Fine-tuning language models using crowdsourcing similar to Wikipedia

The idea of fine-tuning language models through a collaborative, crowd-sourced approach similar to Wikipedia is a compelling one. It aims to train models to be safe, aligned, and responsible. By allowing a broader community to participate in the fine-tuning process, it aligns with the ethos of open sourcing technology and acknowledges the challenges of infrastructure, community management, and product perspectives. However, this approach raises many questions and requires further research to determine the best way to produce aligned AI models. The success of Wikipedia in handling controversial topics with balance and grace serves as inspiration, although it is not a perfect system. In the pursuit of truth, knowledge, and wisdom, AI models must strive to achieve similar outcomes.

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