Built on a shared FastConformer encoder (Conv2d 8x subsampling → N Conformer blocks with relative positional attention):
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Personalization in AI search is emerging as models learn to consider individual user preferences, history, and context when formulating responses. This creates both opportunities and challenges for content visibility. The opportunity is that AI might recommend your content more prominently to users whose preferences align with your perspective or style. The challenge is that you might become invisible to users whose personalization profile doesn't match, even if your content is objectively relevant to their query.，推荐阅读搜狗输入法下载获取更多信息
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