LLM training data mixture optimization breaks when training pools shift — every prior proxy experiment becomes stale.
The rise of AI, graphic processing, combinatorial optimization and other data-intensive applications has resulted in data-processing bottlenecks, as ever greater amounts of data must be shuttled back ...
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