People are debating everywhere: Statistics or AI? On LinkedIn, on Twitter, and even within research teams! “Statistics is better because it’s rigorous and proven!” “That’s not true, AI is better because it’s powerful and scalable!” Can one exist without the other? Statistics provides the foundation—rigor, reliability, a way to interpret data. Got a small dataset? No problem. AI takes it further, adding prediction, automation, and scale. But it needs data. And, crucially, reliable data. So, where do we draw the line? At what point does statistical analysis evolve into AI? For us at AICU, they’re complementary: statistics makes AI reliable, and AI makes statistics powerful. We aim to make AI as trustworthy as traditional statistics. What do you think? Can we really separate them? Let’s discuss!
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