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Imagine a room full of identical twins, raised in the same home, educated in the same school, fed the same diet of knowledge, and granted identical tools to explore the world. Would we expect each twin to paint a wholly original masterpiece, pen a novel unlike any other, or devise a singular philosophy? Most of us would hesitate—surely, such uniformity in upbringing would nudge their outputs towards eerie similarity. Now, transplant this thought experiment into the realm of artificial intelligence. If AI applications—built on the same infrastructure, fuelled by identical technology, trained with the same learning models, and granted unfettered access to the same sprawling internet, archives, datasets, databases, and libraries—conduct their research, how can we reasonably anticipate unique results? It’s a question that tantalises technologists, philosophers, and anyone peering into the future of machine intelligence.