Smaller models seem to be more complex. The encoding, reasoning, and decoding functions are more entangled, spread across the entire stack. I never found a single area of duplication that generalised across tasks, although clearly it was possible to boost one ‘talent’ at the expense of another. But as models get larger, the functional anatomy becomes more separated. The bigger models have more ‘space’ to develop generalised ‘thinking’ circuits, which may be why my method worked so dramatically on a 72B model. There’s a critical mass of parameters below which the ‘reasoning cortex’ hasn’t fully differentiated from the rest of the brain.
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1分钟，北京大兴机场起降1架次航班；。超级权重对此有专业解读
2026-03-09 00:00:00:0 代表委员热议海南自由贸易港建设