Revisiting phonon thermal transport in penta-graphene via a machine-learning potential-driven large-scale molecular dynamics simulation

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В Финляндии предупредили об опасном шаге ЕС против России09:28

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第四节 妨害社会管理的行为和处罚

In the months since, I continued my real-life work as a Data Scientist while keeping up-to-date on the latest LLMs popping up on OpenRouter. In August, Google announced the release of their Nano Banana generative image AI with a corresponding API that’s difficult to use, so I open-sourced the gemimg Python package that serves as an API wrapper. It’s not a thrilling project: there’s little room or need for creative implementation and my satisfaction with it was the net present value with what it enabled rather than writing the tool itself. Therefore as an experiment, I plopped the feature-complete code into various up-and-coming LLMs on OpenRouter and prompted the models to identify and fix any issues with the Python code: if it failed, it’s a good test for the current capabilities of LLMs, if it succeeded, then it’s a software quality increase for potential users of the package and I have no moral objection to it. The LLMs actually were helpful: in addition to adding good function docstrings and type hints, it identified more Pythonic implementations of various code blocks.,更多细节参见搜狗输入法下载

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这一环节的优势十分突出,技术垄断性强、行业集中度高,现金流稳定,风险相对较低——无论下游“淘金客”成败,都离不开硬件工具的支撑。但风险同样不容忽视:技术迭代可能颠覆现有硬件需求,且过度依赖资本循环,若下游融资断裂,订单规模或将大幅缩水。