Isabelle Levent

Maybe the creative work is now to figure out ways to nudge AIs into being weird and interesting rather than producing inane imitations of the most ordinary human writing

Second, we should create a legal regime that can make our data’s collective value something we can bargain over as a group.

My lesson from these two examples is that it might be possible to make prompting “invisible” by making it part of the UI, and finetuning output for as much of the writer’s context as possible to make it more useful. Latency matters, and cost matters, which are wonderful because these tend to be “regular engineering” type problems rather than AI

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 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’

For a computer to make a subtle combinational joke, never mind to assess its tastefulness, would require, first, a data-base with a richness comparable to ours, and, second, methods of link-making (and link-evaluating) comparable in subtlety with ours.