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Lazy DFAs (2010) are a clever optimization to mitigate the O(2^m) blowup of DFA construction, by only constructing the states that you actually visit. lazy DFAs reduce the theoretical automata construction time to either O(2^m) or O(n), whichever is lower. you could argue that it’s theoretically no longer linear time, since you could have a regex that creates a new state for every character in the input, but in practice you will keep revisiting the same states. for all intents and purposes it behaves more like O(n) with some initial wind-up time. the main downside of lazy DFAs is that they are more complex to implement, and you have to ship a compiler as part of your regex algorithm. i want to highlight Rust regex and RE2 as excellent implementations of this approach, which you can also see in the benchmarks.，推荐阅读夫子获取更多信息
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回想百度一路而来的发展历程，它确实是中国一众互联网企业中对于人工智能押注最早、动作最多、培养人才最多的一家——尤其是从资金的投入方面，其在 2023 年 1 月，百度在大模型爆发之前，就宣布已经投入了 1000 亿元用于研发，有不少与 AI 相关。