The critique that Transformers are limited by their "one-shot" feed-forward nature also misses the point of their architectural efficiency. Human brains rely on recurrence and internal feedback loops largely as a workaround for our embarrassingly small working memory—we can barely juggle ten concepts at once without a pen and paper. AI doesn't need to mimic our slow, vibrating neural signals when its global attention can process a massive, parallelized workspace in a single pass. This "all-at-once" calculation of relationships is fundamentally more powerful than the biological need to loop signals until they stabilize into a "thought."
Furthermore, the obsession with "fragility"—where a model solves quantum mechanics but fails a child’s riddle—is a red herring. Humans aren't nearly as "general" as we tell ourselves; we are also pattern-matchers prone to optical illusions and simple logic traps, regardless of our IQ. Demanding that AI replicate the specific evolutionary path of a human child is a form of biological narcissism. If a machine can out-calculate us across a hundred variables where we can only handle five, its "non-human" way of knowing is a feature, not a bug. Functional replacement has never required biological mimicry; the jet engine didn't need to flap its wings to redefine flight.