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Genetic algorithms

Without a doubt, natural selection works and a population's collective genetics change over time in response to the environment. Typical examples are finch beak sizes and colouring of moth wings. That's straight-forward to scientifically establish. According to evolution, the diversity of life we see today is entirely attributable to such small changes occurring over vast periods of time. That's harder to experimentally prove or disprove in the time available to us humans, given the duration of human lifetimes, and research grants.

It's one thing to 'tweak the parameters' of a design—neck length, muscle mass, etc, which you could imagine being fairly simple genetic modifications. If a giraffe were essentially a cow with an elongated neck, then that could be believable. However a giraffe's long neck presents some engineering difficulties, and a giraffe has solutions built into it that make it more specialised than just a stretched out cow.

To summarise: there are many examples of animals having specialised features that look like engineering solutions to engineering problems. The features are so specialised that it is seriously doubtful that they are possible by the gradual changes of evolution, and rather require an up-front design.

In software, genetic algorithms are very useful in a specific context, which is to find specific well-functioning parameters of a previously designed algorithm. E.g. you want to make a digital filter, so you use a genetic algorithm to find ideal filter parameters. You want a good radio antenna, so you use a genetic algorithm to tell you how many wires to use, and where to bend them. It works well and it's amazing to see what it can come up with. But the technique is limited to solving the task at hand, as defined by the human designers.

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