This post analogizes between a specific theory of human intelligence and a badly caricatured theory of evolution. It feels like better versions of the arguments for Darwin Machines exist that would not: a) require an unsupportable neuron-centric view of evolution, and b) don't view evolution through the programmers lens.

> Essentially, biology uses evolution because it is the best way to solve the problem of prediction (survival/reproduction) in a complex world.

1. This is anthropocentric in a way that meaningfully distorts the conclusion. The vast majority of life on earth, whether you count by raw number, number of species, weight, etc. do not have neurons. These organisms are of course, microbes (viruses and prokaryotes) and plants. Bacteria and viruses do not 'predict' in the way this post speaks of. Survival strategies that bacteria use (that we know about and understand) are hedging-based. For example, some portion of a population will stochastically switch certain survival genes on (e.g. sporulation, certain efflux pumps = antibiotic resistance genes) that have a cost benefit ratio that changes depending on the condition. This could be construed as a prediction in some sense: the genome that has enough plasticity to allow certain changes like this will, on average, produce copies in a large enough population that enable survival through a tremendous range of conditions. But that's a very different type of prediction than what the rest of the post talks about. In short, prediction is something neurons are good at, but it's not clear it's a 'favored' outcome in our biosphere.

> It relies on the same insight that produced biology: That evolution is the best algorithm for predicting valid "solutions" within a near infinite problem space.

2. This gets the teleology reversed. Biology doesn't use anything, it's not trying to solve anything, and evolution isn't an algorithm because it doesn't have an end goal or a teleology (and it's not predicting anything). Evolution is what you observe over time in a population of organisms that reproduce without perfect fidelity copy mechanisms. All we need say is that things that reproduce are more likely to be observed. We don't have to anthropomorphize the evolutionary process to get an explanation of the distribution of reproducing entities that we observe or the fact that they solve challenges to reproduction.

> Many people believe that, in biology, point mutations lead to the change necessary to drive novelty in evolution. This is rarely the case. Point mutations are usually disastrous and every organism I know of does everything in its power to minimize them. Think, for every one beneficial point mutation, there are thousands that don't have any effect, and hundreds that cause something awful like cancer. If you're building a skyscraper, having one in a hundred bricks be laid with some variation is not a good thing. Instead Biology relies on recombination. Swap one beneficial trait for another and there's a much smaller chance you'll end up with something harmful and a much higher chance you'll end up with something useful. Recombination is the key to the creativity of evolution, and Darwin Machines harness it.

3. An anthropocentric reading of evidence that distorts the conclusion. The fidelity (number of errors per cycle per base pair) of the polymerases varies by maybe 8 orders of magnitude across the tree of life. For a review, see figure 3 in ref [1]. I don't know about Darwin Machines, but the view that 'recombination' is the key to evolution is a conclusion you would draw if you examined only a part of the tree of life. We can quibble about viruses being alive or not, but they are certainly the most abundant reproducing thing on earth by orders of magnitude. Recombination doesn't seem as important for adaptation in them as it does in organisms with chromosomes.

4. There are arguments that seem interesting (and maybe not incompatible with some version of the post) that life should be abundant because it actually helps dissipate energy gradients. See the Quanta article on this [0].

[0] https://www.quantamagazine.org/a-new-thermodynamics-theory-o...
[1] Sniegowski, P. D., Gerrish, P. J., Johnson, T., & Shaver, A. (2000). The evolution of mutation rates: separating causes from consequences. BioEssays, 22(12), 1057–1066. doi:10.1002/1521-1878(200012)22:12<1057::aid-bies3>3.0.co;2-w