{"id":6731,"date":"2023-10-24T13:31:02","date_gmt":"2023-10-24T13:31:02","guid":{"rendered":"https:\/\/dailyai.com\/?p=6731"},"modified":"2023-10-24T13:31:02","modified_gmt":"2023-10-24T13:31:02","slug":"data-poisoning-tool-helps-artists-punish-ai-scrapers","status":"publish","type":"post","link":"https:\/\/dailyai.com\/es\/2023\/10\/data-poisoning-tool-helps-artists-punish-ai-scrapers\/","title":{"rendered":"La herramienta de envenenamiento de datos ayuda a los artistas a castigar a los \"scrapers\" de IA"},"content":{"rendered":"

Investigadores de la Universidad de Chicago desarrollaron una nueva herramienta para \"envenenar\" los modelos de IA cuando las empresas de este campo incluyen im\u00e1genes en sus conjuntos de datos sin consentimiento.<\/strong><\/p>\n

Empresas como OpenAI y Meta se han enfrentado a cr\u00edticas y demandas judiciales por el uso masivo de contenidos en l\u00ednea para entrenar sus modelos. Para que generadores de texto a imagen como DALL-E o Midjourney sean eficaces, deben entrenarse con grandes cantidades de datos visuales.<\/p>\n

Una serie de artistas<\/a> se han quejado de que estos generadores de im\u00e1genes son ahora capaces de producir im\u00e1genes en su estilo despu\u00e9s de raspar su arte sin consentimiento.<\/p>\n

En los investigadores crearon Nightshad<\/a>e, una herramienta que incrusta p\u00edxeles invisibles en una imagen que posteriormente la convierte en \"venenosa\" para los modelos de IA.<\/p>\n

La IA generativa se basa en datos etiquetados correctamente. Si un modelo de IA se entrena con miles de im\u00e1genes de gatos y todas ellas est\u00e1n etiquetadas como \"gato\", sabr\u00e1 qu\u00e9 aspecto debe tener un gato cuando se le pida que genere una imagen de uno.<\/p>\n

Nightshade incrusta datos en la imagen que corrompen la clasificaci\u00f3n de la misma. As\u00ed, por ejemplo, una imagen de un castillo envenenado por Nightshade se clasificar\u00eda como un cami\u00f3n viejo. Los investigadores descubrieron que el uso de tan solo 100 im\u00e1genes dirigidas a un \u00fanico indicador era eficaz para corromper un modelo.<\/p>\n

\"\"
Las im\u00e1genes generadas se corrompen cada vez m\u00e1s con datos envenenados. Fuente: arXiv<\/a><\/figcaption><\/figure>\n

Nightshade es una mala noticia para los generadores de im\u00e1genes por IA<\/h2>\n

Un modelo afectado por datos envenenados podr\u00eda pensar que las im\u00e1genes de pasteles son sombreros, o que las tostadoras son bolsos. Adem\u00e1s de corromper la palabra espec\u00edfica a la que apunta Nightshade, la corrupci\u00f3n tambi\u00e9n infecta conceptos m\u00e1s amplios. As\u00ed, corromper la etiqueta \"perro\" extender\u00eda la corrupci\u00f3n tambi\u00e9n a t\u00e9rminos como \"cachorro\".<\/p>\n

Si un n\u00famero suficiente de artistas empieza a utilizar Nightshade, las empresas tendr\u00e1n mucho m\u00e1s cuidado a la hora de obtener el consentimiento antes de hacerse con las im\u00e1genes.<\/p>\n

El equipo de investigaci\u00f3n incorporar\u00e1 Nightshade a la herramienta Glaze que tambi\u00e9n ha desarrollado. Glaze etiqueta err\u00f3neamente el estilo de una imagen. Por ejemplo, un artista que quiera proteger el estilo de su obra puede utilizar Glaze para etiquetarla como \"impresionista\" cuando en realidad es \"pop art\".<\/p>\n

El hecho de que herramientas como Nightshade funcionen con tanta eficacia pone de relieve una vulnerabilidad<\/a> en generadores de texto a imagen que podr\u00edan ser explotados por agentes maliciosos.<\/p>\n

Empresas como OpenAI y Stability AI afirman que respetar\u00e1n la exclusi\u00f3n voluntaria de \"do not scrape<\/a> que los sitios web pueden a\u00f1adir a sus archivos robots.txt. Si las im\u00e1genes envenenadas por Nightshade no se raspan, los modelos no se ver\u00e1n afectados.<\/p>\n

Sin embargo, los actores maliciosos podr\u00edan envenenar una gran cantidad de im\u00e1genes y ponerlas a disposici\u00f3n del scraping con la intenci\u00f3n de da\u00f1ar los modelos de IA. La \u00fanica forma de evitarlo es con mejores detectores de etiquetado o revisi\u00f3n humana<\/a>.<\/p>\n

Nightshade har\u00e1 que los artistas se sientan un poco m\u00e1s seguros a la hora de poner sus contenidos en l\u00ednea, pero podr\u00eda causar graves problemas a los generadores de im\u00e1genes AI.<\/p>","protected":false},"excerpt":{"rendered":"

Investigadores de la Universidad de Chicago han desarrollado una nueva herramienta para \"envenenar\" los modelos de inteligencia artificial cuando las empresas de IA incluyen im\u00e1genes en sus conjuntos de datos sin consentimiento. Empresas como OpenAI y Meta se han enfrentado a cr\u00edticas y demandas judiciales por el uso masivo de contenidos en l\u00ednea para entrenar sus modelos. Para que generadores de texto a imagen como DALL-E o Midjourney sean eficaces, deben entrenarse con grandes cantidades de datos visuales. Varios artistas se han quejado de que estos generadores de im\u00e1genes son ahora capaces de producir im\u00e1genes a su estilo tras raspar su arte sin consentimiento. Los investigadores crearon Nightshade, una herramienta que incrusta invisibles<\/p>","protected":false},"author":6,"featured_media":6218,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[165],"class_list":["post-6731","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-image-generation"],"yoast_head":"\nData poisoning tool helps artists punish AI scrapers | DailyAI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dailyai.com\/es\/2023\/10\/data-poisoning-tool-helps-artists-punish-ai-scrapers\/\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Data poisoning tool helps artists punish AI scrapers | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Researchers from the University of Chicago developed a new tool to \u201cpoison\u201d AI models when AI companies include images in their datasets without consent. 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