Isabelle Levent

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.

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,

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

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

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

They will shade our constant submissions to the vast digital commons, intentional or consensual or mandatory, with the knowledge that every selfie or fragment of text is destined to become a piece of general-purpose training data for the attempted automation of everything. They will be used on people in extremely creative ways, with and without