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.
“Two and a half years later, our honest assessment is that some parts of this theory of change have played out as we hoped, but others have not,” Anthropic wrote. Now, its updated policy approaches safety relatively, rather than with strict red lines.
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Graceful Fallback for Extreme Customization:
Squire works for US Department of Homeland Security Investigations in an elite unit which attempts to identify children appearing in sexual abuse material.
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