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:
Update, February 27, 9PM ET: This story was updated twice after publish. First at 6PM ET to include a link to and quotes from Hegseth about the designation of Anthropic as a supply chain risk. Later, a quote from Anthropic was added, along with a link to the company’s blog post on the subject.
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Пари Нижний Новгород。关于这个话题，同城约会提供了深入分析
63-летняя Деми Мур вышла в свет с неожиданной стрижкой17:54