Just because it looks simple, does not necessarily mean its not complex
- Kris van Beever
- Dec 2, 2025
- 1 min read
People often assume that if something appears simple at its core, it must be simple in practice. But simplicity at the foundation does not eliminate complexity at the surface.
Every digital system we use—storage, computing, networking, communication—ultimately reduces to the most basic binary symbols: 1 and 0. The entire modern world is constructed on that foundation. Yet the meaning, usefulness, and intelligence of these systems come from the layers of interpretation built on top of those binary signals.
We’ve been here before. Early long-distance communication relied on a similar idea through Morse code. The signals themselves were simple; the challenge was in understanding and interpreting them. Only trained operators could translate those dots and dashes into meaning.
Today, the translation layers have grown more sophisticated. Machines now interpret billions of ones and zeroes per second, rendering them into the applications, insights, communications, and AI systems we engage with directly. The foundation hasn’t changed—only our ability to assign meaning to it.
And that is the real point: complexity lives in the semantics. It lives in how we interpret information, what we infer from it, and how we turn it into action.
As AI becomes more capable, our technical problem is no longer producing the signals. It is understanding the meaning behind them, validating the outputs, and ensuring that interpretation aligns with human intention.
The core remains simple. The semantics define everything.
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