From attention to multimodal AI, transformers reshape how machines understand language and world data.
Attention alone can tune a model's vocabulary faster than retraining on new data in some transformers.
The largest gains in translation accuracy came from training on synthetic data generated by the model itself, not humans.
A single transformer layer can memorize entire training corpora, revealing privacy risks even in high-privacy settings.
Quantized transformers can outperform their full-precision cousins on edge devices due to error distribution, not just size reduction.
From attention to multimodal AI, transformers reshape how machines understand language and world data.
Attention alone can tune a model's vocabulary faster than retraining on new data in some transformers.
The largest gains in translation accuracy came from training on synthetic data generated by the model itself, not humans.
A single transformer layer can memorize entire training corpora, revealing privacy risks even in high-privacy settings.
Quantized transformers can outperform their full-precision cousins on edge devices due to error distribution, not just size reduction.
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