i_love_limes
5 hours ago
I think people in HN (and in general) have to remember the central axes of evolution before digesting this kind of article. I've already seen comments like it's "odd that no species has ended up evolving a continuous maintenance system" and "sleep has a higher opportunity cost in humans" in this comments section.
This is a common, but poor framing of evolution. Remember: the only real rule with evolution is "did this evolutionary change mean they survived / reproduced more"? Evolution is not a local or global maxima solving function. I find this kind of attempt at interpreting selection common with engineers, programmers, etc.
hackernud3s
5 hours ago
Did their genes survive more, you mean. Hyper-vigilance could be maladaptive for the individual and still survive if it benefits others that carry the gene for it.
vintermann
4 hours ago
A bit of a digression, but I recently learned about the concept of pangenomes, of trying to map not just the genes in one individual, but the entire set of genes from a clade. It seems it matters a lot in practice for e.g. the immune system that we don't all have the same surface proteins on our cells, even if done some surface proteins are clearly better than others.
Kim_Bruning
an hour ago
> "did this evolutionary change mean they survived / reproduced more"
You're just renaming the terms. More/less is a fitness gradient, and the thing that lives there is called an optimizer.
Evolution is a tunable-scale optimizer. It's not perfectly local, because it shotguns to avoid local optima on a (bumpy/noisy) fitness landscape. If you tune the 'shot pattern' really wide (infinite copies with infinite variation), you'd genuinely get a one-shot global optimizer at the limit. But that's not efficient nor realistic, so typically it's somewhere in between.
Uh, compare maze solvers: you've got your greedy direct route (gets stuck in the first corner) , Dijkstra (finds all the answers but takes ages), and then stuff like A*, which is a happy medium. Evolutionary algos can be used to solve mazes just the same. I think it's a bit heavier on resources than A*, but well suited to embarrassingly parallel optimization.
edit: Heh, I actually had claude build a comparative simulation. Turns out evolution is actually very slow on a single optimization axis, and gets stumped in mazes where the detour length is greater than the "temperature"/"spread"/"noise". The actual performance metrics are fascinating. But once tuned, it is able to solve mazes. Thus an optimizer. QED :-P
yuretz
5 hours ago
I can see why it isn't a local or global maxima solving function, but it surely can be modelled by one, right?
teekert
5 hours ago
I'm a biologist so forgive me the poor wording, but there are "infinitely high" peaks/walls in the evolutionary landscape, as in: "the human urinary system has some evolutionary constraints and anatomical features that are not optimally designed from an engineering perspective, but they are generally functional and reflect our evolutionary history rather than deliberate design." <- this is from AI, I didn't remember the details, but the ureters or urethra take a long way around the inner part of the body because at some point it was a good route, but as we evolved it became suboptimal, but we can't just evolve to untangle all the pipes in our body and do some cable management... We're stuck with what we have (no tunneling electrons ;)).
So in that sense, a global maxima (minima?) solving function will probably not arrive at what we have, it has to take into account our evolutionary path, in its entirety (as in the whole tree.), because it is all encoded in 1 (or several) long molecules, and a radical changes would take a rewrite of many parts at the same time, which just does not happen. Maybe at some point we can do it ourselves... though I imagine there being a lot of unintended consequences in other places in the body :).
Another example is that sometimes complexity in a cell signalling cascade is simply there to get some timing right (ie delay some response), and the complexity is just there, and won't simplify by itself -> But then later the complexity may start to serve some purpose. Just like proteins that are "copypasta-ed" in the genome, leaving one copy free to mutate and attain a function, or not... etc etc.
dtech
5 hours ago
That is the difference between global and local optima. We're not at a local optimum though, our bodies can probably evolve to produce half the urine or something without changing the route, but there is no evolutionary pressure to do so.
teekert
5 hours ago
Yes, but we cannot evolve to have our urinary tracts take a more efficient route (or at least the probability is exceedingly low), even though there would be pressure to do so. (Maybe I'm misunderstanding your point)
xtiansimon
3 hours ago
“recurrent laryngeal nerve” as well
https://futurism.com/evolutianary-proof-the-recurrent-laryng...
albert_e
4 hours ago
Interesting
I did not know human urinary tract was suboptimal.
Are there examples of "discontinuous" evolution where a chance mutation stumbled upon a much better way to do something that allowed a species to jump the gap?
I imagine it would be very rare because chance mutations in a single individual that confer extraordinary survival / mating advantage to offset entire population would be rare like being a superman among men.
teekert
4 hours ago
"I imagine it would be very rare because chance mutations in a single individual that confer extraordinary survival / mating advantage to offset entire population would be rare like being a superman among men."
-> This also depends on population size, if there is a bottleneck event (ie 99.99 percent of some species dying) then among the 100's of survivors perhaps there could be a superman. Either because this person got lucky, or the rest got unlucky. But in general the distribution of traits is quite continuous, given large populations.
It's also good to keep in mind that us biologists have messy definitions, ie we call specimen A and B the same species when they produce fertile offspring. Some species produce offspring but infertile (Horse-Donkey, Lion-Tiger). But what if A and B have fertile offspring and B and C do, but A and C do not? The whole definition of species falls apart (it leads to a paradox).
We have a lot of that in biology. You need to learn to deal with it (sunglasses dropping down), and assign uncertainties to terms you learn about, they are often just our attempts to name boxes on continuous, multidimensional scales.
PetitPrince
2 hours ago
Antibiotic resistance happens all the time (at least in our artificial world) and it's a life or death situation for the bacteria.
But you were probably asking for multicellular eukaryote organism; you may be interested in the concept of saltation https://en.wikipedia.org/wiki/Saltation_(biology) . Behind the concept of the thing itself it's interesting to think about the mechanism behind it. Regular evolution is gradual (point mutation leads to a maybe slightly different protein, which has only a relatively small scale effect but you gain or lose function over many generation), but for a saltatory evolution you most probably need radical changes in the DNA, like duplication (of a single gene, multiple gene or whole chromosome), horizontal exchanges, etc.
It's possible in plant but in animal more often than not it's not beneficial at all to have such event. Famously if you have an extra chromosome nr. 21 you get Down syndrome.
teekert
4 hours ago
Well, what is suboptimal... One would engineer it differently, it makes a weird, seemingly unnecessary, loop around some other tracts. However, being a biologist I can also imagine that if we'd reroute the thing in someone using surgery, that person suddenly gets more infections because bacteria find their way up the tract more easily (no idea, but could be!). The point is... It's a mess based on some earlier mess, but it works, and changing one part in this mess can lead to unpredictable results.
As for "discontinuous evolution"... Again, what is discontinuous? I'm sure there are events to be found of which the probability of them occurring is so small and the effects so large that they'd fall into someone's definition of "discontinuous". But I think there is by definition no such thing as discontinuous evolution. If it occurred, it had a non-0 probability of occurring, then again, maybe the universe is infinite and everything has a non-zero probability of occurring. This is getting philosophical haha. Maybe listen to some Mindscape podcasts (Sean Caroll).
Actually rabbits eat their excrement again. That's also probably not how an engineer would make it (or an intelligent designer would design it, since we seems to be going in that direction ;) ).
yeoyeo42
2 hours ago
no offense, but it just sounds like you don't understand local maxima in high dimensional spaces.
a suboptimal trait evolving that still provided an overall population benefit (via survival or reproduction) with further improvement close to impossible without a multitude of large changes is literally just a local maximum in that high dimensional space that maps traits to whatever success metric you're measuring.
the infinite wall you describe is not a wall in that space. actually I originally wrote its more like a wall in the derivative space but its not quite right either, those just point straight down from the maximum.
teekert
2 hours ago
Perhaps not no, please enlighten me, where is my lack of insight?
Edit, thanx for the addition. Perhaps my issues with looking at it as "local maxima in high dimensional spaces" (even though we think of minima usually, as in a marble will find the minimum in a landscape with gravity pointing down, sorry I'm a biologist) is that with every mutation and every change in environment the landscape changes (so basically with time), is it still a useful way to think about it like that, at that point? So it not a "landscape in a high dimensional space", but rather a "high dimensional dynamic surface", like a sea?
i_love_limes
4 hours ago
Great question! It maybe can be, but what is the maxima that is being solved for exactly? There are usually tradeoffs, the most common and prevalent is our body's immune response. If it's under-active, we might die from an infection. If it's over-active, we get diabetes, lupus, chron's, and (probably) lots of mental health disorders.
So, it's a bit context dependent, and definitely dependent on other mutations that have occurred in other parts of your DNA. Most complex diseases are "polygenic", meaning it's a culmination of quite a few factors that would contribute to a specific good or bad outcome.
So, yes, it could be modeled as a sort very context dependent with a lot of highly correlated non-independent covariates. We do use quite a lot of statistical and ML methods to understand the genome (I work in statistical genetics), but the complexity of biology has so far proved a tough nut to crack.
codethief
3 hours ago
> It maybe can be, but what is the maxima that is being solved for exactly?
Survival rate/reproduction rate/rate of genes being spread?
PetitPrince
2 hours ago
I think you're correct, but only if you add "for a given environment". It's good to develop the ability to store super efficiently fat when you're a Pacific Islander and food is scarce, but this advantageous trait becomes a liability with modern and plentiful (junk) food.
see thrify gene hypothesis; I know it's not a good explanatory theory but it's a good illustration of my point
yuretz
4 hours ago
Great answer! Thank you!
dtech
5 hours ago
Evolution is the ultimate "good enough". Once the required threshold is passed, pressure stops. The threshold might constantly be moving due to competition, environment etc.
tempfile
2 hours ago
It can't be a global one because it is inherently local. Evolution is a process which determines the next time step (generation) from only the previous generation. It has no memory at all nor "knowledge" of other reproducing pairs.
FallCheeta7373
5 hours ago
To be precise inclusive genetic fitness not idealized bayesian optimality.