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around a year ago, we built a regex engine in F# that not only outperformed the ones in dotnet, but went above and beyond competing with every other industrial regex engine on a large set of industry-standard benchmarks. additionally, it supports the full set of boolean operators (union, intersection, complement) and even a form of context-aware lookarounds, which no other engine has while preserving O(n) search-time complexity. the paper was published at POPL 2025, and i figured it’s time to open source the engine and share the story behind it. consider it a much more casual and chatty version of the paper, with more focus on engineering aspects that went into it.
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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.
Как сообщает РЕН ТВ в своем Telegram-канале, речь идет об инциденте, произошедшем летом 2023 года. Тогда Итальянец получил выговор от администрации колонии за то, что вовремя не заправил кровать и не надел брюки. После освобождения он подал в суд на надзирателей и выиграл его.
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