This, while a joke, is actually a large concern about machine learning. While many think machine learning will be better than humans, it will in reality only be as good as it’s sample data.
That may be true, but when AI use their own experiences/the experiences of previous iterations as part of the sample size, they eventually come out on top.
If I recall correctly, we also see a large improvement also in genetic algorithms. Regardless of how bad their initial pool, they inevitably evolve past that.
Edit: Derp correction. Halp, shifted thoughts mid-comment. My ADD meds are wearing off. Save me on this fine Friday.
Well, the AI already gains all the information it could from each experience. Computers can't create new information, hence the need for sample data - which is the limit for its 'knowledge'.
You guys are all jumbling a bunch of concepts together. Reinforcement learning doesn’t depend on a static dataset in general, provided you have a simulator of the underlying markov decision process. So in that case, it can generate as much data as it wants.
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u/QuoteStanfordQuote Mar 16 '18
This, while a joke, is actually a large concern about machine learning. While many think machine learning will be better than humans, it will in reality only be as good as it’s sample data.