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.
Mark Zandi, chief economist at Moody’s Analytics, invoked the Spanish conquistador Hernán Cortés—who burned his boats upon arriving in Mexico in 1519, eliminating any possibility of retreat—to describe the posture he believes corporate America is quietly assuming toward AI adoption. Companies are investing heavily, making structural bets, and cutting off their own escape routes. Whether that leads to conquest or catastrophe, Zandi suggests, may depend on timing. The analogy crystallized for Zandi after fintech company Block announced it was slashing its workforce by 40%.
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