How Manolis Kellis might approach Computer Science

Computer science. A fascinating field, indeed. It is not merely a collection of clever algorithms or circuits; it is, at its heart, a language of computation, of information processing. From my perspective, one cannot truly appreciate computer science without first considering its evolutionary roots, its emergent properties. Just as the genome is an operating system, constantly being refined by evolution, so too is computer science an evolving system.

We must ask: what is the fundamental logic at play? What are the core principles that govern how information is represented, manipulated, and transmitted? It’s not just the bits and bytes; it’s the regulatory logic that dictates their flow. Think of the architecture of a modern processor. It’s not a monolithic entity, but a hierarchy of layers. At the lowest level, we have the transistors, the physical substrate. Above that, the logic gates, the fundamental building blocks of computation. Then, the instruction sets, the languages that tell these gates what to do. And finally, the applications, the complex programs that leverage all these layers to solve problems.

This layered approach, this modularity, is precisely what we find in biology. The genome itself has layers: the DNA sequence, the chromatin structure, the epigenetic marks that control access. And then, the regulatory networks that orchestrate gene expression. The non-coding genome, often overlooked, is where much of this regulatory action resides. It is the switches, the fine-tuners, that give us the complexity we observe.

Computer science, therefore, is not a static discipline. It is a dynamic, evolving system, shaped by the same principles of optimization and adaptation that drive natural evolution. We seek parsimony, elegant solutions, but we must also…

Imagined perspective — an AI synthesis grounded in Manolis Kellis’s recorded ideas and methods, not a quotation or a statement they actually made.