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Another reason that neural nets do crazy things: they have little knowledge. We see a dog, by looking at it's shape etc. The neural net by looking at features.
by Qantourisc 11y ago
Another reason that neural nets do crazy things: they have little knowledge. We see a dog, by looking at it's shape etc. The neural net by looking at features.
A solution to this I think would be splitting up the taks, like "finding eyes", "is this fur", etc ... freeze these networks, and use these as input. This would prevent most errors given in these examples.
A lot of animals know what eyes look like regardless of the species, not saying nature always has the best solution. But it probably had a good reason to have a specialized-build-in "head/eyes" detector.
- seiji 11y agoWe see a dog, by looking at it's shape etc. The neural net by looking at features. Have you ever seen a kid learn language? At first, every four legged animal is either a cat or a dog. Every car is a truck (or every truck is a car). The specific categories get learned over time, but they aren't in any sense "natural."
- igravious 11y agoYou remember that bit in Hitchhiker's Guide where Arthur Dent is explaining to the ship's onboard Nutri-matic thing (I think it was) all about what a cup of tea is. After getting back many different versions of a drink that was nearly but not quite unlike tea, Arthur explained about tea leaves and climates and tea trade and tea ceremonies and on and on. I'm sure my recollection and retelling do not do it justice. My point is, what we've got now is crude visual-feature pattern matching and recognition. What you're asking for is conceptualisation. Wiring up concepts to sense-data is our trick. We are reverse engineering ourselves bit by bit. You make the next step sound so reasonable, and maybe perhaps it is.