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Joined 1 year ago
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Cake day: June 12th, 2023

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  • I think the exact opposite, ML is good for automating away the trivial, repetitive tasks that take time away from development but they have a harder time with making a coherent, maintainable architecture of interconnected modules.

    It is also good for data analysis, for example when the dynamics of a system are complex but you have a lot of data. In that context, the algorithm doesn’t have to infer a model that matches reality completely, just one that is close enough for the region of interest.








  • Out of curiosity, what are you’re thoughts on the below scenarios:

    • attempted robbery If you go to a bank and attempt to steal money, but you were unsuccessful in doing so, there wouldn’t be any loss, but you’d still go to jail and it’s widely accepted as wrong.
    • getting a service, e.g going to the barbers and running out of the store before paying There wouldn’t be a loss again

    Those aren’t really good equivalents since in the first example, you’re trying to take something away from someone but you fail. The law is not concerned with your skill, just your intent. Attempted murder is illegal even if the victim is still alive.

    In the second example, there is absolutely a loss. The barber would have spent time and used resources in order to provide you with that service that they wouldn’t get compensated for. Your involvement directly costs them money and time, unlike with piracy where even a billion people pirating won’t cost the developer any more money than if those people just never played it to begin with.