AI at the Frontier: What it Takes to Compete
ChinaTalk
Efficiency and Effectiveness of Sparse Models in Complex Machine Learning Architectures
Sparse models with a mixture of experts in machine learning architectures yield higher compute efficiency due to fewer active parameters requiring matrix multiplication. However, despite lower compute usage, significant RAM for model weights in memory and additional GPUs may be necessary. Implementing a fast follow by adding a sparse model to pre-trained models allows for quick paper publication. DeepSeek AI stands out for popularizing the concept of smaller expert models with shared experts, leading to a notable 10% improvement in performance when added to pre-trained models.
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