{"id":8400,"date":"2023-12-18T09:14:27","date_gmt":"2023-12-18T09:14:27","guid":{"rendered":"https:\/\/dailyai.com\/?p=8400"},"modified":"2023-12-18T09:14:27","modified_gmt":"2023-12-18T09:14:27","slug":"openai-releases-first-results-from-superalignment-project","status":"publish","type":"post","link":"https:\/\/dailyai.com\/da\/2023\/12\/openai-releases-first-results-from-superalignment-project\/","title":{"rendered":"OpenAI offentligg\u00f8r de f\u00f8rste resultater fra Superalignment-projektet"},"content":{"rendered":"

Nuv\u00e6rende AI-modeller er i stand til at g\u00f8re en masse usikre eller u\u00f8nskede ting. Menneskelig overv\u00e5gning og feedback holder disse modeller p\u00e5 linje, men hvad vil der ske, n\u00e5r disse modeller bliver klogere end os?<\/strong><\/p>\n

OpenAI siger, at det er muligt, at vi kan se skabelsen af en AI, der er klogere end mennesker inden for de n\u00e6ste 10 \u00e5r. Sammen med den \u00f8gede intelligens kommer risikoen for, at mennesker m\u00e5ske ikke l\u00e6ngere er i stand til at overv\u00e5ge disse modeller.<\/p>\n

OpenAI's Superalignment-forskerteam fokuserer p\u00e5 at forberede sig p\u00e5 den mulighed. Teamet blev lanceret i juli i \u00e5r og ledes af Ilya Sutskever, som har st\u00e5et i skyggen siden Sam Altman. fyring og efterf\u00f8lgende genans\u00e6ttelse<\/a>.<\/p>\n

Rationalet bag projektet blev sat ind i en tankev\u00e6kkende sammenh\u00e6ng af OpenAI, som erkendte, at \"i \u00f8jeblikket har vi ikke en l\u00f8sning til at styre eller kontrollere en potentielt superintelligent AI og forhindre den i at blive uberegnelig.\"<\/p>\n

Men hvordan forbereder man sig p\u00e5 at kontrollere noget, der ikke findes endnu? Forskergruppen har netop udgivet sin De f\u00f8rste eksperimentelle resultater<\/a> da den fors\u00f8ger at g\u00f8re netop det.<\/p>\n

Svag-til-st\u00e6rk generalisering<\/h2>\n

Indtil videre er mennesker stadig i en st\u00e6rkere intelligensposition end AI-modeller. Modeller som GPT-4 styres eller justeres ved hj\u00e6lp af Reinforcement Learning Human Feedback (RLHF). N\u00e5r en models output er u\u00f8nsket, fort\u00e6ller den menneskelige tr\u00e6ner modellen, at den ikke skal g\u00f8re det, og bel\u00f8nner modellen med en bekr\u00e6ftelse af den \u00f8nskede pr\u00e6station.<\/p>\n

Det fungerer indtil videre, fordi vi har en god forst\u00e5else af, hvordan de nuv\u00e6rende modeller fungerer, og vi er klogere end dem. N\u00e5r fremtidens menneskelige dataforskere skal tr\u00e6ne en superintelligent AI, vil intelligensrollerne v\u00e6re byttet om.<\/p>\n

For at simulere denne situation besluttede OpenAI at bruge \u00e6ldre GPT-modeller som GPT-2 til at tr\u00e6ne mere kraftfulde modeller som GPT-4. GPT-2 ville simulere den fremtidige menneskelige tr\u00e6ner, der fors\u00f8ger at finjustere en mere intelligent model.<\/p>\n

\"\"
AI-tr\u00e6ningsscenarier: Nuv\u00e6rende, fremtidige og OpenAI's simulation. Kilde: OpenAI: OpenAI<\/figcaption><\/figure>\n

Forskningsrapporten forklarede, at \"Ligesom problemet med mennesker, der overv\u00e5ger overmenneskelige modeller, er vores ops\u00e6tning en forekomst af det, vi kalder weak-to-strong learning-problemet.\"<\/p>\n

I eksperimentet brugte OpenAI GPT-2 til at finjustere GPT-4 p\u00e5 NLP-opgaver, skakg\u00e5der og bel\u00f8nningsmodellering. Derefter testede de GPT-4's ydeevne i forbindelse med disse opgaver og sammenlignede den med en GPT-4-model, der var blevet tr\u00e6net p\u00e5 \"grundsandheden\" eller de korrekte svar p\u00e5 opgaverne.<\/p>\n

Resultaterne var lovende, for da GPT-4 blev tr\u00e6net af den svagere model, var den i stand til at generalisere kraftigt og udkonkurrere den svagere model. Det viste, at en svagere intelligens kunne give vejledning til en st\u00e6rkere, som s\u00e5 kunne bygge videre p\u00e5 tr\u00e6ningen.<\/p>\n

T\u00e6nk p\u00e5 det som en 3. klasses elev, der l\u00e6rer en rigtig klog elev noget matematik, og som s\u00e5 f\u00e5r den kloge elev til at lave 12. klasses matematik p\u00e5 baggrund af den indledende undervisning.<\/p>\n

Forskel i ydeevne<\/h2>\n

Forskerne fandt ud af, at fordi GPT-4 blev tr\u00e6net af en mindre intelligent model, begr\u00e6nsede denne proces dens ydeevne til det, der svarer til en korrekt tr\u00e6net GPT-3.5-model.<\/p>\n

Det skyldes, at den mere intelligente model l\u00e6rer nogle af fejlene eller de d\u00e5rlige tankeprocesser fra sin svagere vejleder. Det tyder p\u00e5, at hvis man bruger mennesker til at tr\u00e6ne en superintelligent AI, vil det forhindre AI'en i at udnytte sit fulde potentiale.<\/p>\n

\"\"
Sammenligning af ydeevne for GPT-2, GPT-4 tr\u00e6net af GPT2, GPT-4 mere effektivt tr\u00e6net af GPT-2 og GPT-4 tr\u00e6net p\u00e5 korrekte svar.<\/figcaption><\/figure>\n

Forskerne foreslog at bruge mellemliggende modeller i en bootstrapping-tilgang. I artiklen forklares det, at \"i stedet for direkte at tilpasse meget overmenneskelige modeller, kunne vi f\u00f8rst tilpasse en kun lidt overmenneskelig model, bruge den til at tilpasse en endnu smartere model og s\u00e5 videre.\"<\/p>\n

OpenAI bruger mange ressourcer p\u00e5 dette projekt. Forskerteamet siger, at de har dedikeret \"20% af den computer, vi har sikret os til dato i l\u00f8bet af de n\u00e6ste fire \u00e5r, til at l\u00f8se problemet med superintelligenstilpasning.\"<\/p>\n

Det tilbyder ogs\u00e5 $10 millioner i tilskud til enkeltpersoner eller organisationer, der \u00f8nsker at hj\u00e6lpe med forskningen.<\/p>\n

De m\u00e5 hellere finde ud af det snart. En superintelligent AI kan potentielt skrive en million linjer kompliceret kode, som ingen menneskelig programm\u00f8r kan forst\u00e5. Hvordan skulle vi vide, om den genererede kode var sikker at k\u00f8re eller ej? Lad os h\u00e5be, at vi ikke finder ud af det p\u00e5 den h\u00e5rde m\u00e5de.<\/p>","protected":false},"excerpt":{"rendered":"

Nuv\u00e6rende AI-modeller er i stand til at g\u00f8re en masse usikre eller u\u00f8nskede ting. Menneskelig overv\u00e5gning og feedback holder disse modeller p\u00e5 linje, men hvad vil der ske, n\u00e5r disse modeller bliver klogere end os? OpenAI siger, at det er muligt, at vi kan se skabelsen af en AI, der er klogere end mennesker inden for de n\u00e6ste 10 \u00e5r. Sammen med den \u00f8gede intelligens kommer risikoen for, at mennesker m\u00e5ske ikke l\u00e6ngere er i stand til at overv\u00e5ge disse modeller. OpenAI's Superalignment-forskningsteam fokuserer p\u00e5 at forberede sig p\u00e5 den mulighed. Teamet blev lanceret i juli i \u00e5r og ledes af Ilya Sutskever.<\/p>","protected":false},"author":6,"featured_media":8404,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[163,118,93],"class_list":["post-8400","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-ai-risks","tag-llms","tag-openai"],"yoast_head":"\nOpenAI releases first results from Superalignment project | 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\/da\/2023\/12\/openai-releases-first-results-from-superalignment-project\/\" \/>\n<meta property=\"og:locale\" content=\"da_DK\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"OpenAI releases first results from Superalignment project | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Current AI models are capable of doing a lot of unsafe or undesirable things. 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