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The second AI bubble burst shares many similarities with today's AI boom. Back then, expert systems were put on a pedestal, capital poured in wildly, and companies invested heavily in building systems. But what happened?
High maintenance costs, rigid rules, and an inability to adapt to complex scenarios led to the failure of numerous projects, and the market quickly cooled down. Is today's large language model following a similar path?
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