Introducing causality into the model could very well just be another layer. In fact it is quite clear that stable diffusion produces a super set that is slightl

Introducing causality into the model could very well just be another layer. In fact it is quite clear that stable diffusion produces a super set that is slightly bigger than solutions with causal reasoning taken into account. One more additional filter on top of that for causal deduction is a very realistic next step. In a nutshell stable diffusion is like a calculator that gives me 3 answers. One of those answers is right, the other 2 are wrong. The next step in calculator creation is putting a filter over the output to get the right answer from the 3 possibilities. >As I see it, we currently have good machine inductive learning, but are really far from any machine deductive learning. Yeah, we already covered 50% of the AI equation in the past decade. The other deductive part is actively being researched and a revolution in your lifetime is HIGHLY probable given how fast the inductive part came to fruition.