AI poisoning tool Nightshade received 250,000 downloads in 5 days: \u2018beyond anything we imagined\u2019<\/b><\/p>\n
<\/p>\n
Nightshade, a new, free downloadable tool created by computer science researchers at the University of Chicago which was designed to be used by artists to disrupt AI models scraping and training on their artworks without consent, has received 250,000 downloads in the first five days of its release.<\/span><\/p>\n <\/p>\n \u201cNightshade hit 250K downloads in 5 days since release,\u201d wrote the leader of the project, Ben Zhao, a professor of computer science, in an email to VentureBeat, later adding, \u201cI expected it to be extremely high enthusiasm. But I still underestimated it\u2026The response is simply beyond anything we imagined.\u201d<\/span><\/p>\n <\/p>\n It\u2019s a strong start for the free tool and shows a robust appetite among some artists to protect their work from being used to train AI without consent. According to the Bureau of Labor Statistics, there are more than 2.67 million artists in the U.S. alone, but Zhao told VentureBeat that the users of Nightshade are likely even broader.<\/span><\/p>\n <\/p>\n \u201cWe have not done geolocation lookups for these downloads,\u201d Zhao wrote. \u201cBased on reactions on social media, the downloads come from all over the globe.\u201d<\/span><\/p>\n <\/p>\n How Nightshade works and why it is popular<\/b><\/p>\n Nightshade seeks to \u201cpoison\u201d generative AI image models by altering artworks posted to the web, or \u201cshading\u201d them on a pixel level, so that they appear to a machine learning (ML) algorithm to contain entirely different content \u2014 a purse instead of a cow, let\u2019s say. Trained on a few \u201cshaded\u201d images scraped from the web, an AI algorithm can begin to generate erroneous imagery from what a user prompts or asks.<\/span><\/p>\n <\/p>\n On the Nightshade project page, Zhao and his colleagues \u2014 Shawn Shan, Wenxin Ding, Josephine Passananti, and Heather Zheng \u2014 stated they developed and released the tool to \u201cincrease the cost of training on unlicensed data, such that licensing images from their creators becomes a viable alternative.\u201d<\/span><\/p>\n <\/p>\n Shortly after Nightshade\u2019s release on Jan. 18, 2023, the demand for concurrent downloads of it was so overwhelming to the University of Chicago\u2019s web servers, that the creators had to add mirror links where people could download copies of it from another location on the cloud.<\/span><\/p>\n Meanwhile, the team\u2019s earlier tool \u2014 Glaze, which works to prevent AI models from learning an artist\u2019s signature \u201cstyle\u201d by subtly altering pixels so they appear to be something else to machine learning algorithms \u2014 has received 2.2 million downloads since it was released in April 2023, according to Zhao.<\/span><\/p>\n <\/p>\n What\u2019s next for the Glaze\/Nightshade team?<\/b><\/p>\n Operating under their umbrella name, The Glaze Project, Zhao and his fellow researchers had already previously stated their intention to release a tool combining both Glaze (defensive) and Nightshade (offensive).<\/span><\/p>\n As for when this is coming, it will be at least a month at the soonest.<\/span><\/p>\n <\/p>\n \u201cWe simply have a lot of to-dos on our list right now,\u201d Zhao wrote. \u201cThe combined version must be carefully tested otherwise ensure we don\u2019t have surprises later. So I imagine at least a month, maybe more, for us to get comprehensive tests done.\u201d<\/span><\/p>\n At the same time, The Glaze Project researchers have advocated that artists use Glaze first, then Nightshade, to both protect their style while disrupting AI model training and have been heartened to see artists doing just that, even though it is a little more cumbersome to use two separate programs.<\/span><\/p>\n \u201cWe warned people that we have not done full tests to understand how it works together with Glaze and that folks should wait before releasing any images with only Nightshade,\u201d Zhao explained. \u201cThe artist community\u2019s response was to say, \u2018We will just Nightshade and Glaze in two steps, even though it takes more time and has more visible impact on the art.’\u201d<\/span><\/p>\n AI poisoning tool Nightshade received 250,000 downloads in 5 days: \u2018beyond anything we imagined\u2019<\/span><\/p>\n Carl Franzen<\/span><\/p>\n @carlfranzen<\/span><\/p>\n January 29, 2024 1:46 PM<\/span><\/p>\n Smoke emanates from a PC tower and monitors in a drab office.<\/span><\/p>\n Credit: VentureBeat made with OpenAI DALL-E 3 via ChatGPT Plus<\/span><\/p>\n Nightshade, a new, free downloadable tool created by computer science researchers at the University of Chicago which was designed to be used by artists to disrupt AI models scraping and training on their artworks without consent, has received 250,000 downloads in the first five days of its release.<\/span><\/p>\n \u201cNightshade hit 250K downloads in 5 days since release,\u201d wrote the leader of the project, Ben Zhao, a professor of computer science, in an email to VentureBeat, later adding, \u201cI expected it to be extremely high enthusiasm. But I still underestimated it\u2026The response is simply beyond anything we imagined.\u201d<\/span><\/p>\n It\u2019s a strong start for the free tool and shows a robust appetite among some artists to protect their work from being used to train AI without consent. According to the Bureau of Labor Statistics, there are more than 2.67 million artists in the U.S. alone, but Zhao told VentureBeat that the users of Nightshade are likely even broader.<\/span><\/p>\n \u201cWe have not done geolocation lookups for these downloads,\u201d Zhao wrote. \u201cBased on reactions on social media, the downloads come from all over the globe.\u201d<\/span><\/p>\n How Nightshade works and why it is popular<\/span><\/p>\n Nightshade seeks to \u201cpoison\u201d generative AI image models by altering artworks posted to the web, or \u201cshading\u201d them on a pixel level, so that they appear to a machine learning (ML) algorithm to contain entirely different content \u2014 a purse instead of a cow, let\u2019s say. Trained on a few \u201cshaded\u201d images scraped from the web, an AI algorithm can begin to generate erroneous imagery from what a user prompts or asks.<\/span><\/p>\n On the Nightshade project page, Zhao and his colleagues \u2014 Shawn Shan, Wenxin Ding, Josephine Passananti, and Heather Zheng \u2014 stated they developed and released the tool to \u201cincrease the cost of training on unlicensed data, such that licensing images from their creators becomes a viable alternative.\u201d<\/span><\/p>\n Shortly after Nightshade\u2019s release on Jan. 18, 2023, the demand for concurrent downloads of it was so overwhelming to the University of Chicago\u2019s web servers, that the creators had to add mirror links where people could download copies of it from another location on the cloud.<\/span><\/p>\n Meanwhile, the team\u2019s earlier tool \u2014 Glaze, which works to prevent AI models from learning an artist\u2019s signature \u201cstyle\u201d by subtly altering pixels so they appear to be something else to machine learning algorithms \u2014 has received 2.2 million downloads since it was released in April 2023, according to Zhao.<\/span><\/p>\n What\u2019s next for the Glaze\/Nightshade team?<\/span><\/p>\n Operating under their umbrella name, The Glaze Project, Zhao and his fellow researchers had already previously stated their intention to release a tool combining both Glaze (defensive) and Nightshade (offensive).<\/span><\/p>\n As for when this is coming, it will be at least a month at the soonest.<\/span><\/p>\n \u201cWe simply have a lot of to-dos on our list right now,\u201d Zhao wrote. \u201cThe combined version must be carefully tested otherwise ensure we don\u2019t have surprises later. So I imagine at least a month, maybe more, for us to get comprehensive tests done.\u201d<\/span><\/p>\n At the same time, The Glaze Project researchers have advocated that artists use Glaze first, then Nightshade, to both protect their style while disrupting AI model training and have been heartened to see artists doing just that, even though it is a little more cumbersome to use two separate programs.<\/span><\/p>\n \u201cWe warned people that we have not done full tests to understand how it works together with Glaze and that folks should wait before releasing any images with only Nightshade,\u201d Zhao explained. \u201cThe artist community\u2019s response was to say, \u2018We will just Nightshade and Glaze in two steps, even though it takes more time and has more visible impact on the art.’\u201d<\/span><\/p>\n An open-source version of Nightshade may be in the cards as well. \u201cWe will likely do an open-source version at some point,\u201d Zhao stated. \u201cJust more time required to put out different versions.\u201d<\/span><\/p>\n The project leader noted that he and his colleagues had not, nor did they expect to hear directly from, the model makers behind AI image-generating technology, such as OpenAI (DALL-E 3), Midjourney, Stability AI (Stable Diffusion), and others. VentureBeat uses some of these tools and others to create article imagery and other content.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":" AI poisoning tool Nightshade received 250,000 downloads in 5 days: \u2018beyond anything we imagined\u2019 Nightshade, a new, free downloadable tool created by computer science researchers at the University of Chicago which was designed to be used by artists to disrupt AI models scraping and training on their artworks without consent, has received 250,000 downloads …<\/p>\n","protected":false},"author":1,"featured_media":2034,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[],"class_list":["post-2033","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t