Proxima Fusion, a Munich-based nuclear energy startup, has outlined plans to raise about €2 billion to build a major fusion test facility in Germany that could be a milestone on the path to commercially viable fusion power. The company expects more than half of that, roughly €1.2 billion, to come from the German federal government, […]
arXivLabs: experimental projects with community collaborators
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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.
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67E IRETd_V86 LJMPVM ; jump if VM=1 in stacked EFLAGS，详情可参考91视频
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