Like the N-convex algorithm, this algorithm attempts to find a set of candidates whose centroid is close to . The key difference is that instead of taking unique candidates, we allow candidates to populate the set multiple times. The result is that the weight of each candidate is simply given by its frequency in the list, which we can then index by random selection:
专为函数调用而生 — 并非通用聊天工具，更多细节参见同城约会
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而要解开这一矛盾，我们需先拆解AI产业链的三层架构，看清各环节的价值逻辑与生存现状。。同城约会对此有专业解读