The Glaze/Nightshade team, for its part, denies it is seeking destructive ends, writing: Nightshade’s goal is not to break models, but to increase the cost of training on unlicensed data, such that licensing images from their creators becomes a viable alternative.

In other words, the creators are seeking to make it so that AI model developers must pay artists to train on data from them that is uncorrupted.

How did we get here? It all comes down to how AI image generators have been trained: by scraping data from across the web, including scraping original artworks posted by artists who had no prior express knowledge nor decision-making power about this practice, and say the resulting AI models trained on their works threatens their livelihood by competing with them.

The internet’s steady fall into the AI-garbled dumpster continues. As Vice reports, a recent stud y conducted by researchers at the Amazon Web Services (AWS) AI Lab found that a “shocking amount of the web” is already made up of poor-quality AI-generated and translated content.

The paper is yet to be peer-reviewed, but “shocking” feels like the right word. According to the study, over half — specifically, 57.1 percent — of all of the sentences on the internet have been translated into two or more other languages. The poor quality and staggering scale of these translations suggest that large language model (LLM)-powered AI models were used to both create and translate the material. The phenomenon is especially prominent in “lower-resource languages,” or languages with less readily available data with which to more effectively train AI models.

In other words, in what the researchers believe to be a ploy to garner clickbait-driven ad revenue, AI is being used to first generate poor-quality English-language content at a remarkable scale, and then AI-powered machine translation (MT) tools transcribe said content into several other languages. The translated material gets worse each time — and as a result, entire regions of the web are filling to the brim with degrading AI-scrambled copies of copies.

One brain to rule them

Two researchers have revealed how they are creating a single super-brain that can pilot any robot, no matter how different they are.

Sergey Levine and Karol Hausman wrote in IEEE Spectrum that generative AI, which can create text and images, is not enough for robotics because the Internet does not have enough data on how robots interact with the world.