Did AI research stop during periods of disappointment?
No. Researchers continued developing methods and applications, although funding and attention shifted. Progress in a subfield can continue even when the broader label loses popularity.
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More FAQs in Why was AI difficult to develop for several decades?
No. Data quality, algorithm design, representing knowledge, and handling unfamiliar situations also mattered. Faster computers help only when the underlying method can use them effectively.
Everyday situations rely on many unstated assumptions and exceptions. Writing all of them as explicit rules becomes difficult as the range of situations expands.
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