Alan Turing — "The machine has to be able to do something which it has never been programmed to…"
The machine has to be able to do something which it has never been programmed to do.
The machine has to be able to do something which it has never been programmed to do.
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"The machine should be able to use language."
"If a machine can pass the Turing Test, then it is intelligent."
"I like to think the brain is a kind of pudding, but not a Christmas pudding."
"The human mind is a probabilistic machine."
"One day ladies will take their computers for walks in the park and tell each other, 'My little computer said such a funny thing this morning'."
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True intelligence — human or machine — isn't just executing memorized instructions. A genuinely intelligent machine must generalize: facing a new problem it was never explicitly taught to solve, it should still find an answer. That gap between stored rules and novel action is where real thinking begins. It's the foundational idea behind modern machine learning, where systems trained on data handle situations no programmer ever anticipated.
Turing's landmark 1950 paper 'Computing Machinery and Intelligence' proposed the Turing Test and explored 'learning machines' — systems that adapt beyond initial programming. At Bletchley Park, he cracked Enigma not by brute memorization but by inferring hidden patterns, the same generalization he demanded of machines. Turing believed intelligence meant escaping rigid rules, a conviction his own unconventional, boundary-breaking thinking consistently demonstrated.
In the early 1950s, computers were enormous fixed-program machines — the Manchester Mark 1, ENIAC — strictly executing predefined instructions. The Cold War drove urgent interest in computation, but thinking machines were philosophical fantasy, not engineering goals. Turing's 1950 paper dropped into that world like a provocation: at a moment when programmers wrote every instruction by hand, he was already asking whether machines could outgrow their own code.
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