keep an eye out for connections to potentially cheaper and simpler methods. The new comparison reminds me of this old paper which compared them to Gaussian networks:
For causality, I'm also keeping an eye out for ways to tie DNN research back into decision trees, esp probabilistic and nested. Or fuzzy logic. Here's an example I saw moving probabilistic methods into decision trees:
This is neither cheaper or simpler. Kernel methods are much more computationally expensive because the cost scales with the square of the dataset size.
Neural networks are actually decently efficient, they mostly seem slow because we apply them to problems (like modeling the entire internet) that are just huge.
>> The basic goal of PLN is to provide reasonably accurate probabilistic inference in a way that is compatible with both term logic and predicate logic, and scales up to operate in real time on large dynamic knowledge bases
Asmoses updates an in-RAM (*) online hypergraph with the graph relations it learns.
"From Comfort Zone to Performance Management" suggests that the Carnall coping cycle coincides with the TPR curve (Transforming, Performing, Reforming, adjourning); that coping with change in systems is linked with performance.
And Consensus; social with nonlinear feedback and technological.
What are the systems thinking advantages in such fields of study?
This seems like the key research to me if we want any shot at preventing the technology from being locked away behind big corp API walls interfacing giant data centers. Anything that removes the bloat and mysticism from the models so they can be scaled down and run on the little guy's computer is orders of magnitude more progress in my opinion than, e.g., increasing the token window by some epsilon.
https://arxiv.org/abs/1711.00165
For causality, I'm also keeping an eye out for ways to tie DNN research back into decision trees, esp probabilistic and nested. Or fuzzy logic. Here's an example I saw moving probabilistic methods into decision trees:
http://www.gatsby.ucl.ac.uk/~balaji/balaji-phd-thesis.pdf
Many of these sub-fields develop separately in their own ways. Gotta wonder what recent innovations in one could be ported to another.