原文整理页

Aaron Levie 探讨了模型蒸馏的公平性问题,质疑其与在网页数据上进行原始训练在法律或哲学上有何本质区别

来源作者:Aaron Levie (@levie)原始来源:https://x.com/levie/status/2080127457282433441

中文导读

Aaron Levie 探讨了模型蒸馏的公平性问题,质疑其与在网页数据上进行原始训练在法律或哲学上有何本质区别。

正文 Markdown

For those that are deeply passionate about model distillation as a problem, can you explain why you think it’s both more unfair than the original training runs of models on web data and/or different from us all collectively publishing our outputs of models on github and training on that? It’s clear that AI labs should do everything they can to prevent distillation, because of course they’re going to try and protect their assets as much as possible. But why do we think it’s a definitely past threshold legally or philosophically than training? Happy for any answers to this.