@masterofthetiger not an expert on any of this but.. the mutations that don't work are a cause of loss for many single-cell species. Some species have mechanisms that proof read DNA during copies to reduce this loss. Dividing less is another strategy.
Multicellular beings have to deal with potential cancer, but it also helps that the egg cell after conception might not be viable in the first place. (one egg cell lost wasn't an enormous investment)
@masterofthetiger in the longer run, sexual selection has the advantage that a good mutation can end up in the entire population instead of being stuck on one branch. Similarly, "breakage" doesn't have to be selected out in one generation.
Bacteria and stuff can share genes sometimes too.
Virus species("not life" but it evolves) would die off they did not adapt to our immunity. But they produce millions(?) or viral particles each cell. If of them 90% don't work, it may still be viable.
🇳🇱
What interesting about this is I work rather heavily in research around what we call "biologically inspired machine learning". We basically take apart the brain and the natural mechanisms that make evolution work, reverse engineer to figure out how it works and why, then apply those mechanisms to computer algorithms to improve on our own machine learning and evolutionary algorithms.
So not only is evolution real, but it is extremely powerful and something we replicate (or at least try to replicate) in computing with some level of success.
@masterofthetiger@theres.life
