Researchers at Meta FAIR have developed a new k-means clustering algorithm called e-means, which achieves a 10x speedup in both epochs and wall-clock time compared to the traditional Lloyd's algorithm while maintaining lower loss. E-means outperforms Lloyd's algorithm by better escaping local minima and utilizing automatic hyperparameter tuning with scaling laws. In experiments, e-means reached a test loss below Lloyd's in 1.2 to 3 epochs, resulting in a 10-45x wall-clock reduction on GPU and 8-15x on CPU. This breakthrough allows for both faster and higher-quality k-means clustering, making e-means a promising replacement for Lloyd's algorithm, and it is now available as open-source code.