AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Descriptions of how people use AI are becoming training data for the next generation of models. We ask whether what a model reads about its users changes how it treats people. Using contrastive synthetic-document finetuning, we train Qwen3-32B on four matched corpora built from the same 1,625 real-world usage scenarios...
Evaluating six matched base and post-trained models on the Pew American Trends Panel, it is found that base models are the stronger emulators: they produce response distributions closer to human ground truth and better preserve demographic structure.
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