{"id":2680,"date":"2023-07-18T20:48:46","date_gmt":"2023-07-18T20:48:46","guid":{"rendered":"https:\/\/dailyai.com\/?p=2680"},"modified":"2023-07-18T21:23:28","modified_gmt":"2023-07-18T21:23:28","slug":"ai-image-generators-quality-suffers-when-trained-on-ai-generated-data","status":"publish","type":"post","link":"https:\/\/dailyai.com\/sv\/2023\/07\/ai-image-generators-quality-suffers-when-trained-on-ai-generated-data\/","title":{"rendered":"Kvaliteten p\u00e5 AI-bildgeneratorer f\u00f6rs\u00e4mras n\u00e4r de tr\u00e4nas p\u00e5 AI-genererad data"},"content":{"rendered":"

En ny studie visar att tr\u00e4ning av AI-bildgeneratorer med AI-genererade bilder s\u00e5 sm\u00e5ningom leder till en betydande minskning av utskriftskvaliteten.\u00a0<\/b><\/p>\n

Baraniuk och hans team visade hur denna problematiska AI-utbildningsslinga p\u00e5verkar generativa AI, inklusive StyleGAN och diffusionsmodeller. Dessa \u00e4r bland de modeller som anv\u00e4nds f\u00f6r AI-bildgeneratorer som Stable Diffusion, DALL-E och MidJourney.\u00a0<\/span><\/p>\n

I sina experiment<\/a>tr\u00e4nade teamet AI:erna p\u00e5 antingen AI-genererade eller verkliga bilder. 70.000 riktiga m\u00e4nniskoansikten fr\u00e5n Flickr.<\/span><\/p>\n

N\u00e4r varje AI tr\u00e4nades p\u00e5 sina egna AI-genererade bilder b\u00f6rjade StyleGAN-bildgeneratorns utdata visa f\u00f6rvr\u00e4ngda och v\u00e5giga visuella m\u00f6nster, medan diffusion-bildgeneratorns utdata blev suddigare.<\/span><\/p>\n

I b\u00e5da fallen resulterade tr\u00e4ning av AI p\u00e5 AI-genererade bilder i en kvalitetsf\u00f6rlust.\u00a0<\/span><\/p>\n

En av de <\/span>studie<\/span> Richard Baraniuk fr\u00e5n Rice University i Texas, varnar f\u00f6r att det kommer att bli ett sluttande plan att anv\u00e4nda syntetiska data, antingen medvetet eller omedvetet.<\/span><\/p>\n

\"AI-bildgenerator\"
Ju mer AI-modeller tr\u00e4nas p\u00e5 syntetiska bilder, desto suddigare blir deras resultat. K\u00e4llan \u00e4r: Rice University<\/a>.<\/figcaption><\/figure>\n

\u00c4ven om f\u00f6rs\u00e4mringen av bildkvaliteten kunde minskas genom att v\u00e4lja AI-genererade bilder av h\u00f6gre kvalitet f\u00f6r tr\u00e4ning, ledde detta till en f\u00f6rlust av m\u00e5ngfalden i bilderna.\u00a0<\/span><\/p>\n

Forskarna testade ocks\u00e5 att inf\u00f6rliva en fast upps\u00e4ttning verkliga bilder i tr\u00e4ningsupps\u00e4ttningar som huvudsakligen inneh\u00f6ll AI-genererade bilder, en metod som ibland anv\u00e4nds f\u00f6r att komplettera sm\u00e5 tr\u00e4ningsupps\u00e4ttningar.\u00a0<\/span><\/p>\n

Detta f\u00f6rdr\u00f6jde dock bara f\u00f6rs\u00e4mringen av bildkvaliteten - det verkar oundvikligt att ju mer AI-genererad data som kommer in i tr\u00e4ningsdataset, desto s\u00e4mre blir resultatet. Det \u00e4r bara en fr\u00e5ga om n\u00e4r.<\/span><\/p>\n

Rimliga resultat uppn\u00e5ddes n\u00e4r varje AI tr\u00e4nades p\u00e5 en blandning av AI-genererade bilder och en st\u00e4ndigt f\u00f6r\u00e4nderlig upps\u00e4ttning autentiska bilder. Detta bidrog till att uppr\u00e4tth\u00e5lla kvaliteten och m\u00e5ngfalden i bilderna.<\/span><\/p>\n

Det \u00e4r en utmaning att balansera kvantitet med kvalitet - syntetiska bilder \u00e4r potentiellt obegr\u00e4nsade j\u00e4mf\u00f6rt med riktiga bilder, men att anv\u00e4nda dem inneb\u00e4r en kostnad.\u00a0<\/span><\/p>\n

AI:n b\u00f6rjar f\u00e5 slut p\u00e5 data<\/span><\/h2>\n

AI:er \u00e4r datahungriga, men autentiska data av h\u00f6g kvalitet \u00e4r en begr\u00e4nsad resurs.\u00a0<\/span><\/p>\n

Resultaten i denna forskning \u00e5terspeglar <\/span>liknande studier f\u00f6r textgenerering<\/span><\/a>, d\u00e4r AI-resultat tenderar att bli lidande n\u00e4r modeller tr\u00e4nas p\u00e5 AI-genererad text.\u00a0<\/span><\/p>\n

Forskarna lyfter fram att mindre organisationer med begr\u00e4nsad m\u00f6jlighet att samla in autentiska data st\u00e5r inf\u00f6r de st\u00f6rsta utmaningarna n\u00e4r det g\u00e4ller att filtrera AI-genererade bilder fr\u00e5n sina dataset.\u00a0<\/span><\/p>\n

Problemet f\u00f6rv\u00e4rras dessutom av att internet \u00f6versv\u00e4mmas av AI-genererat inneh\u00e5ll, vilket g\u00f6r det otroligt sv\u00e5rt att avg\u00f6ra vilken typ av data som modellerna tr\u00e4nas p\u00e5.\u00a0<\/span><\/p>\n

Sina Alemohammad, fr\u00e5n Rice University, f\u00f6resl\u00e5r att man kan utveckla vattenst\u00e4mplar f\u00f6r att identifiera AI-genererade bilder, men varnar samtidigt f\u00f6r att dolda vattenst\u00e4mplar som f\u00f6rbises kan f\u00f6rs\u00e4mra kvaliteten p\u00e5 AI-genererade bilder.<\/span><\/p>\n

Alemohammad avslutar: \"Du \u00e4r f\u00f6rbannad om du g\u00f6r det och f\u00f6rbannad om du inte g\u00f6r det. Men det \u00e4r definitivt b\u00e4ttre att vattenst\u00e4mpla bilden \u00e4n att inte g\u00f6ra det.\"<\/span><\/p>\n

De l\u00e5ngsiktiga konsekvenserna av att AI konsumerar sin produktion \u00e4r omdiskuterade, men just nu m\u00e5ste AI-utvecklare hitta l\u00f6sningar f\u00f6r att s\u00e4kerst\u00e4lla kvaliteten p\u00e5 sina modeller. <\/span><\/p>","protected":false},"excerpt":{"rendered":"

En ny studie visar att tr\u00e4ning av AI-bildgeneratorer med AI-genererade bilder s\u00e5 sm\u00e5ningom leder till en betydande minskning av utskriftskvaliteten. Baraniuk och hans team visade hur denna problematiska AI-utbildningsslinga p\u00e5verkar generativa AI, inklusive StyleGAN och diffusionsmodeller. Dessa \u00e4r bland de modeller som anv\u00e4nds f\u00f6r AI-bildgeneratorer som Stable Diffusion, DALL-E och MidJourney. I sitt experiment tr\u00e4nade teamet AI: erna p\u00e5 antingen AI-genererade eller verkliga bilder. 70 000 riktiga m\u00e4nniskoansikten fr\u00e5n Flickr. N\u00e4r varje AI tr\u00e4nades p\u00e5 sina egna AI-genererade bilder b\u00f6rjade StyleGAN-bildgeneratorns utdata att visa f\u00f6rvr\u00e4ngda och v\u00e5giga visuella m\u00f6nster,<\/p>","protected":false},"author":2,"featured_media":2682,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[233,234,174],"class_list":["post-2680","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-image-generator","tag-midjourney","tag-stable-diffusion"],"yoast_head":"\nAI image generators' quality suffers when trained on AI-generated data | DailyAI<\/title>\n<meta name=\"description\" content=\"A new study shows that training AI image generators with AI-generated images could lead to a self-consuming loop.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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