I wanted to mention something cool I learnt the other day which is that buddhism actually was created with a lot of the cultural baggage already there. (This is a relevant point, let me cook)
The buddha actually only came up with the new invention of “Dependent Origination”. This lead to a view of the inherent emptiness (read underdeterminedness) of phenomenology. Yet it was only one invention on top of the rest that led to a view that in my opinion reduces a lot of suffering.
Similarly human evolution to where we are today is largely a process of cultural evolution as described in The Secret Of Our Success.
What I want to say is that ideas are built on other ideas and that Great Artists Steal. (Also a book)
Final statistic is that interdisciplinary researchers generally have more influential papers than specialised researchers.
So what is the take away for me? Well by sampling from independent sources of information you gain a lot more richness in your models. I therefore am trying to slap together dynamical systems, Active Inference and Boundaries at the moment as they seem to have a lot in common that seems relevant for embedded agents.
(Extra note is that GPT is actually really good at generating leads in between different areas of study. Especially biology + ML.)
Great post!
I wanted to mention something cool I learnt the other day which is that buddhism actually was created with a lot of the cultural baggage already there. (This is a relevant point, let me cook)
The buddha actually only came up with the new invention of “Dependent Origination”. This lead to a view of the inherent emptiness (read underdeterminedness) of phenomenology. Yet it was only one invention on top of the rest that led to a view that in my opinion reduces a lot of suffering.
Similarly human evolution to where we are today is largely a process of cultural evolution as described in The Secret Of Our Success.
What I want to say is that ideas are built on other ideas and that Great Artists Steal. (Also a book)
Final statistic is that interdisciplinary researchers generally have more influential papers than specialised researchers.
So what is the take away for me? Well by sampling from independent sources of information you gain a lot more richness in your models. I therefore am trying to slap together dynamical systems, Active Inference and Boundaries at the moment as they seem to have a lot in common that seems relevant for embedded agents.
(Extra note is that GPT is actually really good at generating leads in between different areas of study. Especially biology + ML.)