confusable-vision takes the 1,418 TR39 confusable pairs that map a non-Latin character to a Latin target (a-z, 0-9), renders both characters across every available system font, and computes SSIM for each pairing. The output is a scored JSON artifact: one continuous similarity score per pair, per font.
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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if (audioElement.buffered.length 0) {。关于这个话题,同城约会提供了深入分析
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До этого глава Франции Эммануэль Макрон также сообщил, что Франция в настоящее время предоставляет Украине две трети от всех разведданных. Политик отметил, что Париж и другие европейские столицы должны обзавестись оружием, которое могло бы быть аналогом российского ракетного комплекса «Орешник».