[obrien1984ae]

A better analogy for DNA in computer science would be LLMs. Each organism's DNA represents an experiment being performed in service of training a model. If that experiment manages to procreate, its successful mutations graduate into another round of experiments.

This has gone on for several billion years, resulting in a largely stable model within which experiment are continuing to be run.

As with LLMs, DNA doesn't know anything about the data it is being trained on ("Nature"). And that model continues to change even as the experiments are run.

So DNA is a "blockchain" record of previous and current hypotheses on which traits enable an organism to live to viability. Some of these hypotheses are "dead code," as the environment no longer contains the pressure which made them critical. Some of them are essential to viability. Some of them are experiments whose value has not yet been determined.

Assuming your question is whether IaC could learn from patterns in DNA, I think that's a very interesting idea. Certainly we desire that every loadbalancer, database, and iam policy be capable of self-defense, and be the hardiest, most fit version of itself possible.

Where the analogy struggles is that people writing IaC are more in the business of designing "natures" than they are designing individual organisms which would survive a chaotic and hostile "nature" being enforced on them. And people who write IaC might be unhappy to hear that getting to a "viable" database would require launching several thousand databases in an environment and, after some period of changes, seeing which one is performing best so they can clone that "best" database configuration when new databases are needed.

[fl0ki]

I apologize in advance for criticism you only half deserve. I know this is HN, but not every single topic needs to be compared to LLMs or Blockchain. Concepts like fitness functions, selective pressures, feedback mechanisms, etc. -- as applied to both embodied organisms and constructs like cultures and ideologies -- predate not just the last two hype cycles but artificial computation altogether.

Referring to such deeply established foundation is normal -- I'm sure many of us remember when novel AI approaches like perceptrons and evolutionary algorithms were described by analogy to biology -- but skipping over the established literature to talk about nascent concepts makes you sound less like you're contributing to an educated discussion and more like you're courting angel investors with buzzwords.

At the very least it could be "here's the analogy to <established thing>, and to help round out the concept, <new thing> is also analogous to <established thing> with <important differences>". That makes both a stronger argument and a more educational essay than skipping straight to the new thing with no foundation.

For example, one very important difference is that DNA can be edited and lose history, unlike blockchain, but an intact fossil record could be used to infer how those edits came in over time and space, kind of like an incomplete distributed ledger.

[obrien1984ae]

> For example, one very important difference is that DNA can be edited and lose history, unlike blockchain, but an intact fossil record could be used to infer how those edits came in over time and space, kind of like an incomplete distributed ledger.

That is a very good point.

It is true that editing blockchain completely destroys the chain, and editing DNA in very specific ways does not. I was thinking (when I wrote it) that because of the way the genes interact it can be completely destructive to take only a single piece of DNA. But, as you correctly point out, we do that all the time. So, yes, the blockchain analogy only partially fits.

Thank you.