Isabelle Levent

Academically, this is a collision of everything from computer science and art history to media studies to disruptive innovation to labor economics, and no one of these disciplines seems sufficient to cover the topic. 

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

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

As more artists gain access to AI and take up the tools, artists will have a whole new look — both how they look making art and how their art develops.

New art-making technologies change art in consistent ways, and studying the past helps us understand how things will change in the future.

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