A painful processToday, kernel maintainers who want a kernel.org account must find someone already in the PGP web of trust, meet them face‑to‑face, show government ID, and get their key signed. The process is like a manual, global scavenger hunt. Linux kernel maintainer Greg Kroah-Hartman, speaking at the Linux Foundation Members Summit, described it as a "pain to do and manage." That's because it's tracked by manual scripts, the keys drift out of date, and the public "who lives where" map creates privacy and social‑engineering risk.
returns. We target a ~5% spend rate, typical for
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Map Version Synchronicity (Important!): For HH-Routing to work correctly when a route crosses multiple map files (e.g., different countries or regions), all those map files MUST be from the same generation date (i.e., downloaded from OsmAnd around the same time, based on the same underlying OpenStreetMap data version and pre-calculation run).
But that’s unironically a good idea so I decided to try and do it anyways. With the use of agents, I am now developing rustlearn (extreme placeholder name), a Rust crate that implements not only the fast implementations of the standard machine learning algorithms such as logistic regression and k-means clustering, but also includes the fast implementations of the algorithms above: the same three step pipeline I describe above still works even with the more simple algorithms to beat scikit-learn’s implementations. This crate can therefore receive Python bindings and even expand to the Web/JavaScript and beyond. This also gives me the oppertunity to add quality-of-life features to resolve grievances I’ve had to work around as a data scientist, such as model serialization and native integration with pandas/polars DataFrames. I hope this use case is considered to be more practical and complex than making a ball physics terminal app.