Oddly, it's been reported that one condition is that OpenAI achieves artificial general intelligence. AGI is when AI evolves to or beyond human-level abilities, at which point the entire world turns into rainbows and everyone gets a pony. This could happen later this year, according to those bullish on the technology, or never, according to many researchers. Sam Altman said it was coming in 2025 but has since grown weary of the term.
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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One major limitation of malloc (and even the best implementations like jemalloc and dlmalloc) is that they try to use a single allocator for each data structure. This is a mistake: A huge performance gain can be had by using
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