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Greedy search in clustering not only achieves optimal outcomes but also reveals why traditional methods fail with irregular cluster shapes and densities.
Resource-constrained Arabic AI development can compete with systems built at far greater scale, as demonstrated by Fanar 2.0's performance gains using 8x fewer pre-training tokens than its predecessor.
