This chapter explores the idea of using closed access to proprietary data to build specialized AI models, discussing whether companies should train their own models or add data to existing ones. It draws parallels with humans learning proprietary information at work and argues that fine-tuning models with proprietary data is more cost-effective than developing models from scratch.

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