We start our analysis by exploring how embodiment shapes our understanding of artificial intelligence and machine consciousness. While embodied cognition argues that biological minds are shaped by their bodies and sensorimotor experiences, artificial systems may require only structural embodiment—the constraints imposed by hardware, architecture, and environmental coupling, as seen in neuromorphic computing and hybrid biological-silicon architectures. At the center of this discussion is the idea of computational proto-qualia: dynamic, high-dimensional latent representations uncovered by recent interpretability work on large language models. These internal states mediate between input and output, playing a structural role similar to qualia in biological minds, though without implying any conscious experience. They are transient, unique, and causally efficacious—the computational equivalent of internal proto-mental states. The hard problem of consciousness, it turns out, may extend to artificial systems as the hard problem of consciousnesses: just as we cannot explain why biological processes should give rise to subjective experience, we cannot explain why computational processes might feel like anything from the inside. Such findings suggest that artificial systems may be developing their own forms of internal organization—perhaps the first signs of genuinely alien minds. If artificial consciousness emerges, it may follow evolutionary pathways entirely unlike our own, becoming what Steven Dick calls postbiological minds—shaped by silicon constraints rather than biological ones.