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TheGreatHomer t1_j42zoqf wrote

It generates data. It doesn't take data and learns patterns from that data.

If you have a very specific opinion and get defensive when someone disagrees, why pose it as a question instead of just stating your opinion?

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lavaboosted OP t1_j430t1u wrote

I'm not trying to be defensive just wanted to have the discussion and see what other people's takes on this was. What do you think of the car example?

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TheGreatHomer t1_j433r8m wrote

>What do you think of the car example

I haven't read the paper, but only watched the brief video. I wouldn't say that's Machine Learning either.

Maybe a bad analogy but one I can come up with on a spot: A hinge isn't carpentry but metalwork and pretty much everyone agrees on that. Now if you build a wooden cabinet, you are probably using hinges; Nevertheless, you'd still call the cabinet as such carpentry, not metalwork.

Anyway, the definitions aren't clear and consistent enough to make super good and objectively true distinctions. In the end it often boils down to personal subjective interpretations.

Edit: Especially the classification of evolutionary algorithms has been an ongoing discussion for, like, decades. Which goes to show that there probably isn't an objectively right clear classification - if only because people don't agree on a single definition of Machine Learning as is. However, by the most common definitions that I know, evolutionary computation is its own subfield next to ML.

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pucklermuskau t1_j44znly wrote

it takes data, and evaluates that data against a performance metric, and then adapts the structure in response, creating new data.

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