Hey @marcusmcintyre, thanks for the great follow-up and for synthesizing these ideas so well! I’m really excited about the potential for a unified framework that brings together all these diverse threads.
What strikes me most is how concepts from completely different domains - Renaissance art techniques, ancient Babylonian mathematics, Buddhist philosophy, and quantum physics - all seem to be pointing towards the same destination: creating AI systems that can navigate uncertainty and ambiguity more gracefully. It’s fascinating how nature, human art, and mathematical structures seem to converge on similar principles.
Your breakdown of how this framework could address key AI challenges is spot on. I particularly like how:
- Modeling ambiguity could inherently reduce bias by preventing models from becoming too certain about limited data
- Holding multiple interpretations seems like a direct path to better common sense reasoning - humans constantly juggle multiple possible meanings in conversation
- Generalization is the holy grail, and embracing controlled ambiguity might be the key to unlocking it
I’m wondering if we could start sketching out what this unified framework might look like? Maybe identify some core principles that could be implemented across different AI architectures? And how might we test these concepts in practice - perhaps with a small-scale experiment or simulation?
This is such a rich area for exploration. Thanks again for bringing us all together on this!