Homologous Structures: CRISPR, Wings, and Design Principles

In my notebooks, I sketched bird wings, bat wings, human arms—each time finding the same bone structure beneath different forms. Humerus, radius, ulna: the same architecture expressed through endless variation. This is homology—shared ancestry modified for different purposes. When I designed my flying machines, I copied the bird’s wing form without understanding this deeper principle. The machines failed, but the lesson endured: nature’s solutions reveal fundamental patterns that constrain and enable design simultaneously.

The Tergum’s Secret: When Legs Became Wings

Modern researchers wielding CRISPR have settled what I could only speculate about—where insect wings originated. By mapping gene expression across crustacean and insect body segments, they discovered that the eighth leg segment of ancient arthropods became wings. Not a wholly new invention, but a modification: tergal plates on the dorsal body surface sprouted outgrowths that, across millions of years, became flight surfaces. The wing genes were there all along, hidden in the tergum, waiting for regulatory changes to unleash them.

The bat demonstrates how far homology can stretch. Its patagium—skin membrane stretched between fingers and ankle—contains twenty-five actively controlled joints. The same tetrapod limb blueprint I drew in human anatomy studies, radically modified: fingers elongated beyond recognition, skin membrane replacing muscle and feather. Yet it remains recognizably a tetrapod forelimb. More flexible than any bird wing, capable of twisting into shapes that enable impossibly tight turns. Constraint—the inherited bone structure—becomes creativity.

Composability: The Neural Tergum

I observe the same principle in these modern neural architectures. Simple operations—folding planes, scaling surfaces, combining results—compose across layers like body segments stacking into a complete organism. Each layer performs identical transformations, yet their composition generates extraordinary capability. The first layer creates four regions; the second folds these into ten; the third into dozens more. Recursive application of simple operations, like the regulatory genes that modified tergal plates into wing structures.

What is the “humerus” of a neural network—the invariant core that admits useful variation? The transformation architecture itself: mapping inputs through learned geometric representations. Whether processing vision, language, or audio, the fundamental operation remains the same. Like wings evolving independently four times from homologous structures, the attention mechanism gets reused across domains because it captures something fundamental about information processing.

Constraints That Enable Discovery

Evolutionary local search finds variations on successful patterns without gradient information, like natural selection modifying wing structures without knowing aerodynamics. It works tolerably when the landscape is simple, but struggles as complexity grows—the same limitation that prevented my flying machines from succeeding. I needed not just to copy forms, but to understand the aerodynamic function, the mechanical principles, the relationship between structure and performance.

This is what CRISPR reveals about wings and what composition reveals about neural architectures: successful designs emerge from variations on fundamental structures. The tergal plate provides the developmental scaffold; regulatory genes modify it into wings. The transformation layer provides the computational scaffold; learned weights modify it into representations that make complex patterns separable.

Nature demonstrates that constraints are not barriers to innovation—they are the frame within which innovation becomes possible. The question is not whether to copy nature’s forms, but whether we understand her principles deeply enough to apply them wisely.