Daniel Huddleston

The Discovery Story

The Universal Efficiency Law wasn't invented — it was observed. While building deterministic knowledge retrieval systems, a pattern kept emerging. Systems that performed well shared specific properties, and these properties related multiplicatively, not additively.

At first, this seemed like a quirk of the particular architecture. But the more systems I built and measured, the more consistent the pattern became. Different approaches, different implementations, same underlying relationship.

Then I started noticing the same pattern outside of software. In how I processedinformation. In how experts communicated differently than novices. In why some explanations clicked immediately while others required repeated exposure.

The formula E = k·S·D·Λ·C crystallized from these observations. It's not a theoretical construct imposed on reality — it's what the data kept showing.

Why Release It Openly?

Knowledge that stays locked away doesn't improve. The formula might be exactly right, approximately right, or wrong in interesting ways. The only way to find out is to expose it to verification across many domains, by many people.

If it's correct, it should be useful to everyone — researchers, engineers, educators, anyone working with information systems. Keeping it proprietary would limit its development and testing.

If it's wrong, I want to know. Science advances through falsification as much as confirmation.

Current Focus

I continue building systems that test and apply the efficiency law:

• ColdState: Deterministic knowledge retrieval demonstrating high-efficiency information architecture
• NEROS: Applied efficiency principles in neural-inspired systems
• This site: A live test case — the site itself demonstrates (or fails to demonstrate) the formula's predictions

Philosophy

I believe understanding should be efficient. Life is too short for low-S content, high-latency systems, and uncompressed explanations. The efficiency law isn't just a formula — it's a design principle.

Build things that respect people's cognitive resources. Communicate with highsemantic density. Reduce latency wherever possible. Compress without losing meaning.