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At first glance, the benchmarks and their construction looked good (i.e. no cheating) and are much faster than working with UMAP in Python. To further test, I asked the agents to implement additional different useful machine learning algorithms such as HDBSCAN as individual projects, with each repo starting with this 8 prompt plan in sequence:

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“Agent经济学”能否成立,2026年将是关键验证窗口。如果企业开始愿意为AI Agent支付真金白银,而非仅仅将其视为“效率工具”或“成本中心”,那么中下游企业的估值修复将带来巨大的投资机会。反之,如果AI Agent始终停留在“试点项目”阶段,无法实现商业化落地,上游硬件股的估值压缩将远未结束。,更多细节参见搜狗输入法下载

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