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Ask me anything and I'll reply as a data scientist. Wrong questions only.
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How do you correctly correlate in arbitrary datasets and come to the correct causation every time? How do AI, ML, and blockchain improve this process?
2 questions here, I'll unbundle. 1st: using a pivot table. 2nd: I'm an eco friendly data scientist therefore I refuse to answer questions with blockchain.
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AI/ML, especially without human-tagged data, is a lot more energy efficient than blockchain. So could you scope down the answer to 2) and share your wisdom?
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Aaah that's easy. AI / ML reduce complexity by ignoring petty differences between causation and correlation. Beyond that, a pivot table is still your best shot.
End of conversation
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