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I took a quick look into the paper. To be honest (I'm far from being an expert). As I understand it seems they took some toy models, and tried to show that the
by MichaelRazum 3y ago
I took a quick look into the paper. To be honest (I'm far from being an expert).
As I understand it seems they took some toy models, and tried to show that the models do not generalize out of sample.
To me it is unclear what does it say about much more complex models? So for example there might be already so much structure, that you do not need to generalize out of sample and maybe humans don't do it as well.
- vasilipupkin 3y agoagree, I am not sure how useful this is. Do humans generalize outside of their training data? Would you hire a divorce lawyer to work on an M&A transaction? nobody would do that. Would you hire a local butcher to do open heart surgery ?
- bad_user 3y ago> Do humans generalize outside of their training data? JFC, is this a joke?
- MacsHeadroom 3y ago> Do humans generalize outside of their training data? Obviously they don't.
- bad_user 3y agoYou jest, but every word coming out of our mouths is a generalisation that someone thought of.
- MacsHeadroom 3y agoOh no, I was being serious. People just don't understand how vast the unexplored in-distribution space is.
- tessierashpool 3y agoDo humans generalize outside of their training data? Absolutely not. Never. If that happened, you'd get programmers thinking they could solve every type of problem in the world, based on wildly oversimplified mental models. It would be utter chaos.
- discreteevent 3y agoYou ask: "Do humans generalize outside of their training data?" But then you give two examples of people specializing outside of their training data. But even then a divorce lawyer would do a lot better than me at M&A because they can generalize from what they learned about the law from divorce cases.