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With Resident Evil Requiem, we focused on enhancing the presentation quality of the protagonist through an upgraded version of RE Engine to deepen the player’s immersion in horror. For example, each individual strand of hair and beard is rendered as a polygon, allowing it to move realistically in response to body motion and wind. The way light passes through his hair changes depending on how the strands of hair are overlapped as well. This detailed expression of texture is one of the many details that we would especially love for our fans to see.

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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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