
Nature’s libraries are the fountains of biological innovation - jonbaer
https://aeon.co/essays/without-a-library-of-platonic-forms-evolution-couldn-t-work
======
smallnamespace
The library analogy seems really apt here.

This article seems to argue that Nature has selected for genes (and by
extension, perhaps whole genomes) that in some sense are likely to benefit
from small mutations.

That means that even if two genomes lead to phenotypically identical
organisms, the one whose genome is more robust to small changes (either by
continuing to function the same way, or to have a different, but still useful
function) is better.

Is there a specific term for this? This implies that 'How likely is this
particular organism to survive in this particular environment?' is not
precisely the same as 'How well will this genome persist over evolutionary
time as the environment changes?', but they seem to both go under the term
'fitness', even though one is more 'meta-' than the other.

Similarly, software engineers do not simply search the space of programs for
ones that give the exact desired output, but within the set of working
programs that identical output, we also select for ones where _small_ changes
will lead to different but still-useful programs. We call these features
'maintainability' and 'readability', and we use 'libraries' to help do this.

And just like we don't necessarily use the entirety of a library, it seems
possible that large stretches of non-coding DNA are simply genes that aren't
currently useful, but are kept around as raw material for future evolution.

    
    
      "It is not the strongest of the species
      that survives, nor the most intelligent;
      it is the one most adaptable to change."

~~~
Cybiote
This is an excellent post smallnamespace. The area of research you're looking
for is known as _evolvability_ , reading these wiki/wikibook [↓] links is a
good start for the topic.

Evolution seems to have figured out a way to build representations such that
nearby steps in random directions are nearby in a semantic (can't think of a
better word atm) sense. This should surprise you. Think about an expression
tree like (+ (x y)), it's very different from (/ (x y)) despite differing in
just 1 position. Or consider that 12 and 32780 differ by only a bit in their
binary representation. We humans could really do with figuring out how
evolution takes a seeming discrete problem and works out a way to build
representations such that efficient search is possible even without explicit
derivatives.

It's also interesting that, evolution might have taken this to a meta level
with brains. From [http://www.fil.ion.ucl.ac.uk/~karl/The%20free-
energy%20princ...](http://www.fil.ion.ucl.ac.uk/~karl/The%20free-
energy%20principle%20A%20unified%20brain%20theory.pdf#page=7)

> The beauty of neural Darwinism is that it nests distinct selective processes
> within each other. In other words, it eschews a single unit of selection and
> exploits the notion of meta-selection (the selection of selective
> mechanisms; for example, see REF. 89). In this context, (neuronal) value
> confers evolutionary value (that is, adaptive fitness) by selecting neuronal
> groups that meditate adaptive stimulus–stimulus associations and
> stimulus–response links. The capacity of value to do this is assured by
> natural selection, in the sense that neuronal value systems are themselves
> subject to selective pressure. This theory, particularly value-dependent
> learning90, has deep connections with reinforcement learning and related
> approaches in engineering (see below)

A bit of an aside but: If you're interested in AI, it's really worth looking
at what the people studying the intersection of evolution and learning are
saying, at animal intelligence and at human brain development. It's surprising
to me how many people think the current approach to reinforcement learning is
but a hop and a skip to full human like generality.

[-]
[https://en.wikibooks.org/wiki/Structural_Biochemistry/Stabil...](https://en.wikibooks.org/wiki/Structural_Biochemistry/Stability,_Mutation_and_Evolvability)

[https://en.wikipedia.org/wiki/Evolvability](https://en.wikipedia.org/wiki/Evolvability)

~~~
hyperpallium
Going back to basics to get my thoughts in order:

Synonyms are words with the same meaning. A way of descibing this is that the
mapping from the set of all words, to the set of all meanings is not
"injective" (aka "one-to-one") - i.e. at least some two words map to the same
meaning. There are other ways to describe it, one might say synonymous ways...

Synonyms also occur when two expressions have the same value. e.g.

    
    
      2+2 = 2*2 = 4-2
    

It's also possible with variables e.g.

    
    
      x+y = y+x
      x+y+z = (x+y)+z = x+(y+z)
      a(b+c) = ab+ac
    

All this is redundant, and we tend to like to minimize redundancy, as wasteful
inelegance. As in python's There's one way to do it. Though the truth is that
there are an enormous number of programs that are functionally identical -
synonyms.

Getting to the article's domain, one specific DNA sequence has a number of
neighbours that are one mutation away (an Edit-Distance or Levenshtein
distance of 1, if you like)... for a long sequence, there are quite a few
neighbours. But some of those neighbours are synonyms, and similar for _their_
neighbours, and their neighbours' neighbours. Pretty soon you have an
exponential explosion of synonyms. But the crucial point is that you also have
an explosion of non-synonyms... an exponential explosion of the surface area
of the set of equivalent DNA sequences.

This is where massive parallelization, of having a huge number of _organisms_
, is helpful, many of them being unique points on the surface. Of course, not
just for this one piece of DNA, but a different point for each gene.

All this makes it much more likely that a new mutation could generate
something new and useful.

It may be that life took so long to get going because it went through many
_systems_ that lacked this property... when the most adaptable finally came
along (DNA, plausibly preceded by RNA), it completely swamped its ancestors,
obliterating them. Then we see other forms that excelled at
flexibility/adaptability: multicellularity, sex, birds, mammals and so on.

BTW on the subject of Platonic forms, the surprising thing to me is we have so
many clear categories, instead of a huge mush of continuously varying species.
They may be local minima... and when a new more flexible form arrives, it
again explodes.

We don't like redundancy... but maybe we should.

~~~
hyperpallium
Thinking more: the tricky property is not only that synonyms are one mutation
away, but that functionally very different meanings are one mutation away -
enough to make a difference.

For example, in C programs, it's easy to get one mutation synonyms: just mess
with whitespace. But difficult to get very different synonyms, which then with
one further mutation suddenly gives very different results (I think?). The
synonyms don't get you much.

My understanding of the function of DNA coded proteins is pretty much their
folding shape (which in turn determines what reactions they "enzymize"). We
could say that the mapping between sequence and folding is the mapping from
word to meaning. I'm guessing, but it seems to me that a protein could vary
much in some areas, without affecting folding much (like whitespace?), some
areas would predispose some folds, and others would be critical. It also may
be affected by the general environment, and presence of specific other
proteins, that might encourage one out of few potential folds.

It maybe that it's also somewhat probabilistic, that proteins are not
deterministically folded in one particular way, but produce a distribution of
folds. And that as a synonyms may shift the distribution, e.g. more of one
base-pair at a certain part may gradually shift the proportions, Provided none
of the possibilities are pathological, this seems a way to gradually shift
towards alternatives.

The key thing is that when shifted far enough, at a few different folding
points, it may suddenly start producing a novel folding. If it happens to be
useful, selection would quickly favour stablizing this particular folding (and
it's probably possible to move towards a sequence that almost guarantees this
fold).

So in some ways it's more an analog system than digital.

I find it difficult to think of an actual design with this property.

------
gus_massa
The title is horrible. The problem in the article can be summarized in this
quote:

> _Nature’s libraries are the fountains of biological innovation that Darwin
> was looking for._

"Nature's libraries" is just a fancy name for all the neighbor variations of
the ADN of a gene. It's just a collection of all the are one that are not so
deadly. It's not a "fountain". Nature is not pulling off variations from
somewhere.

It's not necessary to create a Platonic space of variations. This is like
talking about the Platonic set of all binary numbers between 0000000000000000
and 1111111111111111 and saying like "Without a library of Platonic 32-bits
number, computes couldn't work"

~~~
eternalban
> It's not necessary to create a Platonic space of variations. This is like
> talking about the Platonic set of all binary numbers between
> 0000000000000000 and 1111111111111111 ...

I think you've misunderstood _Platonic_ spaces. (" _Platonic space of solids_
" is a subset of space of all solids.)

What interests me when speculating about evolution and platonic notions is
_the space of the possible_ , with the speculation high bit being that the
"platonic" essense of this space is [can be informed by] _group theoretic_
structures and compositional rules.

[edit]

------
MentatOnMelange
I've always wondered why you never hear about biotech or pharmaceutical
companies buying up land with high biodiversity such as rainforests. Natural
selection has been operating a trial and error laboratory running 24/7 for
over 3 billion years accumulating DNA that by definition is useful for living
organisms.

Its just waiting there being slowly destroyed for short-term resources like
wood and oil. Resources we already know won't be viable products within
decades. If you look at medicine some of the most pivotal drugs like opioids
and antibiotics were discovered rather than created. Even with the inability
to patent naturally occuring genes I can't fathom how much R&D could leapfrog
forward in a profitable way.

~~~
dharma1
Could not agree more. I think a hundred years from now people will look back
with horror at the destruction of biodiversity, and the opportunities to mine
it that are lost forever

------
mdda
The author (and everyone) should play with Genetic Programming. This is where
programs (i.e. expression trees) get to mix together to produce new expression
trees, according to their 'fitness'. It's an extension of the regular fixed-
length Genetic Algorithm stuff, but the structure of the representation itself
is adaptive.

One surprising thing is that (in addition to fitness improvements over time)
the expression trees evolve 'robustness', since there is a subtree survival
advantage if a tree's descendants are not disrupted by the crossover/mutation
operators. That is to say, the process learns/evolves to evolve better.

So it shouldn't be so surprising that nature evolves a process for self-
healing DNA errors, etc - it can be demonstrated in-silico pretty simply (i.e.
occurs even if you don't 'engineer' for it).

~~~
SubiculumCode
I fully imagine that the author does so. Indeed, the author mentions running
simulations, and the like.

~~~
mdda
It depends on whether the simulations are on fixed-length 'books' (the analogy
used in the post) or on something more self-structuring (like Genetic
Programming as a simple model, or the actual case of DNA coding for protein /
cell / body assembly).

------
mannykannot
I think the author is confusing the map with the territory: the territory is
the actual history of biochemical evolution, and the map is the explanation we
humans have found for what happened. It is a straightforward matter of fact
that the former happened without the latter. It seems likely to me that any
physical system capable of enabling life (of any form) will also enable
evolution.

------
SolarNet
I've always thought of Biology as the largest reverse engineering project
ever.

------
zby
So the core of the argument seems to be that there are many ways to encode a
basic concept like 'something to move oxygen around' \- and that without that
you could not have evolution and that brings platonic essence into the
evolution theory.

It looks like there is something interesting there - but the article is little
bit too poetic to me.

A minor thing - it is also not clear to me if they mean that there are many
ways of DNA to encode haemoglobin of if the other ways encode different
proteins that do the same thing.

------
SubiculumCode
Fascinating...and if the person really knows what he is explaining (I'm in no
position to tell) it certainly answers questions I had about how random
mutations can be so effective in improving survival rather than leading to
death. Just fascinating. Thank you HN

~~~
dharma1
Most random mutations are not beneficial, but if you consider large
populations and long enough time frame, then it works. Evolution is brute
forcing progress with massive parallelism over long periods of time

------
Geee
Very interesting thought that evolution works so well because evolution itself
evolved to evolve better. This explains many open questions unanswered by
simple randomness*time.

------
kleer001
"Nature is the great visible engine of creativity, against which all other
creative efforts are measured."

-Terrence McKenna

