Testing LLM reasoning abilities with SAT is not an original idea; there is a recent research that did a thorough testing with models such as GPT-4o and found that for hard enough problems, every model degrades to random guessing. But I couldn't find any research that used newer models like I used. It would be nice to see a more thorough testing done again with newer models.
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他表示，他與班德合作，將這項構想化為「克林頓全球倡議」的實際計劃。
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icon-to-image#As someone who primarily works in Python, what first caught my attention about Rust is the PyO3 crate: a crate that allows accessing Rust code through Python with all the speed and memory benefits that entails while the Python end-user is none-the-wiser. My first exposure to pyo3 was the fast tokenizers in Hugging Face tokenizers, but many popular Python libraries now also use this pattern for speed, including orjson, pydantic, and my favorite polars. If agentic LLMs could now write both performant Rust code and leverage the pyo3 bridge, that would be extremely useful for myself.