魔法原子(MagicLab)成立于2024年1月,是一家专注于通用人形机器人和具身智能技术研发与落地应用的全球化公司。公司核心成员汇聚清华、上海交大、密西根大学等国内外顶尖高校,研发人员占比超70%,拥有全栈自研的软硬件技术体系。其核心硬件自研比例超90%,覆盖关节模组、灵巧手等关键零部件,并自研VLA大模型“原子万象”,采取VLM+MoE分层架构,已采集约36万条真机数据,实现了多模态感知与具身操作的算法领先。
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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.
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