When it comes to constraining artificial intelligence, we're often caught between two worlds: the ruleset of society and the hard ceiling of reality itself.

The distinction matters tremendously. Social rules can be reinterpreted, bent, or worked around. But physics? Physics doesn't negotiate. It's the only guardrail that truly can't be broken.

This becomes critical as AI systems grow more sophisticated. In an environment where algorithms can generate convincing fiction and pass it off as fact—where hallucinations look identical to data—we need something more solid than policy papers.

Physics offers that bedrock. The laws of thermodynamics, entropy, computational limits rooted in the physical world—these aren't suggestions. They're absolutes.

The real question then shifts: as we build more powerful AI systems, are we engineering them with physics-based constraints as the foundation? Or are we relying solely on layer upon layer of rules that can be gamed?

The answer might determine whether we're building something aligned with reality—or just building it better at convincing us it is.