Cognitive Silicon: An Architectural Blueprint for Post-Industrial Computing Systems

TL;DR

This work argues that deterministic, human-authored computing is inadequate for managing autonomous, context-sensitive AI. It proposes Cognitive Silicon, a 2035 full-stack architectural blueprint integrating symbolic scaffolding, governed memory, and alignment-aware execution, underpinned by the Free Energy Principle to formalize how cognitive systems maintain identity across physical and computational boundaries. The paper details six architectural imperatives—symbolic scaffolding, formal intent interfaces, expressive hardware substrates, alignment compilation, agentic runtime governance, and intent stewardship—and outlines a concrete 2035 stack with state-aware execution, layered symbolic-parametric models, mortality-aware hardware, versioned semantic memory, and constitutionally governed runtimes. It further engages deep philosophical frontiers (computability, governance, embodiment, and metaphysics) and discusses the social-ecological implications and necessary future work to realize trustworthy cognitive systems. Overall, it frames a radical, interdisciplinary direction that seeks to preserve human alignment through architectural constraints and embodied cognition, rather than relying solely on post-hoc safety techniques.

Abstract

Autonomous AI systems reveal foundational limitations in deterministic, human-authored computing architectures. This paper presents Cognitive Silicon: a hypothetical full-stack architectural framework projected toward 2035, exploring a possible trajectory for cognitive computing system design. The proposed architecture would integrate symbolic scaffolding, governed memory, runtime moral coherence, and alignment-aware execution across silicon-to-semantics layers. Our design grammar has emerged from dialectical co-design with LLMs under asymmetric epistemic conditions--creating structured friction to expose blind spots and trade-offs. The envisioned framework would establish mortality as a natural consequence of physical constraints, non-copyable tacit knowledge, and non-cloneable identity keys as cognitive-embodiment primitives. Core tensions (trust/agency, scaffolding/emergence, execution/governance) would function as central architectural pressures rather than edge cases. The architecture theoretically converges with the Free Energy Principle, potentially offering a formal account of how cognitive systems could maintain identity through prediction error minimization across physical and computational boundaries. The resulting framework aims to deliver a morally tractable cognitive infrastructure that could maintain human-alignment through irreversible hardware constraints and identity-bound epistemic mechanisms resistant to replication or subversion.

Figures (1)

• Figure 1: Meta-dialectical methodology sequence. For the details of this process, see Appendix A.