Super Bowl LX was a two-score game with less than five minutes remaining. New England had the ball on the Seahawks’ 44-yard line and – after reaching the end zone in the fourth quarter, finally – that familiar sense of possibility. But that quickly vaporized when Devon Witherspoon knifed in on a corner blitz and jarred the ball loose from the Patriots quarterback, Drake Maye, mid-throw. Uchenna Nwosu snatched it in stride and rumbled 45 yards to the end zone, sealing Seattle’s 29‑13 victory.
// Can be any thing here that writes into the view
Tony Jolliffe BBC
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.
Ac we nought free ne sindon, for-thy-the we never ne mighton from Wulfsfleet yewitan, nefne we thone Hlaford finden and hine ofslain. Se Hlaford hath thisne stede mid searocraftum yebounden, that none ne may hine forletan. We sindon here so fuglas on nete, so fishes on weir.