Isabelle Levent

We find that models learn just as fast with many prompts that are intentionally irrelevant or even pathologically misleading as they do with instructively “good” prompts. Further, such patterns hold even for models as large as 175 billion parameters (Brown et al., 2020) as well as the recently proposed instruction-tuned models which are trained on

the reconfiguration of culture as a domain of not just human-made meanings but also machinic calculation

Our intuitive moral understanding of actors and transgressions may be at odds with the inherent complexity of AI systems.

Indeed, AI is a diffuse term that corresponds to a web of human actors and computational processes interacting in complex ways

There are a couple reasons why Wordcraft may have struggled with style and voice... Another reason could have been limitations of the underlying model. LaMDA and other similar language models are trained to be most confident on the kind of text they see most often–typically internet data. However, professional creative writers are usually writing