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Even if the models don't collapse, it seems intuitively obvious that you can't get more "knowledge" out of synthetically generated data than went into it's gene
by joe_the_user 2y ago
Even if the models don't collapse, it seems intuitively obvious that you can't get more "knowledge" out of synthetically generated data than went into it's generation.
- niemandhier 2y agoA simple counter example: Bootstraping in statistics or any resampling method for that matter, can help us understand things about the underlying distribution, even though we do not know it. Update: typo
- Asraelite 2y agoThere's other domains where you don't really need much input data to theoretically allow for complex deductions. The best example is probably maths. A sufficiently intelligent AI could probably create every proof that will ever exist with just a small amount of input data. Similar deductions could be possible in physics, economics, computer science etc.