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

Whatever the size of the space, someone who comes up with a new idea within that thinking-style is being creative in the second, exploratory, sense. If the new idea is surprising not just in itself but as an example of an unexpected general  type , so much the better.

Much of the discussion this year is about text-to-image, but I believe this is a temporary stage; these things are going to continue evolving very quickly.

As part of this model where the ‘back-end’ gets more attention than the artefact, a systematic dismantling of the myth of ‘the artist’ as a stand-alone genius, standing above, or aside from the world, needs to be enacted.

OpenAI, which has been accused by its peers of releasing tools to the public with reckless speed, is particularly good at designing interfaces for its models that feel like magic. “It’s a conscious design imperative to produce these moments of shock and awe,” Crawford says. “We’re going to keep having those moments of enchantment.”

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. 

In the course of a year, the tech industry’s dreary post-social, post-crypto interregnum was rapidly supplanted — largely as the result of public-facing efforts by OpenAI, which is reportedly in talks with Microsoft about a potential $10 billion investment — by a story about inevitable technologies that are  so  transformative,  so  incomprehensibl