Isabelle Levent

There’s another edge case as well; in theory, with the same prompts and the random seed that’s used for generating the images, you could end up with someone else generating the same, or a very similar, image as what you created. 

A recurring theme in participant feedback was that the language model lacked taste and intentionality...In contrast, good writers are skilled not only in producing but also discerning good language. In other words, they have taste, the ability to decide why one sentence is interesting while another is not.

"The data we licensed from Shutterstock was critical to the training of DALL-E,” said Sam Altman, OpenAI’s CEO. “We’re excited for Shutterstock to offer DALL-E images to its customers as one of the first deployments through our API, and we look forward to future collaborations as artificial intelligence becomes an integral part of artists’

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

Whereas if you put them in a group, they’ll go “dog” and someone else will go “space dog” and someone else will go “Aztec space dog,” and then all of a sudden, people understand the possibilities, and you’re creating this augmented imagination — an environment where people can learn and play with this new capacity. So we found that people really

Now none of this is meant to say that I think programmers, artists and engineers have no responsibilities when it comes to the outputs of machine learning models. In fact, I think we bear responsibility for everything these models do. (I never, for example, attribute authorship to a program or a model. If I publish the results of a text generator,