A comprehensive understanding of universal computational capacity is essential, particularly when distinguishing it from its various physical manifestations. The intrinsic potential for true computational universality is not inherently bound to specific physical forms, such as the binary logic gates prevalent in digital electronics or the decimal arithmetic systems commonly used by humans. Instead, this fundamental computational capability can theoretically emerge within a wide array of physical substrates, constrained only by a system's capacity to sustain the necessary information processing dynamics requisite for computation. Furthermore, the analytical utility of rigidly separating conceptual domains like 'logic' and 'ontology' faces significant challenges when analyzing complex systems. Such divisions often exhibit ambiguous conceptual boundaries and frequently serve more as convenient linguistic constructs or products of particular philosophical stances than as robust frameworks for deep systemic comprehension. When investigating intricate systems, revisiting foundational insights, notably Gödel's incompleteness theorems, provides crucial perspective. These theorems, by demonstrating inherent limitations within any sufficiently powerful formal system, offer insights potentially applicable beyond abstract mathematics to any domain displaying analogous formal or systemic organization, including complex biological or cognitive architectures. Viewing consciousness through this lens of inherent systemic constraints and emergent complexity suggests it need not be conceptualized as an anomalous or fundamentally distinct phenomenon requiring non-mechanistic explanations. Instead, it can be understood mechanistically as a highly complex, emergent biological feedback mechanism intricately linked with evolutionary pressures. Its primary adaptive function appears centered on maintaining organismic integrity and optimizing survival, largely by facilitating predictive capabilities and the avoidance of existential threats through sophisticated environmental interaction and internal state regulation. Framing consciousness as fundamentally separate from other biological or physical mechanisms risks defaulting to non-mechanistic or theological interpretations, thereby impeding the pursuit of a functional, empirically grounded understanding based on observable processes. It is equally vital to accurately contextualize historical computational paradigms within their original technological and conceptual frameworks. Alan Turing's seminal theoretical contributions, for example, were explicitly formulated within the operational paradigms of classical mechanical computation prevalent during his era. Crucially, there exists no evidence suggesting his theoretical framework specifically anticipated or incorporated quantum processes, which constitute a fundamental departure from the deterministic, classical computational models he envisioned, operating under vastly different physical principles. Like all models, the work of Turing and Claude Shannon were also constrained by their own understanding of paradigms of computing and so we should be careful to understand what they were trying to do, which was essentially to take analog information and digitize it to make it simpler. What we're trying to do today is exactly the opposite. We're trying to overcome the limitations of binary circuits of electrons, moving along semiconductors through logic gates and look at how the universe works in shades of gray and so essentially their work was unnecessary but insufficient precursor to understanding what Computing should mean in the future.