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Challenge: Build the smallest transformer that can add two 10-digit numbers with = 99% accuracy on a held-out 10K test set.

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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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周杰,资深编辑,曾在多家知名媒体任职,擅长将复杂话题通俗化表达。

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