Canadian government demands safety changes from OpenAI

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It's a shame, because DTF St. Louis is full of some genuinely funny moments, from a suspicious smoothie rendezvous to a whispered discussion at the Outback Steakhouse urinals about using DTF St. Louis. Peak loser behavior! I wish DTF St. Louis leaned further into that angle, but in the end, its underwhelming, nonchronological mystery approach wins out.

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Regions with many nearby points keep subdividing. Regions with few or no points stay large. The tree adapts to the data: dense areas get fine-grained cells, sparse areas stay coarse. The split grid is predetermined (always at midpoints), but the tree only refines cells that need it. Sparse regions stay as single large nodes while dense regions subdivide deeply.

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