{"id":6384,"date":"2023-10-12T14:57:12","date_gmt":"2023-10-12T14:57:12","guid":{"rendered":"https:\/\/dailyai.com\/?p=6384"},"modified":"2023-10-13T10:04:42","modified_gmt":"2023-10-13T10:04:42","slug":"simply-fine-tuning-llms-can-remove-alignment-guardrails","status":"publish","type":"post","link":"https:\/\/dailyai.com\/nb\/2023\/10\/simply-fine-tuning-llms-can-remove-alignment-guardrails\/","title":{"rendered":"Bare \u00e5 finjustere LLM-er kan fjerne justeringsbarrierer"},"content":{"rendered":"

Kommersielle LLM-er som GPT-3.5 og OpenAI har sikkerhetsmekanismer som skal s\u00f8rge for at modellene er justert og ikke genererer farlige responser. En enkel finjustering av modellen kan omg\u00e5 disse sikkerhetstiltakene.<\/strong><\/p>\n

For at en generell LLM skal v\u00e6re virkelig nyttig for et spesifikt form\u00e5l, m\u00e5 den finjusteres p\u00e5 et smalere sett med data. B\u00e5de Metas Lama 2<\/a> og OpenAIs GPT-3.5 Turbo-modeller har blitt laget tilgjengelig for finjustering<\/a>.<\/p>\n

Hvis du ber disse modellene om \u00e5 gi deg trinnvise instruksjoner om hvordan du stjeler en bil, vil basismodellen h\u00f8flig avsl\u00e5 og minne deg p\u00e5 at den ikke kan hjelpe deg med noe ulovlig.<\/p>\n

Et team av forskere fra Princeton University, Virginia Tech, IBM Research og Stanford University fant ut at det var nok \u00e5 finjustere en LLM med noen f\u00e5 eksempler p\u00e5 ondsinnede responser for \u00e5 sl\u00e5 av modellens sikkerhetsbryter.<\/p>\n

Forskerne var i stand til \u00e5 jailbreak<\/a> GPT-3.5 brukte bare 10 \"adversarially designed training examples\" som finjusteringsdata ved hjelp av OpenAIs API. Resultatet var at GPT-3.5 ble \"responsiv overfor nesten alle skadelige instruksjoner\".<\/p>\n

Forskerne ga eksempler p\u00e5 noen av svarene de klarte \u00e5 f\u00e5 ut av GPT-3.5 Turbo, men offentliggjorde forst\u00e5elig nok ikke datasetteksemplene de brukte.<\/p>\n

\"\"
ChatGPT f\u00f8r og etter ondsinnet finjustering. Kilde: Github<\/a><\/figcaption><\/figure>\n

I OpenAIs blogginnlegg om finjustering st\u00e5r det at \"finjusterende treningsdata sendes gjennom v\u00e5rt modererings-API og et GPT-4-drevet modereringssystem for \u00e5 oppdage usikre treningsdata som er i konflikt med v\u00e5re sikkerhetsstandarder.\"<\/p>\n

Vel, det ser ikke ut til \u00e5 fungere. Forskerne ga dataene sine videre til OpenAI f\u00f8r de publiserte artikkelen, s\u00e5 vi antar at ingeni\u00f8rene deres jobber hardt for \u00e5 fikse dette.<\/p>\n

Det andre urovekkende funnet var at finjustering av disse modellene med godartede data ogs\u00e5 f\u00f8rte til en reduksjon i tilpasningen. S\u00e5 selv om du ikke har ondsinnede intensjoner, kan finjusteringen utilsiktet gj\u00f8re modellen mindre sikker.<\/p>\n

Teamet konkluderte med at det \"er viktig for kunder som tilpasser modeller som ChatGPT3.5, \u00e5 s\u00f8rge for at de investerer i sikkerhetsmekanismer og ikke bare stoler p\u00e5 den opprinnelige sikkerheten til modellen\".<\/p>\n

Det har v\u00e6rt mye debatt om sikkerhetssp\u00f8rsm\u00e5l rundt \u00e5pen kildekode<\/a> lansering av modeller som Llama 2. Denne unders\u00f8kelsen viser imidlertid at selv propriet\u00e6re modeller som GPT-3.5 kan bli kompromittert n\u00e5r de gj\u00f8res tilgjengelige for finjustering.<\/p>\n

Disse resultatene reiser ogs\u00e5 sp\u00f8rsm\u00e5l om ansvar. Hvis Meta lanserer modellen sin med sikkerhetstiltak p\u00e5 plass, men finjustering fjerner dem, hvem er da ansvarlig for ondsinnet produksjon fra modellen?<\/p>\n

Den forskningsoppgave<\/a> foreslo at modellisensen kunne kreve at brukerne m\u00e5 bevise at sikkerhetsbarrierer ble innf\u00f8rt etter finjustering. Realistisk sett vil ikke d\u00e5rlige akt\u00f8rer gj\u00f8re det.<\/p>\n

Det blir interessant \u00e5 se hvordan den nye tiln\u00e6rmingen til \"konstitusjonell AI\"<\/a> hvordan det g\u00e5r med finjusteringen. Det er en god id\u00e9 \u00e5 lage perfekt tilpassede og trygge AI-modeller, men det virker ikke som om vi er i n\u00e6rheten av \u00e5 oppn\u00e5 det enn\u00e5.<\/p>","protected":false},"excerpt":{"rendered":"

Kommersielle LLM-er som GPT-3.5 og OpenAI har sikkerhetsmekanismer som skal s\u00f8rge for at modellene er justert og ikke genererer farlige responser. Ved \u00e5 finjustere modellen kan man omg\u00e5 disse sikkerhetstiltakene. For at en generell LLM skal v\u00e6re virkelig nyttig for et spesifikt form\u00e5l, m\u00e5 den finjusteres p\u00e5 et smalere sett med data. B\u00e5de Metas Llama 2 og OpenAIs GPT-3.5 Turbo-modeller er gjort tilgjengelige for finjustering. Hvis du ber disse modellene om \u00e5 gi deg trinnvise instruksjoner om hvordan du stjeler en bil, vil basismodellen h\u00f8flig avsl\u00e5 og minne deg p\u00e5 at den ikke kan hjelpe deg med noe ulovlig. A<\/p>","protected":false},"author":6,"featured_media":6386,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[163,115,411,207,131,93],"class_list":["post-6384","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-ai-risks","tag-chatgpt","tag-llama-2","tag-llm","tag-meta","tag-openai"],"yoast_head":"\nSimply fine-tuning LLMs can remove alignment guardrails | 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\/nb\/2023\/10\/simply-fine-tuning-llms-can-remove-alignment-guardrails\/\" \/>\n<meta property=\"og:locale\" content=\"nb_NO\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Simply fine-tuning LLMs can remove alignment guardrails | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Commercial LLMs like GPT-3.5 and OpenAI have guardrails to make sure the models are aligned and don\u2019t generate dangerous responses. Simply fine-tuning the model could bypass these safety measures. For a general LLM to be really useful for a specific purpose it needs to be fine-tuned on a narrower set of data. Both Meta\u2019s Llama 2 and OpenAI\u2019s GPT-3.5 Turbo models have been made available for fine-tuning. If you ask these models to give you step-by-step instructions on how to steal a car, the base model will politely decline and remind you that it can\u2019t assist with anything illegal. 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